Displays

To understand the dynamics-physics-chemistry processes of the whole atmosphere, from earth surface to lower thermosphere, a synthetic observation system was established over the Tibetan Plateau at the end of 2017. This system consists of 5 lidars, 2-micrometer wave cloud radars, a THz spectrometer, and a set of surface meteorological observation instruments as well as atmospheric environmental instruments. The system, we call it as APSOS, is located in central Tibet, Yangbajing, at the altitude of 4300m ASL. During the last 2 years, quasi-continuous observations are made for different realms. A set of observation data have been collected for future analysis. Some of the system ability and case study has been achieved and further work plan will be presented in this paper.

How to cite: Lyu, D., Wang, Y., Pan, W., Xuan, Y., Wang, X., Tian, Y., and Bi, Y.: Recent Progress of APSOS-Tibet System Observation-Current Status and Future Plan, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-2808, https://doi.org/10.5194/egusphere-egu2020-2808, 2020.

National Tibetan Plateau Data Center (TPDC) is one of the first 20 national data centers authorized by the Ministry of Science and Technology of China in 2019 . It is the only data center in China with the most complete scientific data for the Tibetan Plateau and surrounding regions. There are more than 1700 datasets covering many disciplines such as geography, atmospheric science, cryospheric science, hydrology, ecology, geology, geophysics, natural resource science, social economy, and other fields. All data are sorted and integrated in a strict way accordance with the data standards specified by TPDC and the relevant data acquisition specifications. The mission of the data center is to establish a big data center for Third-Pole Earth System Sciences to integrate ThirdPole data resources, particularly those obtained through the implementation of the Third-Pole "Super Monitoring" plan; to develop cutting edge observation technology for extreme environments; and to build a comprehensive and intelligent Internet of Things (IoT) observation system for the Pan-Third Pole region. These developments will facilitate the modeling of environmental changes in the Pan-Third Pole with improved accuracy and performance, as well as support decision-making for sustainable development of the Pan-Third Pole region.

TPDC complies with the “findable, accessible, interoperable and reusable (FAIR)” data sharing principles, in which, the scientific data and metadata can be 'findable' by anyone for exploring and using, can be 'accessible' for being examined, can be 'interoperable' for being analyzed and integrated with comparable data through the use of common vocabulary and formats, can be 'reusable' for public as a result of robust metadata, provenance information and clear usage license. Under the guidance of FAIR data sharing principle, Pan-Third big data system provides online sharing manner for data users, supplemented by offline sharing manner, with bilingual data sharing in Chinese and English.

TPDC has joined WMO (World Meteorological Organization) to promote the project of Integrated Global Cryosphere Information System (IGCryoIS), aiming to collect and share multi-source data in global regions where data is difficult to obtain. Recently TPDC and NSIDC (National Snow and Ice Data Center) officially signed a memorandum of collaboration on data sharing and research to start comprehensive cooperation. TPDC is strengthening cooperation with the international data organizations (e.g. CODATA, WDS) and providing data support for the international science programs of the Tibetan Plateau (e.g. TPE, ANSO). TPDC is applying to become a recommended data repository for the international mainstream journals so as to encourage data authors to share their well-documented, useful and preserved data by giving them credit and recognition.

 In a word, TPDC stores, integrates, analyses, excavates and publishes scientific data such as resources, environment, ecology and atmosphere in Pan-third polar region, gathers Pan-third polar core data resources, forms Pan-third polar key scientific data products, and gradually develops online large data analysis, model application and other functions. Furthermore, a cloud service platform will be built for the extensive integration of data, methods, models and services in Pan-Third Pole Science and to promote the application of large data methods in Pan-Third Pole Science Research.

How to cite: Li, X., Pan, X., Guo, X., Niu, X., Yang, X., Feng, M., Che, T., Jin, R., Ran, Y., and Guo, J.: National Tibetan Plateau Data Center, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-1710, https://doi.org/10.5194/egusphere-egu2020-1710, 2020.

Wetlands are “hot spot” area of global climate change, which are obviously sensitive to climate change. Under climate change, the carbon sequestration potential and carbon balance over wetland ecosystems are greatly altered, and large uncertainties are still existed in carbon budgets over these areas. Tengchong Beihai wetland is the only highland “floating blanket” lake wetland which is located in Southwest of China. As this land surface is composed by both water and terrestrial land surface, it’s doubted whether this type of wetland behaves more like lake or the latter one. Based on one year continuous observation measured with eddy covariance technique over Beihai wetland and Erhai Lake in 2016, the patterns of CO₂ flux and energy fluxes over Tengchong wetland and Erhai lake are analyzed. The results show the diurnal variation of H and LE are both similar to Rn, which is different with Erhai lake. Erhai lake has a higher evaporation rate even in nighttime, which is much larger than Beihai wetland, due to the “floating blanket” vegetation could obviously reduce the evaporation rate. Beihai wetland acts as CO₂ sink for the most time of the year, with an annual CO₂ flux of -202.2 g C m^-2, while Erhai Lake acted as CO₂ source with an annual CO₂ flux of 143.7 g C m^-2. The results indicate the carbon and water exchange process in Beihai wetland behaves more like vegetated land surface.

How to cite: Du, Q., Liu, H., Liu, Y., and Xu, L.: The Comparison of turbulent fluxes between a marsh wetland and a lake ecosystem, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-3236, https://doi.org/10.5194/egusphere-egu2020-3236, 2020.

Many model results showed obvious wet biases during winter while the simulation was good during summer over the Tibetan Plateau (TP). Low gauge density and the limited capacity of snowfall may introduce dry biases into the observation and then exaggerate the overestimation of winter precipitation. To evaluate the winter precipitation products over the TP, we compared six precipitation products, including TRMM, ERA5, ERA-Interim, GLDAS, HAR, and the observation provided by China Meteorological Administration (CMA), against a sublimation dataset derived from remotely sensed snow cover data. The Kuzmin formula constrained with IMS snow cover product and land surface temperature was used to estimate sublimation. To ensure the reliability of the sublimation value, the accuracy of the simulated sublimation value was verified by the sublimation value observed at the pass area of Dadongshu Station and the consistency of two snow cover products was verified by using MODIS daily cloud-free snow cover products over the Tibetan Plateau.

The comparison revealed that the average underestimated area ratio of CMA on the TP and the Inner TP respectively were about 60% and 90%. CMA has an obvious underestimation (80% region showed underestimation and precipitation underestimation ratio mostly more than 100%) in the west of TP where lack of observation site. However, there was not obvious underestimation in East TP because of the dense stations available. It implies that the observation data has considerable dry biases (~200%) in winter precipitation over the Western TP where more ground stations are needed to get a reliable precipitation observation. For other precipitation products, HAR showed the smallest underestimation with a 12% region of precipitation underestimation. ERA5 and ERA-Interim are close behind HAR, but the underestimation area ratio of ERA5 was about 15% smaller than ERA-Interim in each statistical area of TP. TRMM and GLDAS show comparable underestimation and both are more apparent than ERA-interim. The underestimation phenomenon of TRMM shows little difference in the western and eastern TP and the underestimated area ratio of TRMM was 64.68% on the TP.

How to cite: Lu, H., Zhou, J., and Yang, K.: Evaluation of Winter Precipitation Products over the Tibetan Plateau with the Sublimation derived from Remotely Sensed Snow Cover Data, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-6230, https://doi.org/10.5194/egusphere-egu2020-6230, 2020.

In the Pliocene, the Qaidam Basin in the northeastern Tibetan Plateau contained a freshwater mega-lake system. The lake system disappeared and the lower parts of the basin now feature hyperarid conditions. What led to the collapse of the lake system and could it appear again in the future? Understanding the sensitivity of the basin’s water balance to changes in atmospheric conditions is crucial for answering this question. We employed the Weather Research and Forecasting model for the dynamical downscaling of two time slices. These were simulated by ECHAM5-wiso atmospheric general circulation model under different boundary conditions, representing present day and Pliocene climate. We present a comparison study analyzing how the basin‘s water balance changes, when we put the Qaidam basin catchment area with its modern geographical features into the Pliocene climate environment. Furthermore, we investigate large scale controls of the basin’s water balance. We find that (1) the Basin’s water balance is more positive or less negative under Pliocene climate; (2) the atmospheric water transport from the west into the basin to be stronger under Pliocene than under present day conditions except for the summer months, while at the same time the influence of the Indian Summer Monsoon is weaker. The analysis suggests that minor changes in atmospheric boundary conditions can have substantial effects on the basin’s water balance.

How to cite: Schmidt, B., Wang, X., Mutz, S., Botsyun, S., Ehlers, T., and Scherer, D.: Changes in water balance of the Qaidam Basin from Pliocene to present day, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-20666, https://doi.org/10.5194/egusphere-egu2020-20666, 2020.

Convective momentum transport (CMT) measurements are scarce, but important to constrain the impacts of CMT on wind profiles, variability of the wind and possibly the large-scale circulation.

We investigate how wind profiles and momentum fluxes change with cloudiness and convection. With stronger convection, we expect that the wind shear in the lowest 200m, wherein wind turbines are located, reduces. Cumulus days are generally strongly convective and hence well mixed. They are expected to differ from clear-sky days: the boundary layer is deeper, and cumulus may induce a different (thermal) circulation in the sub-cloud layer. Comparing cumulus and other days fairly, we must be mindful of the changes in convection strength with cloud cover, time of the day, seasons, and the wind strength that impacts the wind shear magnitude.

This study uses nine years of data from the Cabauw observatory, The Netherlands, containing 10-minute averages of wind speed, wind direction, and momentum fluxes from a 200 m tall tower along with cloud-base heights from a ceilometer. Realistic fine-scale Large Eddy Simulation (LES) hindcasts over the same time period and a 5km³ domain over Cabauw provide insight into the processes at higher altitude. In both observations and LES, days with rooted clouds, which have strong connection to the sub-cloud layer, are separated from clear-sky days and days in which clouds only impact the convection through radiation effects. Days with rooted clouds are subsequently divided into three groups of increasing cloud cover: 5-30% (shallow clouds), 30-70% (somewhat deeper clouds) and >70% (overcast).

Both observations and LES show that shear in the near-surface wind speed (NSWS) reduces with stronger insolation, which is expected: more insolation causes a more unstable atmosphere, stronger convection, thus more mixing. In a weakly unstable atmosphere, rooted clouds (5-70% cloud cover) generally have better mixed winds (less normalised shear). The NSWS accelerates more from morning to afternoon on these days, indicating that not only the mixing is stronger, but also that downward mixing of higher momentum by the clouds affects the wind in the lowest 200m. If this is true, the assumption of Monin-Obukhov Similarity Theory (MOST) that large convective eddies are not important in the surface layer, does not hold. This possibly has a great impact on surface-flux parametrizations based on MOST, which are used by many numerical models, from local and mesoscale to global models. Analysing surface-layer scaling for momentum, we test whether this assumption is indeed violated in such cases.

Momentum transport profiles in LES show that when deeper clouds with larger cloud cover are present, transport in the cloud layer is larger. In the cross-wind component of the profile, the four categories show different deceleration in the mixed layer, and different acceleration near the top of the mixed layer. Likely, the stronger inversion-jump in the cross-wind causes this momentum flux character.

With this study, we provide an overview of the effects that have been observed in different cloudiness and convective conditions and gained understanding of the important processes and implications of the cloud effects on momentum transport.

How to cite: Koning, M., Nuijens, L., Bosveld, F., Siebesma, P., Verzijlbergh, R., and Jonker, H.: Observed influence of moist convection and cloudiness on boundary layer wind and momentum flux profiles. , EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-5155, https://doi.org/10.5194/egusphere-egu2020-5155, 2020.

Climatic-triggered natural hazards such as landslides and glacier lake outburst floods pose a threat to human lives in the third pole region. Availability of accurate climate data with high spatial and temporal resolution is crucial for better understanding climatic triggering mechanisms of these localized natural hazards. Within the framework of the project “Climatic and Tectonic Natural Hazard in Central Asia” (CaTeNA), High Asia Refined analysis version 2 (HAR v2) is under production, and is freely available upon request. HAR v2 is a regional atmospheric data set generated by dynamical downscaling of global ERA5 reanalysis data using the Weather Research and Forecasting (WRF) model. Compared to its predecessor (HAR), HAR v2 has an extended 10 km domain covering the Tibetan Plateau and the surrounding mountains, as well as a longer temporal coverage. It will be extended back to 1979, and will be continuously updated in the future. This presentation will contain the following aspects: (1) summarizing the WRF configuration; (2) validating HAR v2 against observational data; (3) comparing HAR v2 with other gridded data sets, such as the newly developed ERA5-Land reanalysis data; (4) providing information about data format, variable list, data access, etc.  

How to cite: Wang, X., Tolksdorf, V., Otto, M., and Scherer, D.: High Asia Refined Analysis Version 2 (HAR v2): a New Atmospheric Data Set for the Third Pole Region, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-8756, https://doi.org/10.5194/egusphere-egu2020-8756, 2020.

The Tibetan Plateau is one of the most important high elevation areas on the earth, performing sensitive response to global changes. As the Asia water tower, high mountain melting water is important water supplies for human development in TP and surrounded areas, but water phase transition is less known, especially under the climatic warming. Lakes are links of water phase transition and water cycle in TP. Lake water storage variations are sensitive to precipitation differentiations in the domination of the Westerlies and Indian monsoon. However, lake water storage performs inconsistent response in different regions & time periods. Based upon water balance observation, lake water storage variations are influenced by different factors, which also changed during different time period. Lake water temperature and thermoclines vary with seasons, and change water temperature gradient which influence water-air heat exchange. Lake salinities generally decreased since 1970s in the Serling Co region due to increasing of water storage. Based upon more than 60 lakes monitoring correction, it is found that lake transparency generally increased during 2000-2017 inferred by remote sensing interpretation. To aim at the deep recognizing of interactions between lake water variations and climatic changes, we need to know lake water storages and their variations for whole region and consecutive time series. To understand how heat exchanges between changing lakes and atmosphere, we need more consecutive observation data from large lakes. Therefore, the proposed work is to finish more lake survey and water balance monitoring, and continue to improve water cycling studies in the large lake basin scale for deep understanding how water cycles accompanied with mass and nutrients under the warming climatic conditions.

How to cite: Zhu, L., Qiao, B., Yang, R., Liu, C., Wang, J., and Ju, J.: The role of lakes in water cycling on the Tibetan Plateau under warming climate, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-6832, https://doi.org/10.5194/egusphere-egu2020-6832, 2020.

The change in spatial-temporal distribution of seasonally frozen ground (SFG) is an important indicator of climate change. Based on observed daily freeze depth of SFG from meteorological stations on the Tibetan Plateau (TP) from 1960 to 2014, the spatial-temporal characteristics and  trends in SFG were analyzed, and the relationships between them and climatic and geographical factors were explored. Spatial-temporal distribution of SFG on a regional scale was assessed by multiple regression functions. Results showed multi-year mean maximum freeze depth, freeze-thaw duration, freeze start date, and thaw end date demonstrate obvious distribution characteristics of climatic zones. A decreasing trend in maximum freeze depth and freeze-thaw duration occurred on the TP from 1960 to 2014. The freeze start date has been later and the thaw end date has been significantly earlier. Warming and wetting conditions of the soil resulted in a decrease in the maximum freeze depth and freeze-thaw duration, both spatially and temporally. The spatial distribution of SFG has been altered significantly by soil thermal conditions on the TP and could be assessed by elevation and latitude or by air temperature and precipitation, due to their high correlations. The regional average of maximum freeze depth and freeze-thaw duration caused by climatic and geographical factors was larger than those averaged using meteorological station data because most stations are located at lower altitudes. Maximum freeze depth and freeze-thaw duration has decreased sharply since 2000 on the entire TP.

How to cite: Luo, S.: Spatial-Temporal Distribution and Change of Seasonally Frozen Ground on the Tibetan Plateau from 1960 to 2014, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-4050, https://doi.org/10.5194/egusphere-egu2020-4050, 2020.

Soil temperature, soil water content and soil thermal properties were measured in an artificial forestland and a natural regrowth grassland from November in 2017 to July in 2019. The results show that the effects of soil temperature and soil water content on thermal properties are different in different soil condition. Soil thermal conductivity (K) and soil volumetric heat capacity (C) increase with increasing temperature in unfrozen period, but soil diffusivity (D) has no significant dynamic cycle and it almost keeps a constant level in a certain time. Soil thermal conductivity (K) decreases with increasing temperature during soil frozen period. The C and K increase with increasing soil water content in unfrozen period, while the D decrease with increasing soil water content.

How to cite: Zhang, T. and Ma, X.: The effect of soil temperature and soil water content on thermal properties in an artificial forestland and a natural regrowth grassland, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-9352, https://doi.org/10.5194/egusphere-egu2020-9352, 2020.

Arctic amplification leads to rapid changes in the terrestrial water and energy balances at high northern latitudes. Advances in Earth System Models (ESMs) is improving our understanding of the underlying feedback mechanisms leading to these changes. The representation of the land surface in ESMs is essential to simulate and understand changes at the global and regional scales. The latest version of the land component of the Norwegian Earth System Model (NorESM), namely the Community Land Model (CLM5), has received substantial new implementations to help simulate the land surface processes in cold environments. At the same time, the behaviour of offline CLM5 simulations and new observational data sets have not been systematically compared over Scandinavian regions. In this study, we run the CLM5 model at relatively high resolution (0.25 degrees) over Scandinavia (including Svalbard) for 15 years between 2002 and 2016. We evaluate the water and energy budget components of CLM5 using several reanalyses and satellite-based observational data sets. In particular, we use monthly model outputs and compare with the satellite retrievals from GRACE, MODIS, AMSR2, and AMSR-E, and reanalysis data sets from ERA5, GLDAS, and MERRA-2. As an additional data source, we use the local‐scale measurements obtained from the Finse Eco-Hydrological Observatory (Finse EcHO) at 1200 m a.s.l, and the high-Arctic research site at Bayelva near Ny-Ålesund, Svalbard. Our investigation is focused on several variables including terrestrial water storage, snow water equivalent, turbulent fluxes, net radiation, and skin temperature. The results indicate that the perceived performance of the land surface model (CLM5) depends strongly on the reference observational data set. Regional discrepancies between data sets, particularly for Svalbard, prompts further investigation of the underlying sources of uncertainty. The results of this evaluation provide a valuable source of information for future studies in the region, particularly in the Land-ATmosphere Interactions in Cold Environments (LATICE) project, which focuses on cold region land surface dynamics, integrating across observational systems, laboratory experiments, field, and modeling efforts.

Acknowledgement : This study is conducted under the LATICE strategic research initiative funded by the Faculty of Mathematics and Natural Sciences at the University of Oslo, and the project EMERALD (294948) funded by the Research Council of Norway.

How to cite: Yılmaz, Y. A., Tallaksen, L. M., and Stordal, F.: Hydroclimatological evaluation of CLM5 simulations using multiple data sources for land-atmosphere interaction studies over Scandinavia, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-7247, https://doi.org/10.5194/egusphere-egu2020-7247, 2020.

Nam Co Lake is the third largest salt lake in China. Nam Co Lake is a typical inland salt lake and a typical representative area of the complex topography of the Tibetan Plateau. In this study, the effects of Nam Co Lake on the short-term climate in the lake area are analyzed using the Weather Research and Forecasting (WRF) model in conjunction with field observation data for the Nam Co Lake area through a control experiment on the Nam Co Lake area and a sensitivity experiment on the same area without the presence of Nam Co Lake. Moreover, a backward water vapor transfer model is also employed to investigate the contribution of water vapor evaporation (transpiration) from this typical plateau lake and various types of surfaces to local precipitation. The following conclusions are derived: (1) After the removal of the lake, the sensible heat in the original lake area increases, whereas the latent heat decreases. The sum of the sensible and latent heat in the lake area simulated with and without the presence of the lake is 187.6 and 116.7 W·m^-2, respectively. (2)After the removal of the lake, precipitation in the central Nam Co Lake area increases significantly, generally by more than 20–30 mm. The presence of Nam Co Lake effectively reduces the height of the ABL over the lake during the day. (3) Approximately 76.93% of the total precipitation in the Nam Co Lake area is contributed by external water vapor sources. Evapotranspiration from grassland surfaces is the secondary water vapor source for precipitation in the study area and 18.34% of the total precipitation is contributed by this source. Approximately 2.46% of the total precipitation in the lake area is contributed by evaporation from Nam Co Lake.

How to cite: yang, X.: Lake-atmospheric Interaction and its Impact on the Local Precipitation over Nam co region, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-4381, https://doi.org/10.5194/egusphere-egu2020-4381, 2020.

Indian agriculture equipped the most intensive irrigation worldwide and still maintains an increasing trend of irrigation due to the decreasing of Indian summer monsoon rainfall. Irrigation could largely increase soil moisture and evapotranspiration while cooling air temperature. Several researches showed that Indian irrigation did not significantly contribute to local precipitation, so will the Indian irrigation affect the adjacent regions, such as the Tibetan Plateau is unclear. Here, we set up 10-years simulations for two nested domains (30-10km) over the South-East Asia to quantify the irrigation effects with a coupled dynamic crop model and regional climate model (WRF4.0-CLM4Crop). Besides the numeric simulations, we adopted a water vapor back trajectory tracking method to track where the evaporation from the irrigated land fall as precipitation. Our preliminary results showed that Indian irrigation did not significantly affects temperature, sensible heat flux, and latent heat flux over the Tibetan Plateau, but the water vapor from Indian irrigation contributed to 10% of the summer precipitation on the Tibetan Plateau.

How to cite: Lu, Y. and Lin, S.: Indian irrigation effects on precipitation over the Tibetan Plateau, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-4467, https://doi.org/10.5194/egusphere-egu2020-4467, 2020.

We investigated the factors influencing the daily maximum boundary layer height (h_max) and their relationship with air quality in the Sichuan Basin, China. We analyzed the factors influencing h_max on cloudy and sunny days in winter using five years of observational data and a reanalysis dataset and investigated the relationship between h_max and air quality. The inversion layer in the lower troposphere has a critical impact on h_max on cloudy days. By contrast, the sensible heat flux and wind shear are the main influencing factors on sunny days, although the contribution of the sensible heat flux to h_max is less than that of the wind shear. This is because the turbulence is mainly affected by mechanical mixing induced by the topographic effect of the Tibetan Plateau to the west of the Sichuan Basin. The secondary circulation over the Sichuan Basin is weaker on cloudy days than on sunny days. These results are important for understanding the dispersion of air pollutants over the Sichuan Basin.

How to cite: Cao, B.: Factors influencing the boundary layer height and their relationship with air quality in the Sichuan Basin, China, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-4627, https://doi.org/10.5194/egusphere-egu2020-4627, 2020.

The Tibetan Plateau (TP), which is located in Asia and has an average elevation of over 4000 m, acts as a raised source of heat and an isolated region of humidity in the atmosphere. The TP serves as a “world water tower” because it stores large amounts of water as glaciers, lakes, and rivers. Furthermore, previous studies have found that the easterly outflow of water vapor and clouds away from the TP contributes significantly to precipitation over downstream regions. However, the dynamic mechanism behind these observations is still unclear. It is known that the key driver in the transportation of air and water resources from the TP is the wind field. Under global warming, the pole ward expansion of the Hadley circulation and the thermal effect of the terrain over the TP forces the mid-latitude subtropical westerly jet(SWJ) to shift. However, the true effects of the SWJ are unclear.

Here, we propose a dynamic mechanism of the northern drought attributable to the TP in summer. The TP, similar to a very large engine, drives the nearby movement of water vapor, clouds, and aerosols. This “engine effect” controls precipitation near the TP and can trigger flooding or droughts in downstream regions. The northern drought is driven by the collocation of the subtropical westerly jet (SWJ) position and the TP engine effect. The meridional shift in the SWJ is the determining factor of the northern drought in summer. When the SWJ shifts northward, the upper-level westerly wind is weakened; thus, the water vapor, clouds or dusty clouds over the TP are transported to north less often, reducing precipitation and causing more frequent droughts. In contrast, when the SWJ shifts southward, the northern area of China experiences increased precipitation in summer.

How to cite: Huang, J., Liu, Y., Li, Y., Zhu, Q., and Wang, S.: Attribution of the Tibetan Plateau to Northern Drought, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-6239, https://doi.org/10.5194/egusphere-egu2020-6239, 2020.

In the current Earth System Model (ESM), the soil water and heat transport in the land surface model (LSM) is not strongly coupled. As such, the discrepancy between the modelled land surface states and fluxes and the observed ones was mainly remedied by revising relevant simplified parameters, while the detailed physics (and/or physiography) was not necessarily consistent. While zooming in those studies over the cold region, the current ESMs do not consider the hydro-permafrost-carbon coupling. For example, the strong impact of soil moisture on spatial patterns of soil carbon stocks has been observed at sites, while the current ESMs cannot show this impact. On the other hand, soil moisture can affect the temperature sensitivity of decomposition rate and alter soil thermal dynamics significantly. To address the foregoing issues, it calls for an interdisciplinary approach to investigate soil-water-energy-plant interactions. Such approach is even more so desired for cold regions, where permafrost and seasonal frozen ground widely spread. This pressing need is mainly due to the carbon release from climate-induced permafrost thawing into the atmosphere, called as permafrost carbon feedback (PCF). It is also due to the tight coupling between hydrological processes and carbon dynamics, which, if ignored, will lead to the underestimation of global carbon turnover time by 36%. As a trial, this research coupled the detailed soil water and heat model with the biogeochemical model to investigate the mechanisms behind the impacts of enhanced soil water and heat dynamics on ecosystem functioning.

How to cite: Su, Z., Yu, L., Wang, Y., and Zeng, Y.: Impacts of Enhanced Soil Water and Heat Dynamics on Ecosystem Functioning, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-13774, https://doi.org/10.5194/egusphere-egu2020-13774, 2020.

In context of global warming, permafrost, as an important component of cryosphere in the Qinghai-Tibetan Plateau (QTP) that is located in middle and low latitudes with a high radiation intensity of high Asia mountains, is particularly sensitive to climate changes. The active layer thickness (ALT) in a permafrost area is an important index to indicate its stability. Traditional methods for measuring ALT in QTP mainly rely on ground-based field surveys and accordingly are extremely time- consuming and labor-intensive. The field works provide a good quality of data at a single site, however, such measurements are limited in spatial coverage and difficult for multi-temporal acquisitions. In addition, the harsh environment in QTP is not suitable for large-scale field measurements. In this study, the ALT of permafrost in QTP is estimated using modelling and remote sensing data. Particularly, the surface deformation on permafrost, as detected by the long-term InSAR technique, is considered as an input to the inversion model of ALT. The time-series deformation results over an experimental permafrost area were obtained by the SBAS-InSAR technique. Then, combined with the soil characteristics of soil moisture and soil thermal conductivity in the Stefan model, the melting thickness was estimated. Finally, the resulting ALT was tested and verified against a set of in-situ borehole measurements of depth-temperature.

How to cite: Li, R., Hao, T., Lu, P., Qiao, G., Chen, L., Han, J., and Zhenshi Li, Z.: Estimation of active layer thickness from modeling and InSAR deformation data at QTP, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-6560, https://doi.org/10.5194/egusphere-egu2020-6560, 2020.

The water availability of agricultural arid regions can be assessed at presence using the physical-mathematical model of water and heat exchange between land surface and atmosphere LSM (Land Surface Model) adapted to satellite-derived estimates of meteorological and vegetation characteristics. The LSM is designed to calculate soil water content W, evapotranspiration Ev, vertical heat fluxes and other water and heat regime elements. Soil and vegetation characteristics were used in the LSM as parameters and meteorological characteristics were utilized as input variables.

The case study was carried out for the territory of the Saratov and Volgograd Trans-Volga region (the left-bank part of the Saratov and Volgograd regions) of 66600 km² for the vegetation seasons 2016-2018.

The satellite measurement data from radiometers AVHRR/NOAA, SEVIRI/Meteosat-10, -11, -8, and MSU-MR/Meteor-M No. 2 in visible and IR ranges were thematic processed to built estimates of vegetation index NDVI, emissivity E, vegetation cover fraction B, leaf index LAI, land surface temperature LST and precipitation.

LAI and B estimates were obtained using empirical dependencies on NDVI. The adequacy of the LAI and B estimates obtained from all sensor data was verified when comparing the LAI time behavior built for named vegetation seasons. Errors of determining B and LAI were 15 and 20%, respectively.

Satellite-derived estimates of daily, decadal and monthly precipitation sums for each pixel were obtained using the Multi Threshold Method (MTM) for detecting clouds, identifying its types allocating precipitation zones and determining their maximum intensity. The MTM is based on the developed algorithm of the transition from the assessment of precipitation intensity to the assessment of their daily amounts. Testing of the method was carried out when comparing these amounts with observed at meteorological stations. The probability of satellite-detected precipitation zones corresponded to the actual ones was ~ 80% for all radiometers.

Based on the MTM, computational algorithm to evaluate the LST was developed and verified on the study region data. Comparison of ground-measured and satellite-derived LST showed that the latter estimates for the overwhelming number of observation turned out to be comparable in accuracy with each other and with the ground-based data.

Calculations of water and heat regime elements (being the final products of the simulation) were carried out when replacing ground-based estimates of precipitation, LST, LAI and B in the LSM by satellite-derived ones at each time step in all nodes of the computational grid. The efficiency of such replacement procedures was confirmed by comparing measured and calculated values of W and Ev (the difference between them didn’t exceed 15% for W and 25% for Ev).

The possibility of using soil surface moisture estimates obtained from all-weather measurements by the scatterometer ASCAT/MetOp in the microwave range when simulating soil water content was also revealed. These estimates may use to set initial conditions for the vertical soil water transfer equation, as well as for calculating evaporation from the soil surface and the subsequent formation of the upper boundary condition for this equation.

As a summary, the described approach can be considered as a method for assessing the water availability for agricultural arid region.

How to cite: Muzylev, E., Startseva, Z., Volkova, E., and Vasilenko, E.: Using satellite data in the Land Surface Model to estimate water availability of arid agricultural region, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-13037, https://doi.org/10.5194/egusphere-egu2020-13037, 2020.

Net radiation is the main energy balance component of land surfaces. It is an important factor in the studies of land-atmosphere processes, water resources management and so on. This is particularly true in the UBN basin where significant parts of the basin are dry and evapotranspiration (ET) is a major path of water loss. In this paper, we have estimated instantaneous net radiation distributions in the basin from MODIS Terra satellite and Automatic Weather Station (AWS) data. As downward shortwave radiation and air temperature usually vary spatially due to topographic effects, which are common features of our study area, we had applied residual kriging spatial interpolation approaches in the conversion processes of point weather data to surface data. Validation attempts of the simulated net radiation outputs with an independent field measurement at Choke flux tower site, which is in the central part of the basin, has shown that our method were able to reproduce downward shortwave, upward shortwave., and net radiation flux with a statistical metrics of Mean bias (MB) and Root Mean Square (RMSE) lesser than other studies done in similar physiographic regions in several parts of the world. It looked that the use of AWS data and residual kriging spatial interpolation technique made our results robust and even comparable to works done using finer spatial resolution satellite data than MODIS. The estimated net shortwave, net longwave and overall net radiations were in close agreement with ground truth measurements with MB of -14.84, 5.7 & 20.53 Wm^-2 and RMSE 83.43, 32.54 & 78.07 Wm^-2 respectively. The method has potential applications in research works like energy balance, ET estimation, and weather predictions in regions with similar physiographic features as that of the Nile basin.

How to cite: Tegegne, E. B., Ma, Y., Chen, X., Ma, W., Wang, B., Ding, Z., and Zhu, Z.: Estimations of net radiation flux distributions from automatic weather stations and satellite data in the Upper Blue Nile (UBN) basin, Ethiopia, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-1833, https://doi.org/10.5194/egusphere-egu2020-1833, 2020.

Remote sensing-based river discharge estimation for a small river flowing over the high mountain regions of the Tibetan Plateau

Mulugeta Genanu Kebede ^{1, 2, 3}, Lei Wang^{1, 2*}, Xiuping Li¹ and Zhidan Hu⁴

¹ Key Laboratory of Tibetan Environment Changes and Land Surface Processes, Institute of Tibetan Plateau Research, Chinese Academy of Sciences, and CAS Center for Excellence in Tibetan Plateau Earth Sciences, Beijing, China

² University of Chinese Academy of Sciences, Beijing, China

³ Arba Minch University, Water Technology Institute, Faculty of Meteorology and Hydrology, Arba Minch, Ethiopia

⁴ Information Center, Ministry of Water Resources, Beijing 100053, China

* Correspondence to: Dr. Lei Wang, Professor

Email: wanglei@itpcas.ac.cn;     Tel.: +86-10-8409-7107; Fax: +86-10-8409-7079

ABSTRACT

River discharge, as one of the most essential climate variables, plays a vital role in the water cycle. Small-scale headwater catchments including high-mountain regions of Tibetan Plateau (TP) Rivers are mostly ungauged. Satellite technology shows its potential to fill this gap with high correlation of satellite-derived effective river width and corresponding in-situ gauged discharge. This study is innovative in estimating daily river discharge using modified Manning equation (Model 1), Bjerklie equation (Model 2), and Rating curve approach (Model 3) by combining river surface hydraulic variables directly derived from remote sensing datasets with other variables indirectly derived from empirical equations, which greatly contributes to the improvement of river flow measurement information especially over small rivers of TP. We extracted the effective width from Landsat image and flow depth via hydraulic geometry approach. All the input parameters directly or indirectly derived from remote sensing were combined and substituted into the fundamental flow equations/models to estimate discharges of Lhasa River. The validation of all three models’ results against the in-situ discharge measurements shows a strong correlation (the Nash–Sutcliffe efficiency coefficient (NSE) and the coefficient of determination (R²) values ≥ 0.993), indicating the potentiality of the models in accurately estimating daily river discharges. Trends of an overestimation of discharge by Model 1 and underestimation by Model 2 are observed. The discharge estimation by using Model 3 outperforms Model 1 and Model 2 due to the uncertainties associated with estimation of input parameters in the other two models. Generally, our discharge estimation methodology performs well and shows a superior result as compared with previously developed multivariate empirical equations and its application for other places globally can be the focus of upcoming studies.    

Keywords: River discharge estimation, remote sensing, effective width, hydraulic relationship, Tibetan Plateau

How to cite: Kebede, M. G., Wang, L., Li, X., and Hu, Z.: Remote sensing-based river discharge estimation for a small river flowing over the high mountain regions of the Tibetan Plateau , EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-2282, https://doi.org/10.5194/egusphere-egu2020-2282, 2020.

Diurnal temperature range (includes land surface temperature diurnal range and near surface air temperature diurnal range) is an important meteorological parameter, which is a very important factor in the field of the urban thermal environmental. Nowadays, the research of urban thermal environment mainly focused on surface heat island and canopy heat island.

Based on analysis of the current status of city thermal environment. Firstly, a method was proposed to obtain near surface air temperature diurnal range in this study, difference of land surface temperature between day and night were introduced into the improved temperature vegetation index feature space based on remote sensing data. Secondly, compared with the district administrative division, we analyzed the spatial and temporal distribution characteristics of the diurnal range of land surface temperature and near surface air temperature.

The conclusions of this study are as follows:

1 During 2003-2012s, the land surface temperature and near surface air temperature diurnal range of Beijing were fluctuating upward. The rising trend of the near surface air temperature diurnal range was more significant than land surface temperature diurnal range. In addition, the rise and decline of land surface temperature and near surface air temperature diurnal range in different districts were different. In the six city districts, the land surface temperature and near surface air temperature diurnal range in the six areas of the city were mainly downward. The decline trend of near surface air temperature diurnal range was more significant than land surface temperature diurnal range.

2 During 2003-2012s, the land surface temperature and near surface air temperature diurnal range of Beijing with similar characteristics in spatial distribution, with higher distribution land surface temperature and near surface air temperature diurnal range in urban area and with lower distribution of land surface temperature and near surface air temperature diurnal range in the Northwest Mountainous area and the area of Miyun reservoir.

How to cite: Guo, Z. and Cheng, M.: Study on Urban Thermal Environment based on Diurnal Temperature Range, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-12971, https://doi.org/10.5194/egusphere-egu2020-12971, 2020.

Soil moisture (SM) is a key variable in understanding the climate system through its controls on the land surface energy and water budget. Large scale SM products have become increasingly available thanks to development in microwave remote sensing and land surface modeling. Comprehensive assessments on the reliability of satellite-derived and model-simulated SM products are essential for their improvement and application. In this research, the active, passive and combined Climate Change Initiative (CCI V04.2) SM products and the China Land Data Assimilation System (CLDAS V2.0) SM products were evaluated by comparing with in situ observed data over three networks in China: Hebi, Naqu and Heihe. The three sites have different environmental conditions and sensor densities, providing observations covering more than 2 years. Four statistic scores were calculated: R (considering both original data and anomalies), Bias, RMSE, ubRMSE. TC (Triple Collocation) analysis was also carried out in which uncertainties in observations are taken into account. Results indicate that the performance of the two SM products varies between the monitoring networks. For Naqu site, both products show good performance, with CCI-SM showing slightly higher R and lower ubRMSE. For Hebi site, CLDAS-SM performs better than CCI-SM, whereas for Heihe site, CLDAS-SM performs worse than CCI-SM. The expected uncertainty (0.04 m³/m³) can be achieved in Naqu and Heihe site by CCI-SM, and in Hebi and Naqu site by CLDAS-SM, which is quite encouraging. The two products agree in terms of sign of the Bias value, which is positive in Hebi and negative in Naqu and Heihe. Among all the three networks, Heihe site exhibits the lowest accuracy due to its complicated terrain and heterogeneous land surface. R_anom of CLDAS-SM in Heihe is close to 0, indicating its inability to capture short term variability. TC results reveal that for Naqu site the observation data have quite good qualities, while for Hebi site CLDAS-SM is more approximate to ‘ground truth’ than in situ observations, suggesting a refinement of network maybe needed in the future. Overall, the two products are complementary. CLDAS-SM performs better in populated area (e.g., Hebi) where meteorological forcing is more accurate and CCI-SM performs better in remote areas (Naqu, Heihe) where RFI is usually low. More reliable validation networks are needed in the future to comprehensively understand the advantages and disadvantage of the two SM products in China.

How to cite: Wang, Y. and Li, G.: Evaluating model-simulated and satellite-derived SM using in situ observations under different environment conditions in China, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-2819, https://doi.org/10.5194/egusphere-egu2020-2819, 2020.

GPS Radio Occultation (RO) cloudy profiles during a seven-year period from 2007 to 2013 over the globe are firstly selected and grouped into four types of ice clouds (e.g., nimbostratus, deep convective, cirrus, altostratus) based on collocated CloudSat data. Vertical temperature profiles within ice clouds below -20^oC are then retrieved from GPS RO refractivity observations, in which the vertical profiles of ice water content required by the forward model of refractivity are obtained from CloudSat retrievals of ice water content. Vertical distributions of relative humidity and lapse rate within clouds are finally examined in terms of their occurrences, mean values and standard deviations. It is found that ice clouds have preferred values of relative humidity and lapse rate depending on cloud types and altitudes. Most altostratus ice clouds are located between 4-8 km with relative humidity between 55-75%. The cirrus clouds have a relative humidity around 60% and are located mostly above 6 km to as high as 13 km. Difference from cirrus and altostratus ice clouds, nimbostratus ice clouds that occur mostly in polar regions are found at all altitudes below 10 km with a relative humidity decreasing linearly from about 90% near the surface to about 60% around 6 km. Within deep convective ice clouds, the relative humidity also decreases linearly from about 100% around 2.5 km to about 60% around 9 km. The lapse rate slightly increases with altitude and its value ranges between 5-8^oC km^-1 within nimbostratus, deep convective and altostratus ice clouds. The lapse rate within cirrus clouds varies from 6^oC km^-1 to 9^oC km^-1. Vertical variations of the lapse rate derived from GPS RO cloudy retrievals compared favorably to those derived from radiosonde profiles. Both show the mean lapse rate increases with altitude from about 5^oC km^-1 around 3 km to about 7^oC km^-1 around 7 km, and the standard deviations are much smaller than the mean lapse rate.

How to cite: Yang, S.: Lapse Rate Characteristics in Ice Clouds Inferred from GPS RO and CloudSat Observations, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-11980, https://doi.org/10.5194/egusphere-egu2020-11980, 2020.

The Western Tibetan Vortex (WTV) was identified through research efforts to understand the causal mechanisms responsible for the ‘Karakoram Anomaly’. The WTV has been shown to be an important anomalous circulation system influencing near surface climate over the Tibetan Plateau (TP). Existing researches have characterised the dynamical characteristics and thermodynamic behaviours of the WTV in detail. Scientific consensus has not yet been established. However, regarding the physical mechanisms which produce the WTV itself, a recent argument has asserted that the WTV is the set of wind field anomalies resulting from changes in 2m near-surface air temperatures (T_2m) over the western TP. This argument can spur constructive discussion for improving our understanding on the WTV. This paper examines whether a putative thermal-generating machanism for the WTV can explain the established defining features of the WTV. In particular we evaluate if warmer (colder) T_2m over the western TP is sufficient to drive downward (upward) wind anomaly in the overlying air column. Detailed consideration is given to whether the supposedly thermally induced vortex does indeed have the expected baroclinic structure – i.e. cyclonic (anti-cyclonic) wind anomaly at the mid-lower (mid-higher) troposphere – rather than a quasi-barotropic structure – i.e. cyclonic or anti-cyclonic wind anomaly at both the mid-lower and mid-higher troposphere –  as the research first identifying the WTV reported. This work thus seeks to determine the ‘direction of causality’ of whether  the WTV drives T_2m over the western TP or the thermal forcing of the western TP’s T_2m is the mechanism generating the WTV. This work utilises ERA5 meteorological reanalysis data to assess how the WTV may impact the western TP’s T_2m through modulating the cloud cover and hence net surface radiation. These analyses complement previously published evaluation of the prosoposed adiabatic heating mechimism through which the WTV impacts the mid-lower tropospheric and near surface air temperarure. It is important to note that further evaluations of the skill of the newly released ERA5 dataset in representing the atmospheric conditions accurately over the western TP are still needed.

How to cite: Li, X. and Yu, J.: The Western Tibetan Vortex as an emergent feature of near-surface temperature variation? , EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-19376, https://doi.org/10.5194/egusphere-egu2020-19376, 2020.

Land surface temperature (LST) is the direct driving force of turbulent heat fluxes at the surface and atmosphere interface and is widely used in the fields of evapotranspiration estimation (Su et al., 2002) and energy budget (Liang et al., 2019). Remote sensing products offer the only possibility for measuring LST with completely spatially averaged values. The thermal radiation directionality (TRD) effect has been widely concerned in the area of thermal infrared (TIR) remote sensing over 50 years which can lead to the directional brightness temperature (DBT) difference between different viewing directions up to 10 K (Cao et al., 2019). Many models have been proposed to simulate the DBT patterns over different underlying surfaces aimed to achieve the TRD effect correction for the satellite LST products. In practice, it is advised to handle only TRD models having a limited number of input parameters for operational normalization of LST products. The use of TIR kernel-driven models appears a good tradeoff between physical accuracy and operationality. It remains that the existing 4 TIR kernel-driven models (Ross-Li, LSF-Li, Vinnikov, RL) underestimate the hotspot effect, especially for continuous canopies. In this study, a new general framework of TIR kernel-driven modeling is proposed to overcome such issue. It is a linear combination of three kernels (including a base shape kernel, a hotspot kernel and an isotropic kernel) with the ability to simulate the bowl, dome and bell shapes in the solar principal plane. 4 specific models (Vinnikov-RL, LSF-RL, Vinnikov-Chen, LSF-Chen) within the new framework were further developed to assess their fitting abilities for both continuous and discrete vegetation canopies. To evaluate 4 existing models and 4 new models comprehensively, it was prepared 102 groups of 4SAIL/DART generated multi-angle datasets considering 6 different canopy architectures and 17 component temperatures. Results show that the 4 new models behave slightly better than the 4 existing models over discrete canopies (R2 increases from 0.791~0.989 to 0.976~0.996) whereas they significantly improved the fitting accuracy over continuous canopies (R2 increases from 0.661~0.970 to 0.940~0.997). The innovative new general framework with three kernels and four parameters improve the fitting ability significantly since the addition of one more degree of freedom. This new kernel-driven modeling framework is a potential tool to achieve angular correction of LST products.

How to cite: Cao, B., Liu, Q., Du, Y., Li, H., Bian, Z., Hu, T., and Xiao, Q.: A General Framework of Kernel-driven Modeling in the Thermal Infrared Band for Land Surface Temperature Normalization, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-20449, https://doi.org/10.5194/egusphere-egu2020-20449, 2020.

The FY-4A satellite is the first quantitative remote sensing satellite of a three-axis stabilization structure on geostationary orbit launched by China in 2016. The capability and efficiency are improved with the new variety of instruments in earth observation. The thermal infrared (TIR) channels of Advanced Geosynchronous Radiation Imager (AGRI) which one of the new instruments onboard FY-4A provides high-frequency, high-precision, and quantitative observation data to obtain diurnal variation of land surface temperature (LST). In this paper, nine candidate split window LST algorithms were applied to evaluate the applicability of the different algorithm for FY-4A, and the Ulivieri & Cannizzaro (1985) algorithm was selected. Then different algorithms in day and night for dry and wet atmosphere conditions are developed and optimized to improve the accuracy of retrieved FY-4A LST. Then, the operational products of FY-4A LST are produced in clear sky. Results show that the diurnal variation characteristics of LST can be efficiently obtained. And the validation shows the following: 1) the root mean square errors (RMSE) is 3.5 K in day and 4.24 K in night when compared with the Himawari8 LST product; 2) compared with ground-measured data, the average accuracy of our algorithm is 2.5 K in day and 3.56 K in night. Sensitivity analysis shows that emissivity is lower sensitive to the algorithm accuracy, and the atmospheric water vapor content is higher sensitive to the algorithm accuracy with the view angle increased. In general, our algorithm exhibits good accuracy and is an easy retrieval approach to produce LST operational products on a regional scale. And the FY-4A LST operational products will help to the weather services, climate change, land–atmosphere interaction research, and ecological civilization construction, and so on.

How to cite: Dong, L., Xu, N., and Chen, L.: Retrieval of FY-4A Land Surface Temperature for Operational Application, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-2529, https://doi.org/10.5194/egusphere-egu2020-2529, 2020.

As one of the most important indicators in the energy exchange between land and atmosphere, Land Surface Temperature (LST) plays an important role in the research of climate change and various land surface processes. In contrast to in-situ measurements, satellite remote sensing provides a practical approach to measure global and local land surface parameters. Although passive microwave remote sensing offers all-weather observation capability, retrieving LST from thermal infra-red data is still the most common approach. To date, a variety of global LST products have been published by the scientific community, e.g. MODIS and (A)ASTR /SLSTR LST products, and used in a broad range of research fields. Several global and regional satellite retrieved LSTs are available since 1995. However, the temporal-spatial resolution before 2000 is generally considerably lower than that after 2000. According to the latest IPCC report, 1983 – 2012 are the warmest 30 years for nearly 1400 years. Therefore, for global climate change research, it is meaningful to extend the time series of global LST products with a relatively higher temporal-spatial resolution to before 2000, e.g. that of NOAA AVHRR. In this study, global daily NOAA AVHRR LST products with 5-km spatial resolution were generated for 1981-2000. The LST was retrieved using an ensemble of RF-SWAs (Random Forest and Split-Window Algorithm). For a maximum uncertainty in emissivity and water vapor content of 0.04 and 1.0 g/cm², respectively, the training and testing with simulated datasets showed a retrieval accuracy with MBE of less than 0.1 K and STD of 1.1 K. The generated RF-SWA LST product was also evaluated against in-situ measurements: for water sites of the National Data Buoy Center (NDBC) between 1981 and 2000, it showed an accuracy similar to that for the simulated data, with a small MBE of less than 0.1 K and a STD between 0.79 K and 1.02 K. For SURFRAD data collected between 1995 and 2000, the MBE is -0.03 K with a range of -1.20 K – 0.54 K and a STD with a mean of 2.55 K and a range of 2.08 K – 3.0 K (site dependent). As a new global historical dataset, the RF-SWA LST product can help to close the gap in long-term LST data available to climate research. Furthermore, the data can be used as input to land surface process models, e.g. the Community Land Model (CLM). In support of the scientific research community, the RF-SWA LST product will be freely available at the National Earth System Science Data Center of China (http://www.geodata.cn/).

How to cite: Ma, J., Zhou, J., Göttsche, F.-M., and Wang, S.: Global Land Surface Temperature from historical NOAA AVHRR datasets (1981-2000), EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-3102, https://doi.org/10.5194/egusphere-egu2020-3102, 2020.

Ground-based component temperatures are important inputs to model the energy exchange between the heterogeneous land surface and atmosphere. Although some excellent researches have been done, factors affecting the ground-based component temperatures over sparsely vegetated surface are still needed for further understanding. In order to obtain an in-depth understanding of component temperatures, a MUlti-Scale Observation Experiment on land Surface temperature (MUSOES) was designed and performed in a nature oasis with highly heterogeneous vegetated surface in the downstream of Heihe River basin, northwest China. The MUSOES was under the framework of the Heihe Watershed Applied Telemetry Experimental Research (HiWATER). During the intensive observation period, between July 20th and August 20th of 2014, surface temperatures were obtained at two scales around two hydrometeorological observatory stations: the mixed forest station (MFS) and the superstation (SUP). At MFS, six and four component temperatures were identified from the measurements of scale I (scale of thermal infrared (TIR) imagers) and scale II (scale of TIR radiometers), respectively. Due to the dense shrubs and absence of trees at SUP, two component temperatures were identified under each scale. Results show that intrinsic characteristics influence the variability of temperature between components and within a component. For the component temperatures measured by TIR imager, the mean differences between sunlit soil, shrub, and tree canopy were 17.9 K and 7.0 K at MFS; the mean difference between soil and shrub was 17.7 K at SUP. At the direction-level and pixel-level, the components exhibit different internal temperature differences. Furthermore, the component temperatures significantly affected by the illumination condition, viewing direction, and instrument type. Deviation exists between the component temperatures measured by the TIR radiometer and the TIR imager and depends on the components (e.g. 6.7 K for soil and -7.9 K for shrub at SUP). The TIR radiometer faces great challenge to measure the component temperature with good spatial representativeness over highly heterogeneous surface. Findings from this study can benefit our understandings of the attribute and ground observation of component temperatures, and promote the further study of the energy exchange between the heterogeneous land surface and atmosphere.

How to cite: Li, M. and Zhou, J.: In-depth understanding of component temperatures over sparsely vegetated surfaces, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-19974, https://doi.org/10.5194/egusphere-egu2020-19974, 2020.

Meltwater from seasonal snow provides a substantial amount of runoff to many of the rivers that originate in the high mountains of Asia, yet the importance of snow in the region as streamflow component, its changes over the past decades, and its sensitivity to future climatic changes are relatively unknown. To understand future changes in the water supply to the millions of people living downstream, a better understanding of snow dynamics at large scale is key. Using a novel snow model, forced by ERA5 climate reanalysis and calibrated by MODIS remote sensing observations, we generate daily snow water equivalent output at 0.05° resolution covering all major river basins in Asia. We show that between 1979 and 2018 significant and spatially variable changes have occurred in snow meltwater availability and its timing, with melt peaks attenuating and/or advancing in time, and snowmelt seasons shortening. Additionally, our results reveal that snowmelt is a much more important contributor to streamflow than glacier melt in many of Asia's large river basins. In a bottom-up elasticity analysis we project strong changes in snowmelt in the future under changing temperature and precipitation. Sensitivity of snowmelt to climate change varies among basins, however, and actual losses are strongly dependent on the degree of future climate change. Limiting climate change in the current century is therefore crucial in order to sustain the role of seasonal snow packs in Asia’s water supply.

How to cite: Kraaijenbrink, P., Stigter, E., Yao, T., and Immerzeel, W.: Climate change decisive for Asia’s snow meltwater supply, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-2404, https://doi.org/10.5194/egusphere-egu2020-2404, 2020.

To resolve a series of ecological and environmental problems over the Loess Plateau, the was initiated at the end of 1990s. Following the conversion of croplands and bare land on hillslopes to forests, the Loess Plateau has displayed a significant greening trend with soil erosion being reduced. However, the GFGP has also affected the hydrology of the Loess Plateau which has raised questions whether the GFGP should be continued in the future. We investigated the impact of revegetation on the hydrology of the Loess Plateau using high resolution simulations and multiple realisations with the Weather Research and Forecasting (WRF) model. Results suggests that land cover change since the launch of the GFGP has reduced runoff and soil moisture due to enhanced evapotranspiration. Further revegetation associated with the GFGP policy is likely to increase evapotranspiration further, and thereby reduce runoff and soil moisture. The increase in evapotranspiration is associated with biophysical changes, including deeper roots that deplete deep soil moisture stores. However, despite the increase in evapotranspiration our results show no impact on rainfall. Our study cautions against further revegetation over the Loess Plateau given the reduction in water available for agriculture and human settlements, without any significant compensation from rainfall.

How to cite: Guo, W., Pitman, A., Ge, J., Zan, B., and Fu, C.: Impact of revegetation of the Loess Plateau of China on the regional growing season water balance, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-3877, https://doi.org/10.5194/egusphere-egu2020-3877, 2020.

The Local land atmosphere coupling (LoCo) focuses on the interactions between soil conditions, surface fluxes, PBL growth, and the formations of convective clouds and precipitations, and a study of LoCo over the Tibetan Plateau (TP) is of great significance to understand its role of “Asian Water Tower”. This study investigates the LoCo characteristics over a typical underlying surface in central TP in the rainy season based on a series of real case simulations using Weather Research and Forecasting Model (WRF) with different combinations of land surface model (LSM) schemes and planetary boundary layer (PBL) schemes based on in-situ measurements. Then the LoCo characteristics over a typical underlying surface in central TP are analyzed using a mixing diagram. The simulations results indicates that WRF simulations using Noah with BouLac, MYNN, and YSU produce much better results in terms of curves of Cp*theta and Lv*q, surface fluxes (H_sfc and LE_sfc), entrainment fluxes (H_ent and LE_ent) at site BJ/Nagqu that those using CLM with BouLac, MYNN, and YSU do. The frequency distributions of H_sfc, LE_sfc, H_ent, and LE_ent in the study area confirmed this result. The spatial distributions of simulated H_sfc, LE_sfc, H_ent, and LE_ent using WRF with Noah and BouLac suggest that the spatial distributions of H_sfc and LE_sfc in the study area show a good consistent with that of soil moisture, but the spatial distributions of H_ent and LE_ent are quite different from that of soil moisture. A close examination of the relationship between entrainment fluxes and cloud water contents (QCloud) reveals that the grids with small H_ent and large LE_ent are likely to have high QCloud and H_sfc. This means that high H_sfc is conductive to convective cloud formations, which lead to small H_ent and large LE_ent. Sensitivity analysis of LoCo to the soil moisture at site BJ/Nagqu indicates that in a sunny day, an increase in soil moisture leads to an increase in LE_sfc but a decrease in H_sfc, H_ent, and LE_ent. The sensitivity of the relationship between simulated max daytime PBLH and mean daytime EF in the study area to soil moistures indicates that the rate at which the max daytime PBLH decrease with the mean EF increases as the initial soil moisture goes up. The analysis of simulated H_sfc, LE_sfc, H_ent, and LE_ent under different soil moisture conditions reveals that the frequencies of H_ent ranging from 80 W/m² and over 240 W/m² and frequency of LE_ent ranging from -240 W/m² to -90 W/m² increase as the initial soil moisture increases. Coupled with the changes in QCloud, the changes in H_ent and LE_ent as the initial soil moisture increases indicate that the increase in soil moisture lead to an increase in cloud amounts but a decrease in QCloud.

How to cite: Sun, G., Hu, Z., Ma, Y., and Yang, S.: Simulation Analysis of Local Land Atmosphere Coupling in Rainy Season over a Typical Underlying Surface in the Tibetan Plateau, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-6648, https://doi.org/10.5194/egusphere-egu2020-6648, 2020.

Microplastics have been widely found in the aquatic and terrestrial environments, such as in sea water, sea ice, lake/river water, and sediments. Glaciers also bring an important temporal component to microplastics studies, which can reveal atmospheric deposition in polar or high-altitude environments. However, microplastics accumulating in glaciers or being released from melting glaciers are still sparsely reported, particularly in the Tibetan Plateau (TP), which covers 5 million km² with an average elevation of >4,000 m a.s.l. (above sea level), and contains a large volume of glaciers in the mid-low latitude regions. Adjacent to human settlements in South Asia, East China, and central Asia, the TP is readily influenced by cross-border air pollution that can affect its vulnerable and pristine environments, among which the cryospheric environments, particularly glaciers, have been drawing increasing attention for their accelerated melting and relevant risks to regional water resources and quality. Recently, microplastics have been detected in glaciers and lake water at different locations on the TP, indicating that they can be transported to the TP. The findings are expected to be significant for narrowing knowledge gaps in connecting transport atmospheric pollutants and cryospheric changes over the TP, and for serving as a valuable and fundamental scientific basis for regional environmental protection and policy-making.

How to cite: Zhang, Y. and Gao, T.: Microplastics intrude into the Tibetan Plateau, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-2292, https://doi.org/10.5194/egusphere-egu2020-2292, 2020.

In recent days there have been discussions regarding the impact of climate change and its vagaries of the weather, particularly concerning extreme events. Nepal, being a mountainous country, is more susceptible to precipitation extreme events and related hazards, which hinder the socioeconomic
development of the nation. In this regard, this study aimed to address this phenomenon for one of the most naturally and socioeconomically important regions of Nepal, namely, Eastern Nepal. The data were collected for the period of 1997 to 2016. The interdecadal comparison for two periods
(1997–2006 and 2007–2016) was maintained for the calculation of extreme precipitation indices as per recommended by Expert Team on Climate Change Detection and Indices. Linear trends were calculated by using Mann‐Kendall and Sen's Slope estimator. The average annual precipitation was found to be decreasing at an alarming rate of −20 mm/year in the last two decades' tenure. In case of extreme precipitation events, consecutive dry days, one of the frequency indices, showed a solo increase in its trend (mostly significant). Meanwhile, all the intensity indices of extreme precipitation showed decreasing trends (mostly insignificant). Thus, it can be concluded that Eastern Nepal has witnessed some significant drier days in the last two decades, as the events of heavy, very heavy, extremely heavy precipitation events, and annual wet day precipitation (PRCPTOT) were found to be decreasing. The same phenomena were also seen in the Tropical Rainfall Measuring Mission 3B42 V7 satellite precipitation product for whole Nepal.

How to cite: Subba, S., Ma, Y., and Ma, W.: Spatial and Temporal Analysis of Precipitation Extremities of Eastern Nepal in the Last Two Decades (1997–2016), EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-2784, https://doi.org/10.5194/egusphere-egu2020-2784, 2020.

Model realism testing is of vital importance in science of hydrology, in terms of realistic representation of hydrological processes and reliability of future prediction. We conducted three modeling case studies in cold regions of China, i.e. the upper Heihe River basin, the Urumqi Glacier No.1 basin, and the Yigong Zangbu River basin, to test the importance of stepwise modeling and internal fluxes validation to improve model realism.

In the upper Heihe River basin, we used four progressively more complex hydrological models (FLEXL, FLEXD, FLEXT0 and FLEXT), to stepwisely account for distributed forcing inputs, tailor-made model structure for different landscapes, and the realism constraints of parameters and fluxes. We found that the stepwise modeling framework helped hydrological processes understanding, and the tailor-made model structure and realism constraints improved model transferability to two nested basins.

In the Urumqi Glacier No. 1 basin, with 52% of the area covered by glaciers, we developed a conceptual glacier-hydrological model (FLEXG) and tested its performance to reproduce the hydrograph, and separate the discharge into contributions from glacier and nonglacier areas, and establish estimates of the annual glacier mass balance (GMB), the annual equilibrium line altitude (ELA), and the daily snow water equivalent (SWE). We found that the FLEXG model, involving effects of topography aspect, was successfully transferred and upscaled to a larger catchment without recalibration.

In the Yigong Zangbu River basin, with 41.4% glacier area, we designed three models (FLEXD, FLEX-S, FLEX-SG) to stepwisely understand the impact of snow, glacier to reproduce historic streamflow. We found that by involving snow and glacier modules, the model performance was dramatically improved. Although the daily streamflow of FLEX-SG reached up to 0.93 Kling-Gupta Efficiency (KGE) in calibration, it significantly overestimated snow cover area (SCA) and glacier mass balance (GMB). With satellite measured precipitation lapse rate, we improved FLEX-SG model realism not only to reproduce hydrography but also SCA and GMB.

How to cite: Gao, H., Ren, Z., and Duan, Z.: Stepwise modeling and the importance of internal fluxes validation to improve hydrological model realism: three case studies in cold regions of China, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-12264, https://doi.org/10.5194/egusphere-egu2020-12264, 2020.

The Tibetan Plateau (TP) exerts a significant impact on the weather and climate over many places of the world through both mechanical and thermal-dynamical effects. In summer, the major rainfall of the TP occurs over the southern slope, and the associated atmospheric latent heating dominates the total diabatic heating of TP. Then the variation of summer rainfall can directly regulate the TP’s thermal effects. On the other hand, the rainfall center over the southern slope is corresponding with the northern branch of South Asian summer monsoon, which is important to the agricultural productivity and economic stability along the Ganges River with dense population. This study shows that there existed a drying tendency over the southern TP (STP) in the rainy season of recent decades. A moisture budget analysis indicates that the dynamic change in vertical moisture advection is the dominant contributor to the drying trend, which is associated with the weakened upward motion over the STP. The changes in dynamic process over STP are induced by the northward shift of the subtropical westerly jet, whose northward shift reduces the upper-level anticyclone over STP and weakens the upper-level divergence, leading to a trend of vertical sinking motion. Furthermore, the northward shift of the jet is mainly attributed to the internal variability of the atmosphere, characterized by an upper-level circum-global wave train. The influence of atmospheric internal variability is demonstrated by the CESM Large Ensemble Project data.

How to cite: Wang, Z., Yang, S., and Duan, A.: Drying Tendency over the Southern Tibetan Plateau in Recent Past Decades, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-12583, https://doi.org/10.5194/egusphere-egu2020-12583, 2020.

This study examines the seasonal and diurnal variations of carbon dioxide and energy fluxes over three land cover types of Nepal by using the eddy covariance method from March to November 2016. The surface energy balance closures were moderate with the values of about 56%, 61%, and 64% closure at Kirtipur, Simara, and Tarahara sites respectively. The monthly average values of net radiation flux and latent heat flux peaked in August at Kirtipur and Tarahara sites whereas in June at Simara site respectively. The maximum monthly average measured sensible heat flux was 37 W m^-2, 43.6 W m^-2, and 36.3 W m^-2 in April for all the sites whereas soil heat flux was 5.1 W m^-2 and 2.9 W m^-2 in April for Kirtipur and Simara sites and 6.2 W m^-2 in June for Tarahara site. The magnitude of diurnal peak of net ecosystem CO₂ exchange (NEE) reached up to 11.04 µmol m^-2 s^-1 at Kirtipur, 15.04 µmol m^-2 s^-1 at Simara, and 10.44 µmol m^-2 s^-1 at Tarahara sites respectively. Among the three study sites, the ecosystem at the Kirtipur site was a good carbon source; the ecosystems at Simara and Tarahara sites were low and good carbon sink in the growing season. In addition, all three different land cover ecosystems were carbon sources when accounted for the measurement period.    

How to cite: Joshi, B. B., Ma, Y., Ma, W., and Wang, B.: Seasonal and Diurnal Variations of Carbon Dioxide and Energy Fluxes over Three Land Cover Types of Nepal, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-1820, https://doi.org/10.5194/egusphere-egu2020-1820, 2020.

 The Third Pole is the headwater of major rivers in Asia, which provide water resources for more than 2 billion people downstream. Compared with discharge, riverine sediment flux is a more sensitive variable in response to climate and land surface process changes, and also as an important index to quantify regional land degradation and soil resource changes. In this study, eight rivers originated in the Third Pole, including YerKang River, Shule River, Heihe River, Yarlung Tsangpo River, Nujiang River, Yellow River, YangTze River and Lancang River, were selected to study the variation of sediment flux in the source zone or upper reaches. Firstly, the amount and spatial variation of runoff depth and sediment yield of these rivers were explored. Secondly, the changes of riverine sediment fluxes in recent decades (1960-2017) were analyzed, with the spatial and temporal variations of sediment flux compared to climate (temperature, precipitation) and land surface process (glacier, frozen soil, vegetation cover) factors. Thirdly, the uncertainty of sediment flux variation associated with interaction of multi-factors were discussed. Finally, the significant impacts of sediment flux variation on the Third Pole environment and the safety of hydropower projects was pointed out with typical cases.

How to cite: Zhang, F., Shi, X., Zeng, C., Wang, G., Chen, Y., and Wang, L.: Recent Changes of Riverine Sediment Fluxes from the Third Pole, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-1825, https://doi.org/10.5194/egusphere-egu2020-1825, 2020.

The Land surface scheme is crucial for the performance of regional climate models in dynamic downscaling application. In this study, we investigate the sensitivity of the simulation  with high resolution (10km) WRF model to the land surface schemes over Central Asia. The high resolution WRF simulations for 19 summers from 2000 to 2018 are conducted with four different land surface schemes (hereafter referred to as Exp-CLM, Exp-Noah-MP, Exp-PX and Exp-SSiB, respectively). The initial and boundary conditions for the WRF model simulations are provided from the NCEP-FNL analysis product. The ERA-Interim reanalysis (ERA), the GHCN-CAMS (CAMS) and the CRU gridded data are used to comprehensively evaluate the WRF simulations. Compared with verification data, the WRF model with high resolution can reasonably reproduce the spatial patterns of summer mean large scale atmospheric circulation, 2-m temperature and precipitation. The simulation results, however, are sensitive to the option of land surface scheme. The performance of Exp-CLM4 and Exp-SSiB are better than that of Exp-Noah-MP and Exp-PX assessed by the multivariable integrated evaluation method. To comprehensively understand the dynamic and physical mechanisms behind the WRF model sensitivity to land surface schemes, the differences in the surface energy balance between the ensemble means Ens-CLM4-SSiB and Ens-NoanMP-PX are analyzed in detail. The results demonstrate that the intensity of the simulated sensible heat flux over Central Asia is weaker in Ens-CLM4-SSiB than that in Ens-NoahMP-PX. As a result, large differences in geopotential height occur over the model simulation domain. The simulated wind fields are subsequently affected due to the geostrophic adjustment process, thus the simulation of 2-m temperature, precipitation, surface soil moisture and surface skin temperature are all affected.

How to cite: Lu, S., Guo, W., Xue, Y., and Huang, F.: Sensitivity of high resolution WRF model to land surface schemes in simulating boreal summer climate over Central Asia, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-1877, https://doi.org/10.5194/egusphere-egu2020-1877, 2020.

Black carbon (BC) can change the energy budget of the earth system by strongly absorbing solar radiation: both suspended in the atmosphere, incorporated into cloud droplets, or deposited onto high-albedo surfaces. BC’s direct radiative forcing is highly dependent on its vertical distribution. However, due to large variabilities and the small number of vertical profile measurements, there is still large uncertainty in this forcing value. Moreover, the vertical profile of BC and its relative elevation to clouds determine BC’s lifetime in the atmosphere and its transport and removal processes. In November-December 2017, a series of tethered balloon flights was launched at the Southeast Tibet Observation and Research Station for the Alpine Environment of the Chinese Academy of Sciences. A cylindrical balloon with a diameter of 7.9 m and maximum volume of 1250 m³ was used. A 7-channel Aethalometer was installed in the gondola attached to the balloon, together with several other instruments including a GPS for altitude, and sensors for temperature and relative humidity. The airborne Aethalometer measured BC mass concentration (ng/m³) on a on a 1-second timebase at 7 wavelengths ranging from 370 nm to 950 nm. Meanwhile, another Aethalometer was used to monitor BC mass concentration near the surface, at a height of about 10 m above the ground. From the tethered balloon flights, we derived three profiles designated as ‘F1’, ‘F3-ASC’, and ‘F3-DES’. The maximum height for the F1 flight was 500 m a.g.l., namely 3800 m a.s.l.; while the maximum height for the F3 flight was 1950 m a.g.l., namely 5250 m a.s.l. Based on the potential temperature and relative humidity data, the profiles were divided into three layers: the stable boundary layer (SBL), the residual layer (RL), and the free troposphere (FT). The vertical distribution of BC shows a prominent peak within the SBL. The mean BC concentration in SBL (1000±750 ng/m³) was one order of magnitude higher than in RL and FT, which were 140±40 ng/m³ and 120±40 ng/m³, respectively. The BC concentration measured in the present study in FT over the southeastern Tibetan Plateau is comparable to measurements in Arctic regions, but lower than values in South Asia. Analysis of the wavelength dependence of the data yields an estimate of the biomass burning contribution. This showed a maximum value in SBL of 44±37%, and was 16±6% in RL and 13±5% in FT. Analysis of 24-hour isentropic back trajectories showed that BC in SBL and RL was dominated by local sources, while in the FT, BC is mainly influenced by mid- to long-distant transport by the westerlies. In addition, analysis of the variations of BC concentration and biomass burning contribution on a high-resolution time scale showed that BC concentrations and the nature of their sources are largely influenced by air mass origins and transport. To our knowledge, this is the first ever in situ measurement of BC concentration over the Tibetan Plateau in the atmospheric boundary layer and free troposphere up to 5000 m a.s.l.

How to cite: Wang, M., Xu, B., Yang, S., Gao, J., Zhang, T., He, Z., Kobal, M., and Hansen, A.: Black Carbon profiles from tethered balloon flights over the Southeastern Tibetan Plateau, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-1926, https://doi.org/10.5194/egusphere-egu2020-1926, 2020.

It is very difficult to predict accurate temperature, especially for maximum and minimum temperature, due to the large diurnal temperature range in arid area. Based on the temperature forecast products from ECMWF, T639, DOGRAFS and GRAPES models and hourly temperature observations at 105 automatic weather stations in Xinjiang during 2013~2015, two kinds of error correction and integration schemes were designed by using the decaying averaging method, ensemble average and weighted ensemble average method, the effects of error correction and integration on predicted maximum and minimum temperature in fore seasons in different partitions Xinjiang were tested contrastively. The first scheme was integrating forecast temperature before correcting errors, while the second scheme was correcting forecast errors firstly and then giving an integration. The results are follows as: (1)The accuracy of temperature predictions from ECMWF model was the best in Xinjiang as a whole, while that from DOGRAFS model was the worst, and the improvement to minimum temperature predictions was higher than that of maximum temperature prediction. (2) With regarding to different partitions Xinjiang, the accuracies of predicted maximum and minimum temperature in northern Xinjiang, west region and plain areas were correspondingly higher than those in southern Xinjiang, east region and mountain areas, and the correction capability to temperature prediction in winter was higher than that in other seasons. (3) The integrated prediction of maximum and minimum temperature by weighted ensemble average method was better than that of ensemble average method. The second scheme was superior to the first scheme. (4) The improvement to maximum(minimum) temperature prediction in the extreme high(low) temperature event process from 13 to 30 July 2017(from 22 to 24 April 2014) in Xinjiang was significant by using the second scheme.

How to cite: lihong, J.: Research on Error Correction and Integration Methods of Maximum and Minimum Temperature Forecast Based on Multi –model in arid area, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-2112, https://doi.org/10.5194/egusphere-egu2020-2112, 2020.

CO₂ fluxes and concentrations are not well understood in Northeast China, where dominant land surface types are mixed forest and cropland.  Here, we analyzed the CO₂ fluxes and concentrations using Eddy Covariance (EC) measurements, satellite observations, and the Weather Research and Forecasting model coupled with the Vegetation Photosynthesis and Respiration Model (WRF-VPRM).  We also used WRF-VPRM outputs to examine CO₂ transport/dispersion, and to quantify the biogenic and anthropogenic contributions to atmospheric CO₂ concentrations.  Finally, we investigated the uncertainties of simulating CO₂ fluxes related to four VPRM parameters (including maximum light use efficiency, photosynthetically active radiation half-saturation value, and two respiration parameters) using offline ensemble simulations with randomly selected parameter values.  The results indicated that mixed forests acted as a larger CO₂ source and sink than rice paddies on average in 2016 due to a longer growth period and stronger ecosystem respiration, although the minimum EC-measured daily mean net ecosystem exchange (NEE) was smaller at rice paddy (-10 μmol m^-2 s^-1) than at mixed forest (-6.5 μmol m^-2 s^-1) during the growing season (May through September).  The monthly fluctuation of column-averaged CO₂ concentrations (XCO₂) exceeded 10 ppm in Northeast China during 2016.  Biogenic contribution (large negative in summer and insignificant in other months) offset about 70% of anthropogenic contribution of XCO₂ in this region.  WRF-VPRM modeling successfully captured seasonal and episodic variations of NEE and CO₂ concentrations, however, the NEE in mixed forest was overestimated during daytime, mainly due to the uncertainties of VPRM parameters, especially maximum light use efficiency.

How to cite: Li, X., Hu, X.-M., Cai, C., Jia, Q., Zhang, Y., and Liu, J.: Terrestrial CO2 Fluxes, Concentrations, Sources and Budget in Northeast China: Observational and Modeling Studies, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-2317, https://doi.org/10.5194/egusphere-egu2020-2317, 2020.

A Tibetan Plateau vortex (TPV) is defined as a shallow cyclonic meso-α-scale low-pressure system that originates over the main body of the Tibetan Plateau in the warm season and presents most notably at 500 hPa. It is the main precipitation-inducing weather system over the plateau in the warm season.

Knowledge of the TPV structure is of considerable importance for understanding the generation and development mechanisms of this mesoscale system. However, our understanding of vortex structures and our ability to classify them on a physical basis is limited due to insufficient observations. The high-resolution NCEP Climate Forecast System Reanalysis (CFSR) dataset is used in the present paper to investigate the general structural features of various types of mature TPV through classification and composite structure analysis. Results indicate that the dynamic and thermodynamic structures show regional and seasonal dependency, as well as being influenced by attributes of translation, associated precipitation, and the South Asian high (SAH).

The common precipitating TPV (type I), frequently occurring in the west–east-oriented zonal region between 33° and 36°N, is a notably low-level baroclinic and asymmetric system. It resides within a large-scale confluent zone and preferentially travels eastwards, potentially moving out of the plateau. The heavy rain vortex (type II) corresponds to a deep vortex circulation occurring in midsummer. The low-level baroclinic sub-category (type IIa) is associated with a low-level jet and mainly originates in the area (32°–35°N, 86°–94°E), preferentially moving east of 90°E and even away from the plateau; meanwhile, the nearly upright sub-category (type IIb), which has a cold center at low levels and a warm center at mid-upper levels, is a quasi-stationary and quasi-symmetric system favorably occurring west of 92°E. A western-pattern SAH exists in the upper troposphere for these two sub-categories. The springtime dry vortex in the western plateau (type III) is warm and shallow (~100 hPa deep), and zonal circulation dominates the large-scale environmental flows in the middle and upper troposphere. The precipitating vortex in the southern plateau occurring during July–August (type IV) is not affected by northerly flow at low levels. It is vertically aligned and controlled by a banded SAH.

How to cite: Feng, X., Liu, C., Fan, G., and Zhang, J.: Structures of Different Tibetan Plateau Vortex Types, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-2533, https://doi.org/10.5194/egusphere-egu2020-2533, 2020.

Firstly, based on the difference of model and in-situ observations, a serious of sensitive experiments were done by using WRF. In order to use remote sensing products, a land-atmosphere model was initialized by ingesting AMSR-E RS products, and the results were compared with the default model configuration and with in-situ long-term CAMP/Tibet observations.

Secondly, a land-atmosphere model was initialized by ingesting AMSR-E products, and the results were compared with the default model configuration and with in-situ long-term CAMP/Tibet observations. The differences between the AMSR-E initialized model runs with the default model configuration and in situ data showed an apparent inconsistency in the model-simulated land surface heat fluxes. The results showed that the soil moisture was sensitive to the specific model configuration. To evaluate and verify the model stability, a long-term modeling study with AMSR-E soil moisture data ingestion was performed. Based on test simulations, AMSR-E data were assimilated into an atmospheric model for July and August 2007. The results showed that the land surface fluxes agreed well with both the in-situ data and the results of the default model configuration. Therefore, the simulation can be used to retrieve land surface heat fluxes from an atmospheric model over the Tibetan Plateau.

All of the different methods will clarify the land surface heating field in complex plateau, it also can affect atmospheric cycle over the Tibetan Plateau even all of the global atmospheric cycle pattern.

How to cite: Ma, W., Ma, Y., Han, Y., Hu, W., and Zhong, L.: The evaluation of AMSR-E soil moisture data in atmospheric modeling using a suitable time series iteration to derive land surface fluxes over the Tibetan Plateau, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-2546, https://doi.org/10.5194/egusphere-egu2020-2546, 2020.

The combination of in situ observations from a large tethered balloon and remote sensing instruments (aerosol lidar and Doppler wind lidar) enabled the evolution of the residual layer (RL) to be observed during an intensive vertical detection experiment of the planetary boundary layer (PBL) conducted during December (Dec) 2018 in Wangdu County, China. This paper focused on the important role played by the RL in the variations of the vertical distributions of pollutant particulates. The results of the present analysis revealed the following. (1) A considerable proportion of pollutant particulates remained suspended in the RL (e.g., the nitrate concentration reached 30 µg m^-3) in the nocturnal boundary layer (NBL). Multilayer pollutant structures appeared often, partly because of the existence of the RL. Because pollutants were still stored in the RL and the shallow surface inversion layer, the aerosol lidar-calculated PBL height was closer to the top of the RL before midnight in the NBL; after midnight, the PBL height was more consistent with the top of the surface inversion layer. (2) As the convective mixing layer gradually became established after sunrise the following day, the pollutants stored in the nocturnal RL of the preceding night were entrained downward into the mixing layer. The early morning PM_2.5 concentration near 700 m in the RL on Dec 20 decreased obviously compared with the concentration at 13:34 on Dec 20 at the same height (ranging from 30 µg m^-3 to 5 µg m^-3). The nitrate concentration also decreased significantly in the RL, but its concentration increased to 12 µg m^-3 in the mixing layer. Near-surface PM_2.5 diffused upward more easily due to strong vertical mixing during the daytime, causing reductions in the surface concentration. The mixing layer heights in Wangdu County were estimated to be 600 m in the winter, and various emitted pollutant particulates eventually became well-mixed within the mixing layer. The daytime mixing layer heights were consistent with the PBL heights calculated by aerosol lidar representing the pollutant accumulation depth. (3) The RL was characterized by a Richardson number (Ri) below the threshold value of 0.25, revealing that turbulence still existed within the RL.

How to cite: Yu, S., Hu, F., Sun, H., Zhang, Z., and Ding, W.: The impacts of residual layer on the vertical distributions of pollutant particulate matter: combining large tethered balloon and remote sensing observations, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-2599, https://doi.org/10.5194/egusphere-egu2020-2599, 2020.

Physicochemical characteristics of the atmospheric boundary layer over North Plain China during the comprehensive observation experiment from 10 to 21 December 2018 were investigated in this paper. The observation data are obtained from the large tethered balloon, Doppler wind lidar, ground-level instruments. The maximum concentration of PM_2.5 exceeded 200 µg m-3, and the ratio value of PM_2.5/PM₁₀ was basically around 0.4 (maximum has reached approximately 0.8) during the whole observation period, indicating that explosive growth of fine ode dominant aerosols during the winter heating season. The peak solar irradiance was slightly larger on the clean day, compared with the value during the pollution process. The correlation coefficient between the concentration of PM_2.5 and CO was highest (0.725) among the gas pollutants, and the relationship between O₃ and PM_2.5 was basically negative correlated, not simple linear relationship. Three distinctly different vertical profile types of the PM_2.5 were categorized according to the vertical changes based on the total 33 vertical profiles obtained by the tethered balloon. Type 1 was mainly observed in the daytime, accounted for nearly 51.5%, the PM_2.5 concentration decreased nearly linearly as a function of height below approximate 600 m; Type 2 shows a sharp decreasing trend from the ground to about 200 m; Type 3 shows multi-layer structure of pollutants, some pollutants suspended aloft in upper air. The vertical profile of PM_2.5 was closely related to the atmospheric vertical structure such as the wind, temperature and turbulent kinetic energy, caused by the diurnal variation of the boundary layer. Small wind layer and the weak turbulence activities contributed to the accumulation of pollutants. Vertical patterns of the concentration of PM_2.5 were also greatly affected by the local ground emission sources and regional transport processes.

How to cite: Sun, H., Shi, Y., Hu, F., Zhang, Z., and Ding, W.: Analysis of physicochemical characteristics in the atmospheric boundary layer over the North Plain China based on large tethered balloon and Doppler wind lidar, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-2795, https://doi.org/10.5194/egusphere-egu2020-2795, 2020.

Studies with satellite-based passive microwave L-band observations have been fostered strongly by the launch of NASA's Soil Moisture Active Passive (SMAP) satellite on January 31, 2015 (Entekhabi et al. 2010), which complements and extends the observations at L-band by the ESA's Soil Moisture Ocean Salinity (SMOS) mission in orbit since 2009 (Kerr et al. 2001, Mecklenburg et al. 2012, Lievens et al. 2014). SMOS and SMAP data assimilation studies started during their pre- and post-launch period. Flores et al. (2012) used an Ensemble Kalman Filter to constrain the uncertainties of the simulated soil moisture fields from physical-based hydrological models. Our work intends to explore the use and value of passive L-band satellite observations for ensemble-based data assimilation with fully-coupled terrestrial system models for mesoscale catchments. An observation operator for satellite-based passive microwave (PMW) observations based on the community microwave emission model (CMEM) (de Rosnay et al. 2009, Drusch et al. 2009) has been modified, applied and tested in an ideal case developed within the FOR2131 (Schalge et al. 2016) with the coupled subsurface-land surface-atmosphere simulation platform TerrSysMP (Shrestha et al. 2014), which couples ParFlow (subsurface), Community Land Model (CLM, surface), and COSMO (atmosphere). We achieve the development of a satellite simulator for passive L-band observations of the satellite missions SMAP and SMOS and its adaptation to the ideal case, and the lower-resolution TerrSysMP model applied for data assimilation (TerrSysMP-PDAF).

How to cite: Lv, S., Poll, S., Schalge, B., Garfias, P., and Simmer, C.: The implementation of Community Microwave Emission Model (CMEM) as the observation operator in TerrsysMP-PDAF, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-3073, https://doi.org/10.5194/egusphere-egu2020-3073, 2020.

The Community Land Model version 4.5(CLM4.5), driven by the atmospheric forcing dataset CRUNCEP, was used to simulate the spatial and temporal characteristics of soil moisture(SM) across the Tibetan Plateau (TP) from 1981 to 2016. This study reveals the relationship between SM on the TP in May and summer precipitation in eastern China and the physical mechanism for the impact of SM on summer precipitation. To investigate the relationship between SM on the TP in May and the summer precipitation in eastern China, this study used the monthly mean SM data from CLM4.5 and monthly precipitation data from CN05.1 for the period from 1981 to 2016. Singular value decomposition (SVD) analysis shows that the surface SM in the south-central TP was positively related to the summer precipitation in South China and negatively related to that in the middle and lower reaches of the Yangtze River and Northeast China. The SM in the western TP was the opposite of that in the south-central region. The wetter the surface SM in the south-central TP in May was, the lower the surface temperature, sensible heat flux and net longwave radiation flux, and the higher the latent heat flux and net shortwave radiation flux, leading to weaker surface heating. In contrast, lower surface SM in the western TP led to stronger surface heating. This led to a weaker western Pacific subtropical high and a more northerly rain belt. The weather in South China was controlled by large cyclonic circulations forming convergences and updrafts that led to more rainfall in South China. The precipitation in the middle and lower reaches of the Yangtze River and Northeast China was less under the control of a single summer monsoon than that in South China.

How to cite: Lai, X. and Yuan, Y.: The Impacts of soil moisture over the Tibetan Plateau on Summer Precipitation in China, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-3808, https://doi.org/10.5194/egusphere-egu2020-3808, 2020.

Evapotranspiration (ET), composed of evaporation (ETs) and transpiration (ETc) and intercept water (ETw), plays an indispensable role in the water cycle and energy balance of land surface processes. A more accurate estimation of ET variations is essential for natural hazard monitoring and water resource management. For the cold, arid, and semi-arid regions of the Tibetan Plateau (TP), previous studies often overlooked the decisive role of soil properties in ETs rates. In this paper, an improved algorithm for ETs in bare soil and an optimized parameter for ETc over meadow based on MOD16 model are proposed for the TP. The nonlinear relationship between surface evaporation resistance (r_s^s) and soil surface hydration state in different soil texture is redefined by ground-based measurements over the TP. Wind speed and vegetation height were integrated to estimate aerodynamic resistance by Yang et al. (2008). The validated value of the mean potential stomatal conductance per unit leaf area (C_L) is 0.0038m s^-1. And the algorithm was then compared with the original MOD16 algorithm and a soil water index–based Priestley-Taylor algorithm (SWI–PT). After examining the performance of the three models at 5 grass flux tower sites in different soil texture over the TP, East Asia, and America, the validation results showed that the half-hour estimates from the improved-MOD16 were closer to observations than those of the other models under the all-weather in each site. The average correlation coefficient(R²) of the improved-MOD16 model was 0.83, compared with 0.75 in the original MOD16 model and 0.78 in SWI-PT model. The average values of the root mean square error (RMSE) are 35.77W m^-2, 79.46 W m^-2, and 73.88W m^-2 respectively. The average values of the mean bias (MB) are -4.08W m^-2, -52.36W m^-2, and -11.74 W m^-2 overall sites, respectively. The performance of these algorithms are better achieved on daily (R²=0.81, RMSE=17.22W m^-2, MB=-4.12W m^-2; R²=0.64, RMSE=56.55W m^-2, MB=-48.74W m^-2; R2=0.78, RMSE=22.3W m^-2, MB=-9.82W m^-2) and monthly (R2=0.93, RMSE=23.35W m^-2, MB=-2.8W m^-2; R2=0.86, RMSE=69.11W m^-2, MB=-39.5W m^-2; R2=0.79, RMSE=62.8W m^-2, MB=-9.7W m^-2) scales. Overall, the results showed that the newly developed MOD16 model captured ET more accurately than the other two models. The comparisons between the modified algorithm and two mainstream methods suggested that the modified algorithm could produce high accuracy ET over the meadow sites and has great potential for land surface model improvements and remote sensing ET promotion for the ET region.

How to cite: Yuan, L., Ma, Y., and Chen, X.: Developing the soil texture effects on the surface resistance to bare soil based on MOD16 algorithm to estimate evapotranspiration over the Tibetan Plateau, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-3833, https://doi.org/10.5194/egusphere-egu2020-3833, 2020.

The planetary boundary layer (PBL) parameterization schemes play a critical role in the weather and climate models, while they describe physical processes associated with the momentum, heat and humidity exchange between land surface and atmosphere. The sensitivity of boundary layer variables to eight PBL parameterization schemes (three non-local and five local closure schemes), available in the Weather Research and Forecasting(WRF) model, is evaluated over the central Tibetan Plateau with field measurements of the Third Tibetan Plateau atmospheric scientific experiment (TIPEX III) in July. Model results showed acceptable behavior, but no particular scheme produced the best performances for all observation stations and meteorological parameters. All PBL schemes underestimated the surface temperature over the central Tibetan Plateau. The BouLac scheme showed the minimum cold bias of the surface temperature. For the surface energy budget components, it was found that the sensible heat flux and the downward longwave radiation were the main factors causing the lower surface temperature. The sub-grid scale gravity wave drag was added to reduce biases result from unresolved topography over the central Tibetan Plateau. It led to smaller cold bias, causing warmer lower-tropospheric temperature, smaller water vapor content and higher PBL height. The modified model results show more close to the observation.

How to cite: Xu, L., Liu, H., Du, Q., and Liu, Y.: The improvement of the planetary boundary layer simulation over the central Tibetan Plateau, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-3842, https://doi.org/10.5194/egusphere-egu2020-3842, 2020.

Surface soil moisture and freeze/thaw state monitoring is essential for quantifying water and heat exchanges in cold regions, e.g. the Tibetan Plateau. L-band (1.4 GHz, 21 cm) radiometry is recognized as one of the best suitable techniques for global monitoring of soil moisture and freeze-thaw dynamics. This study reports a long term ground-based L-band radiometry measurements conducted in a seasonally frozen grassland site located in the northeastern part of the Tibetan Plateau. The ESA funded ELBARA-III radiometer is deployed in a Tibetan meadow ecosystem where a well-instrumented in-situ soil moisture and soil temperature (SMST) monitoring network was developed. The network holds 20 SMST profile measurement stations, and each station records every 15-min readings of 5TM ECH2O probes installed at soil depths of 5, 10, 20, 40, and 80 cm. The ELBARA-III radiometer has been deployed in the center of the SMST network at the beginning of 2016. The L-band radiometer is mounted on a tower with a height of 4.8m, and the antenna beam waist is about 6.5m above the surface. Brightness temperature (T_B) measurements with vertical and horizontal polarizations are performed every 30 min at observation angles of 40° to 70° in steps of 5°. A sky measurement with an observation angle of 155° is performed once per day for calibration purposes next to the internal calibration sequence performed as part of every measurement run. The internal calibration adopted to derive the T_B from the raw data is based on a two-point calibration strategy using a resistive load (RL) and an active cold load (ACL). A vertically dense SMST measurement profile is installed next to the radiometer tower. Concurrent measurements of micrometeorological variables are also performed in vicinity of the radiometer tower, such as solar radiation, wind speed, air temperature, air pressure, and humidity. A rain gauge and eddy-covariance system are setup in the ELBARA-III field site at the end of 2016 providing precipitation and surface heat flux measurements. Preliminary analysis of the ELBARA-III T_B measurements will be given in this study.

How to cite: Wen, J., Su, Z., Zheng, D., and Wang, X.: L-band Radiometry Measurement in the Tibetan Plateau, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-3978, https://doi.org/10.5194/egusphere-egu2020-3978, 2020.

Snow falls frequently over the Tibetan Plateau, and is a vital component of the widespread cryosphere which has vital feedback to climate change. Snowfall and the subsequent evolution of the snowpack have a large effect on surface energy balance and water cycle. Albedo, the main determinant of net radiation flux, is a major driver of land surface processes. However, the current widely used Noah land surface model does not describe snow albedo correctly, although it keeps snow-related variables i.e. snow cover and age into account. In our study, the impact of an improved albedo parameterization scheme in WRF coupled with Noah was investigated. In the improved albedo scheme, albedo was parameterized as functions of snow depth and age which was developed using remote sensing retrievals of albedo. Numerical experiments were conducted to model a severe snow event in March 2017. The performance of WRF coupled with Noah applying the improved albedo scheme was compared with that of applying the default albedo scheme and with that of WRF coupled with CLM applying CLM’s complex albedo scheme. First, the improved albedo scheme largely reduces the WRF coupled with Noah albedo overestimation in the southeastern Tibetan Plateau, remarkably reducing the large cold bias estimates by 0.7 ℃ air temperature RMSE. Second, the improved albedo scheme gives the highest correlationship between the satellite-derived and the model estimated albedo, contributing to achieve the SWE spatial pattern, heavy snow belt and maximum SWE estimates in eastern Tibetan Plateau. Remarkable underestimation of albedo in WRF coupled with CLM contributes to regional maximum SWE underestimation and failure in heavy snow belt estimates.

In addition, WRF default land cover and green vegetation fraction were out of date but played a large impact on estimates of air temperature, albedo and SWE. Updated land parameters led to improve the model performance in simulating the severe snow event, by reducing albedo RMSE by 1%-4%. The choice of the algorithm to retrieve green vegetation fraction had a large impact on the accuracy of green vegetation fraction retrievals. It remains open to debate the optimal algorithm to estimate land surface properties in the complex topographic Tibetan Plateau.

How to cite: Liu, L., Menenti, M., Ma, Y., and Ma, W.: Evaluation of WRF coupled with Noah using an improved albedo parameterization scheme during a severe snow event over the Tibetan Plateau, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-4000, https://doi.org/10.5194/egusphere-egu2020-4000, 2020.

The northwest China is located at the northeast of the Tibet Plateau, with a broad zone and complex terrain. The torrential rain occurred occasionally in the region. The formation of torrential rain and defensive ability of human beings are different due to the complex terrain. The storms occurred simultaneously with mountain torrents and debris flows, resulting in major casualties and economic losses. Studies have shown that most of the heavy rain occurred in the front of upper trough under the background of warm and wet southwest flow and near the shear line formed by both northerly and southerly at low level. A heavy rain occurred at the east side of the Tibet Plateau is completely different from previous features of heavy rain in the same region. It happened under the control of warm high ridge and south wind flow field in synoptic scale. Heavy precipitation has emerged in the warm region before large scale rain belt arrived. The torrential rain occurred in warm region mostly appeared in south China and rarely in north area. It has the feature of severe convective precipitation with weak disturbance in synoptic scale. The NWP model is capacity-constrained to forecast it.

A torrential rain in warm sector occurred at east side of Tibet Plateau, with the maximum hourly rainfall of 65mm, along with thunder and lightning. The evolution of mesoscale convective system was analyzed focusing on the development and propagation at by using the data of satellite, CINRAD, automatic weather stations, the conventional observation, and NCEP/NCAR reanalysis data. The results show that, due to the bell-like terrain of the east of Tibet Plateau and the block of Liupanshan mountain, a low-level jet formed as long as 200-300 km on 700 hPa. The low level jet triggered the development of convective cloud band. The forward propagation of Meso-β-scale convective cloud cluster (MCS) was the major cause of Torrential rain. The radar echoes showed obvious characteristics of low center of mass warm cloud precipitation, the zonal distribution in north and south of strong echo monomer greater than 35 dBz, the movement of convective cells with 1time/h along the low-level Jet from south to north. The significant train effect formed zonal torrential rain at east side of Tibet Plateau.

In the environmental conditions of high temperature and humidity, extreme instability of the atmosphere and a potential for severe convective weather, more attention should be paid to the formation and maintain of southwest low-level Jet. It is significant to the formation and development of the convective system in warm sector. In order to improve the forecast ability of NWP model, it is necessary to investigate the mechanics of the formation of torrential rain in the warm sector.

Key words: East side of the Tibet Plateau; Low level Jet; Convective cloud band; Convective cells propagation; Torrential rain in Warm sector

How to cite: Zhao, Q. and Zhang, W.: The Mesoscale Convection System of Torrential Rain in Warm Sector over East Side of the Tibet Plateau, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-4168, https://doi.org/10.5194/egusphere-egu2020-4168, 2020.

As land-surface properties are heterogeneous over a broad range of length-scales, surface-induced fluxes are heterogeneous too. Representing land-surface heterogeneity and the corresponding fluxes is a challenging task in numerical prediction of weather and projection of climate.

In this work, we introduce the approach of 'para-real' ensemble modelling to investigate the dynamic effect of land-surface heterogeneity. We perform a large ensemble of high-resolution simulations using the Weather research and forecast model (WRF-ARW-LSM). The para-real simulation ensembles are externally forced by a reanalysis of a real case in spring 2013, but become exposed to different synthesized surface patterns (SP) generated as quasi-fractal Brownian surfaces (quasi-fBs) with exact control of the dominant wave length and fractal persistence.

The focus of this study is on the three inter-related land-surface and atmosphere coupling mechanisms--the thermodynamic coupling, aerodynamic coupling, and hydrological coupling. For each mechanism, a corresponding surface property is identified, namely surface albedo (α) for thermodynamic coupling, roughness length (z₀) for aerodynamic coupling, and soil type (s_t) for hydrological coupling. For each surface property, we generate a set of quasi-fBs with different dominant length scale and fractal persistence. In our para-real ensembles, the original fields of the surface properties are replaced by the quasi-fBs, for which we estimate the control parameters from the original data, i.e., the probability density distribution of the original data matches that of the quasi-fBs which eliminates the flux aggregation effect and allows us to focus on the dynamic effect.

We find, first, a strong impact of the length scale of the surface forcing on the intensity of coupling: while the dynamic effect of surface heterogeneity significantly impacts the state of the atmospheric boundary layer for all cases investigated,  the impact of the surface signal on the atmospheric state  grows with the length-scale of the surface heterogeneity. Second, we demonstrate that larger fractal persistence of the surface signal also strengthens the atmosphere--surface coupling. Third, the qualitative impact of the surface forcing is shown to depend on time, which eliminates the possibility of a simple linear forward propagation of the surface signal; there is strong sensitivity to the diurnal cycle, in particular with respect to the horizontal wind components: The maximum intensity of atmosphere--surface coupling (measured in terms of correlation) is found around noon for the atmospheric temperature, and some hours later (in the early afternoon) for water vapor. Fourth, among the different surface forcing investigated, we find that the heterogeneity of soil type is the most important to the atmospheric state--surface exchanges and its signal are detected in the atmospheric water-vapor up to 2km height; in particular, the soil-type pattern with the smallest length-scale causes a doubling of cloud-water above 500m height  whereas no impact on the bulk atmospheric state is found for patterns with other length-scales and fractal persistence or forcing of other surface variables. This illustrates the key part that hydrological coupling plays in connecting the atmosphere to the surface, and it underlines the relevance of improved hydrological process-level representation for improved parameterization of the coupled land--atmosphere system.

How to cite: Parsakhoo, Z., Ansorge, C., and Shao, Y.: Modelling multi-scale atmosphere and land-surface interactions, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-4181, https://doi.org/10.5194/egusphere-egu2020-4181, 2020.

Based on the encryption automatic station data, the conventional ground and high altitude observation data, the FY2 static satellite data, and the initial field data of the ECMWF fine grid forecast model (spatial resolution 0.125 °× 0.125 °) in Tarim Basin in the southern Xinjiang, the rare rainstorm process occurred on the north slope of Kunlun Mountains from 24-26 June 2019 is analyzed. Aiming at the circulation situation, the weather system and the configuration of the high and low altitude systems, the plateau weather systems such as the Qinghai-Tibet high pressure, the plateau low vortex and shear line, and the jet stream south of the plateau were analyzed. Their important effects of the formation of Rainstorm on the northern slope of Kunlun Mountain is concluded as follows:

(1) The development and maintenance of the Qinghai-Tibet Plateau weather system are generated during favorable weather-scale dynamic and thermal processes, which are mainly manifested in the following three aspects: First of all, the South Asian High pressure changed from a double type to Qinghai-Tibet high pressure at 100hPa. At 200 to 300hPa, the southwestern jet stream lifted northward from the plateau and strengthened in the Tarim Basin in the southern Xinjiang. Suction effect can promote the ascending movement over the rainstorm area; Secondly, the low value system of the shear line nearly in the north-south direction between the Qinghai-Tibet high, the plateau vortex, the shear line and the Indian low is stable in 500hPa. The southerly flow prevails in the periphery of the West Pacific subtropical high, which runs through the Qinghai-Tibet Plateau and the South Xinjiang basin from the Bay of Bengal. The positive vorticity advection and warm advection on the southerly flow over the Qinghai-Tibet Plateau are conducive to the large-scale uplift movement over the rainstorm area and the western part of South Xinjiang, forming water vapor channel from south to north. While warm air transporting to the north, the North-South cold and warm air convergence is enhanced. Thirdly, the coupling between strong high-level divergence and middle-level convergence during heavy rains can result in enhanced mid-level water vapor convergence and vertical water vapor transport.

 (2) Weather systems below 600hPa have positive feedback on the maintenance and development of plateau weather systems. Easterly airflow was in the Tarim Basin in the southern Xinjiang between 600hPa and 700Pa，and the airflow at 600hPa was stronger than 700hPa. The easterly airflow carried part of the cold air into the Tarim Basin in the southern Xinjiang. A cold pad was formed in the lower layer below 600hPa in the southern Xinjiang basin, which facilitated the transfer of warm and humid air northward by the 500hPa middle-south wind and the 500 to 200hPa ascent movement development and maintain, while exacerbating the vertical cold and warm exchanges.

 (3) Water vapor mainly comes from the Bay of Bengal, the Caspian Sea and the Aral Sea, but the water vapor contribution from the Bay of Bengal is even greater.

How to cite: junlan, Z.: Impact of the Qinghai-Tibet Plateau Weather System on the Rainstorm on the North Slope of Kunlun Mountain, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-4311, https://doi.org/10.5194/egusphere-egu2020-4311, 2020.

Understanding seasonal variability in n-alkane δD values (δD_wax) among plant forms/lineages and the underlying physiological and biochemical factors that causes it is crucial for δD_wax-based quantitative paleoclimate reconstruction. Herein, we present parallel controlled study of Stipa bungeana (monocotyledonous grass) and Quercus aquifolioides (dicotyledonous tree) by conducting semimonthly paired δD analysis of precipitation, soil and leaf water, and n-alkanes over two years. We show that δD_wax in both plants inherit precipitation hydrogen isotopic compositions throughout the growing season. However, it is synchronous in S. bungeana and belated in Q. aquifolioides. We reveal previously unrecognized phenomenon that, for trees alkanes with higher concentration percentages utilize lighter deuterium preferentially, whereas grasses do not. We conclude that dicotyledonous trees have a selection mechanism whereby leaf water hydrogen is utilized for n-alkane biosynthesis, whereas monocotyledonous grasses do not. This fundamentally explains δD_wax discrepancy between dicotyledonous trees and monocotyledonous grasses, having significant implications for δD_wax paleoapplication.

How to cite: Zhang, X., Xu, B., Günther, F., and Gleixner, G.: Seasonal variability and differences in n-alkane deltaD values between dicotyledonous tree and monocotyledonous grass, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-4414, https://doi.org/10.5194/egusphere-egu2020-4414, 2020.

Abstract: Water plays a vital role in plants, animals and human survival, as well as water resources planning and protection. The spatial and temporal changes of rivers have a profound impact on climate change and the scientific protection of the regional ecological environment in Qingzang-Tibet plateau. Due to the influence of snow and cloud cover, optical remote sensing images in this region have less effective coverage. Many researches in the past mainly faced the challenge of misclassification caused by shadows from cloud and mountain. In this study, we proposed a method to improve the extraction of rivers by reducing the effect of shadows by fusing Sentinel-1 radar data and Sentinel-2 optical imagery. For the optical imagery, water indices including MNDWI (Modified Normalized Difference Water Index) and RNDWI (Revised Normalized Difference Water Index) and morphological operations were used to extract the river coverage. In addition, radar data is used to extract water in areas where there is no optical image coverage or where optical images are misclassified by using a combination of both the histogram and Otsu threshold methods. The GEE (Google Earth Engine) platform is used to implement the analysis using two classification datasets at a regional level. Relevant results from Sentinel-1 and Sentinel-2 data showed that the RNDWI has a more accurate water extraction results in this region. We further compared the final river width results with the manually measured samples from Google Earth and situ data of hydrological stations for accuracy assessment. The R² value is 0.90, and the standard deviation is 18.663m. The river width can be estimated well by this method, which can provide basic data for the study of water in depopulated zone.

Keywords: Remote sensing, shadow removal, water extraction, water index, Otsu threshold, Google Earth Engine

How to cite: Li, D., Wu, B., Chen, B., Wang, Y., Zhang, Y., Xue, Y., and Qin, C.: Fusion of Sentinel-1 radar and Sentinel-2 MSI imagery for water extraction in Tibetan plateau, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-4512, https://doi.org/10.5194/egusphere-egu2020-4512, 2020.

Green vegetation fraction (GVF) has a prominent influence on the partitioning of surface sensible and latent heat fluxes in numerical weather prediction models. However, the multi-year monthly GVF climatology, which is the most commonly-used representation of vegetation states in models, has limited ability to capture the real-time vegetation status. In our study, a near real-time (NRT) GVF dataset generated from 8-day composite of the normalized difference vegetation index (NDVI) is compared with the 10-year averaged monthly GVF provided by the Weather Research and Forecasting (WRF) model. We examine the annual and inter-annual variability of the GVF over North China in details. Many differences of the GVF between the two datasets are found over the dryland cropland and grassland areas. Two experiments using different GVF datasets are performed to assess the impact of the GVF on the forecasts of screen-level temperature and humidity for one year. The results show that using the NRT GVF can lead to a widespread reduction of 2-m temperature in the order of 0.5 ℃, and an increase of 2-m humidity during the warm season. An evaluation against in-situ observations displays an overall positive impact on the near surface parameter forecasts. Over the dryland cropland and grassland areas, a quantitative validation shows that the root mean square errors of 24-h forecasts decline by 9%, 10% and 6% for 2-m temperature, 2-m specific humidity and 10-m wind speed, respectively, in May of 2012. Our study demonstrates that the NRT GVF can provide a more realistic representation of vegetation state which in turn helps to improve the short-range forecasts in the arid and semiarid regions of North China.

How to cite: Lu, B., Zhong, J.-Q., Wang, W., Tang, S.-H., and Zheng, Z.-J.: Influence of Near Real-Time Green Vegetation Fraction Data on the Numerical Weather Prediction in WRF over North China, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-4551, https://doi.org/10.5194/egusphere-egu2020-4551, 2020.

Land surface temperature (LST) is an important variable that controls the energy and water exchange between the Earth’s surface and the atmosphere. It is widely used to estimate evapo-transpiration and vegetation water stress through surface energy balance models. On a large scale, LST is obtained from space-borne instruments (remote sensing) consisting of radiometers measuring the thermal radiance from the underlying surface. On the other hand, at plot scale, flux towers record longwave radiation, which can be used to estimate LST locally. The up-welling and down-welling longwave radiation measured by radiometers mounted on the eddy covariance towers can be inverted to deduce LST using the Stefan-Boltzmann law and longwave balance (Eq.1):

                                                                                                               L↑ = εσ T_s⁴+ (1− ε)L↓ (1)

where L↑ = upwelling longwave radiation (Wm⁻²), L↓ = downwelling longwave radiation (Wm⁻²), ε = surface emissivity, T_s = surface temperature (K) and σ = Stefan Boltzmann constant (Wm^-2K^-4).

Since down-welling longwave radiation was not measured routinely for a long time, the second term in Eq. 1 is commonly omitted, arguing that emissivity is close to unity and therefore Eq. 1 can be approximated by Eq. 2:

                                                                                                              L↑= εσT_s⁴ (2)

Even with the availability of down-welling longwave measurements it is very common to use Eq. 2. This gives rise to the query if the simplified equation is adequate to estimate LST from flux tower measurements. Another question associated with this method is how to obtain the correct surface emissivity (SE) values needed for LST retrievals.

The present work addresses these two important issues by using FLUXNET data for different land cover types (mulga, tropical savanna, and eucalyptus forest). SE was estimated by comparing measured sensible heat flux (H) with estimated radiometric surface-air temperature difference (ΔT) and assuming that ΔT=0 if H=0 (Holmes et al., 2009). Our FLUXNET-based estimate of LST and SE was compared with space-borne measurements (MODIS). We found that LST values obtained using Eq. 1 were more strongly correlated with MODIS (MOD11) estimates, compared to Eq. 2. However, the SE derived using Eq. 1 was much lower than the MODIS emissivities, whereas surface emissivity based on Eq. 2 was very close to the MODIS values. Generally, we found that, even at the high emissivity values taken from MODIS, the estimated LST values differed significantly (2 K or more) between the two equations for all ecosystems.

Considering that Eq. 1 physically correct equation, whereas Eq. 2 is an approximation, our analysis suggests that results based on Eq. 2 are likely biased and should be considered with caution. It further questions the implication of large scale SE at plot scale.

References:

How to cite: Thakur, G., Schymanski, S., Mallick, K., Trebs, I., and Suils, M.: Inconsistencies in the estimation of land surface temperature from longwave radiation measurements, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-4969, https://doi.org/10.5194/egusphere-egu2020-4969, 2020.

Based on the CO₂ fluxes measured with eddy covariance method from 2008 to 2012 at 47, 140 and 280m in Beijing 325m meteorological tower, we have investigated the exchange process of CO₂ flux between atmosphere and the urban surface in Beijing megacity. Because of the total vehicle control from 2011, the increasing rate of annual total CO₂ flux at 140m from 2008~2010 is 7.8% while from 2010~2012 is 2.3%. The average annual total CO₂ flux during the 5 year measurement is largest at 140m (6.41kg C m^-2 yr^-1) while at 47 (5.78 kg C m^-2 yr^-1) and 280m (3.99 kg C m^-2 yr^-1) are much smaller. The measured fluxes were highly dependent on the prevailing wind direction. The CO₂ fluxes at weekends are nearly the same as at weekdays because of the traffic restriction rule during Mon to Fri. Total vehicle numbers and population are main controlling factors of annual total CO₂ fluxes in Beijing. The CO₂ fluxes at three layers all present positive correlation with road fraction in the footprint area. The R-squares are respectively 0.69, 0.57 and 0.54 at 47, 140 and 280m. The decreasing fraction of vegetation will cause the increasing of annual total CO₂ flux and there is a exponential relationship between them. The annual total CO₂ flux is larger when the population density is higher.

How to cite: Liu, Y. and Liu, H.: Multiple level of CO2 fluxes over Beijing megacity with eddy covariance method, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-5391, https://doi.org/10.5194/egusphere-egu2020-5391, 2020.

The Planetary Boundary Layer Height (PBLH) is important for the exchange of energy, water, and momentum between the surface and the free atmosphere, making it a significant factor in studies of surface climate and atmospheric circulation. Over the Tibetan Plateau (TP) - a vast elevated heat source exerting significant influence on the Asian monsoon systems - the climate is changing rapidly. Among the many climate variables expected to change as global temperatures rise is the PBLH which, in addition to temperature profile, mechanical turbulence production, vertical velocity, and horizontal advection, is highly dependent on the surface sensible heat  fluxes. Our understanding of PBLH over the TP is very limited, although scattered estimates has indicated that it sometimes reach unusual heights – up to the vicinity of the tropopause. Long-term assessment of PBLH covering the whole TP is hampered by the fact that observations are scarce in time and space. This study takes advantage of a recently available high-resolution reanalysis (ERA5) for 1979-2018 to create a multi-decadal climatology of PBLH over the TP, and assess the seasonality, interannual variation and long-term trend of PBLH in relation to other climate variables such as tropopause height and surface sensible heat flux as well as large-scale atmospheric circulation. 

The results show that the most prominent feature of the PBLH trend is a large region of decline in the central TP during the monsoon season. Notably, this is a region where the temperature increase is smaller than in the rest of the region, and the precipitation shows a statistically significant increasing trend. Increased cloudiness may therefore have decreased the surface heating and thus the sensible heat flux and PBLH. Assessing the spatially averaged trends for the first and second halves of the period separately reveals that the monsoon season PBLH does in fact increase during the first half of the period. In the dry season in contrast, the spatially averaged PBLH decreases by almost 30 meter per decade during the first half of the period and increases slightly in the second. Although none of the spatially averaged PBLH trends are statistically significant at the 95% level, it can be noted that the shift from decreasing to increasing PBLH for the dry season is in accordance with a recent study of spring sensible heat flux over the TP. The aforementioned study found that although the sensible heat flux has been declining because of wind speed decreases, it has recently started to recover in response to an increased difference between the ground surface temperature and the air temperature. Given that the PBLH is highly dependent on the surface sensible heat flux, this decline and recovery may very well have produced the PBLH trends for the dry season. In the monsoon season, with cloudy conditions and less solar radiation reaching the ground, other factors are likely of greater importance for the PBLH.

How to cite: Slättberg, N. and Chen, D.: A long-term Climatology of Planetary Boundary Layer Height over the Tibetan Plateau revealed by ERA5, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-5517, https://doi.org/10.5194/egusphere-egu2020-5517, 2020.

In order to study the characteristics of turbulence over the homogeneous and inhomogeneous underlying surfaces and its effects on the transport of material and energy in the Source Region of the Yellow River (SRYR), northeast of the Tibetan Plateau. We use the GPS sounding data and eddy covariance data observed during a field experiment in the Ngoring Lake Basin in summer 2012, and for the first time large eddy simulations are performed to investigate the characteristics of the fine turbulence structure in the convective boundary layer (CBL) of the two different underlying surfaces (grassland and lake) in the SRYR. It shows that the simulated CBLs of grassland and lake in the SRYR is in good agreement with the observations, but the characteristics of the turbulence structure in the CBLs are obviously different. The spatio-temporal distribution of turbulence energy and the structure characteristics of thermal bubbles in the CBL above the grassland are consistent with those of the typical thermally driven CBL above the land. Convective rolls are simulated in the shear dominant CBL above the lake. Turbulence intensity in the surface layer above the grassland is higher, while it is larger at the top of CBL above the lake due to the strong entrainment. We also found that the simulations are sensitive to the horizontal resolution on the two different homogeneous underlying surfaces. The higher horizontal resolution should applied to the CBL above the lake to improve the accuracy in the simulation of turbulence kinetic energy and turbulence flux of the surface layer and the entrainment layer, while avoiding underestimating the turbulence flux due to the small range of the waves simulated at low resolution. For the CBL of the grassland, it is suggested that the grid distance should be between 200 m-300 m, which can save the calculation time, also can give the turbulence flux and the fine turbulence structure. In addition, 3-D simulations are also performed to figure out the differences of turbulence intensity over homogeneous and inhomogeneous underlying surfaces. It is found that lake breeze induced by surface inhomogeneity would enhance the wind shear, decreasing the intensity of vertical turbulence and increasing that of horizontal turbulence.

How to cite: Zhang, Y., Huang, Q., and Ma, Y.: Large eddy simulation of boundary-layer turbulence over different underlying surfaces in the Source Region of the Yellow River, northeastern Tibetan Plateau, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-6283, https://doi.org/10.5194/egusphere-egu2020-6283, 2020.

The stratification of atmospheric surface layer (ASL) plays an important role in regulating the water vapour and heat exchange across lake-air interface. Based on one-year data measured by Eddy Covariance (EC) technique over Erhai Lake in 2015, the ASL stability (ζ) was divided into six ranges, including unstable, weakly unstable, near-neutral(unstable side), near-neutral(stable side), weakly stable, and stable range. The characteristic of ASL stability conditions and factors controlling the latent (LE) and sensible (H) heat fluxes under different stability conditions were analyzed in this study. The stability conditions of Erhai Lake have noticeably seasonal and diurnal variation, which the near-neutral and (weakly)stable stratification usually occurred before July with frequency of 51.7% and 23.3%, respectively, but most of the (weakly)unstable stratification was observed since July with frequency of 59.8%. Large evaporation occurred even in stable atmospheric conditions, due to the coupled effects of relative larger lake-air vapor pressure difference and wind speed. The relative controls of LE and H by different atmospheric variables are largely dependent on the stability conditions. In stable and unstable range, LE is closely correlated with vapour pressure difference, whereas in weakly unstable to weakly stable range, LE is primarily controlled by wind speed. H is related to wind speed and lake-air temperature difference under stable conditions, but shows no obvious relationship under unstable conditions.

How to cite: Meng, X. and Liu, H.: Factors controlling the latent and sensible heat fluxes over Erhai Lake under different atmospheric surface layer stability conditions, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-6291, https://doi.org/10.5194/egusphere-egu2020-6291, 2020.

Progress in urban climate science is severely hindered by the lacuna of globally consistent and coherent information that describes aspects of the form and function of urban morphology at a detailed spatial resolution. The World Urban Database and Access Portal Tools (WUDAPT) project is proposed to solve the above problems, which has adopted the Local Climate Zone (LCZ) scheme as a basic and consistent description of form and function of cities at neighborhood scale. This study aims to develop a LCZ classification map and establish the urban morphology database for climate research and urban planning in China’s major cities. A simple workflow provided by WUDAPT project has been applied to perform this task.

The results from the quality assessments show that the LCZ maps of 63 cities in China are generally of good quality, i.e. 69–92% overall accuracy (OA). In particular, the acceptable accuracy (77-93%) is much higher when considering weights that take the morphological and climatic similarity of certain classes into account. The building height data from surveying of these cities, including of Beijing, shanghai, Changsha, Chongqing, Fuzhou, Qingdao, Lanzhou, Harbin and Lhasa，were used for testing, and a moderate accuracy (at building height) was of 51-68%. Most of buildings heights of LCZ types are in line with the surveying data, except for Compact high-rise (LCZ 1) and Open high-rise (LCZ 4), which is about 20.5±4.7 m, and has slightly lower than the LCZ standard value (>25 m). This is due to insufficient underlying input information on building height, and a general tendency to confuse these two classes with Compact mid-rise (LCZ 2) and Open mid-rise (LCZ 5).

Construction area is a very important type of underlying surface in developing countries like China. For example, in Beijing, Guangzhou and Chongqing, this type accounts for 21%, 9% and 9%, mainly distributed in suburban areas. This is an important urban underlying surface in China, but this underlying surface type has not been defined by Stewart and Oke. A follow-up study will try to define the underlying surface of construction area in LCZ classification system.

How to cite: Ma, Q., Wang, Y., and Miao, S.: Mapping Local Climate Zone in China’s Major Cities, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-6322, https://doi.org/10.5194/egusphere-egu2020-6322, 2020.

Due to manifold land-atmosphere interactions, soil moisture is an essential part of the energy-water cycle. Especially when the incoming solar radiation is high, large effects of soil moisture onto the lower atmosphere can be expected. In addition, the knowledge of large-scale soil moisture fields is important for other applications, e.g., in hydrology and agriculture. Remotely sensed soil moisture products provide information on global scales, continuously yielding better quality as well as higher spatial and temporal resolution. The ingestion into data assimilation systems propagates the obtained information in time and – via subsequent modelling – onto other physical variables.

By the assimilation of a high-resolution soil moisture product, we aim to develop a high-level soil-moisture product for Europe and to provide an improved surface initialisation for the NWP model AROME. Our focus is on fully exploiting the high spatial resolution (1 km) of the multi-layer fused soil-moisture product SCATSAR-SWI. For assimilation, we use the surface model SURFEX, which employs a simplified Extended Kalman Filter and the multi-layer diffusion scheme ISBA-DIF. We ran the assimilation system on different resolutions and found an improvement of the forecast metrics of the 2 m temperature and 2m relative humidity using higher resolution systems. In addition, we use the water balance as a reference measure for a domain-covering verification of the soil moisture analysis.

How to cite: Vural, J., Schneider, S., Bauer-Marschallinger, B., and Haslinger, K.: Assimilating the SCATSAR-SWI with SURFEX for a high-resolution European soil moisture product, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-6723, https://doi.org/10.5194/egusphere-egu2020-6723, 2020.

To improve land surface parameterizations of radiation and energy balance, eddy covariance measurements were performed on three typical land covers types over the Tibetan Plateau , including bare soil, naturally sparse alpine meadow and dense alpine grassland from 2007 to 2012. We investigated how land surface parameters changed with surface properties and vegetation canopy growth and analyzed the characteristics of diurnal and seasonal variations of aerodynamic parameters. Results show that the annual mean surface albedo and surface roughness lengths for momentum were 0.27 and 2.29 cm, 0.241 and 1.39 cm and 0.19 and 6.52 cm over bare soil, naturally sparse alpine meadow and dense alpine grassland areas, respectively. The yearly average turbulence transfer coefficients for momentum and sensible heat under neutral condition were 4.12×10^-3 and 2.29×10^-3, 4.11×10^-3 and 2.33×10^-3 and 6.67×10^-3 and 4.14×10^-3, respectively. The median values of κB^-1 averaged over multiple years are 6.65, 5.89 and 4.88, respectively.

How to cite: Ding, Z., Ma, Y., and Chen, X.: Comparative analysis of land surface parameters on three typical underlying surfaces over the Tibetan Plateau, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-6783, https://doi.org/10.5194/egusphere-egu2020-6783, 2020.

Eddy covariance data from Xilinhaote National Climatological Observatory in Xilin Gol League during growing seasons of 2010—2013 as well as MODIS data were used to validate an ecosystem respiration model based on enhanced vegetation index (EVI), land surface water index (LSWI) and land surface temperature (LST) in a semi-arid grassland of Inner Mongolia. The limitations of this remote sensing respiration model were also discussed. The results indicate that this model can successfully simulate the variations of nocturnal ecosystem respiration (Reco) in the growing seasons and between different years. The simulated nocturnal Reco also agreed remarkably with the observed Reco (R2=0.90, RMSE=0.02 mgCO2/(m2·s)). Moreover, the observed nocturnal Reco showed a good linear correlation with EVIs×Ws (R2=0.63), in which EVIs and Ws are response functions of EVI and LSWI on photosynthesis, respectively. The response of nocturnal Reco to LST was also found following the L-T equation (R2=0.39). In addition, the difference between responses of nocturnal Reco to EVIs×Ws and LST in the early, middle and late stages of the growing season is indicated as one principal source of the deviations of model results.

How to cite: Jiang, H., Ye, H., and Hao, Y.: A Study of MODIS-Based Ecosystem Respiration Model in a Semi-Arid Grassland of Inner Mongolia, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-7085, https://doi.org/10.5194/egusphere-egu2020-7085, 2020.

The glacier ratio influences both the contribution of meltwater runoff and the response of the basin's hydrological processes to climate change. In this study, the Karuxung, the Tuotuo and the Babao river basins with glaciers accounting for 20.7%, 2.1% and 0.38% respectively, were selected to study their hydrological processes under the climate change. Based on the daily runoff data of 30 years and MODIS snow cover products, the J2000 model was applied to quantify the contribution of meltwater and rainfall runoff, analyze the temporal and spatial variation characteristics of runoff and clarify the influence of climate change on these three basin. The main findings are as follows: (1) The contribution of glacier and snow melt runoff for the Karuxung, Tuotuo and Babao river basin was 60.7%, 25.3% and 19.9%, respectively. The contribution of rainfall runoff for the three basins was 39.3%, 74.7% and 81.1%, respectively. (2) The peak of glacier and snow melt runoff converted from summer to spring with the glacier ratio decreasing. (3) The runoff supplies in the Karuxung, Tuotuo and Babao river basin were from the 5500m-6500m, 4500m-5500m zone, and 3500m-4500m elevation zone, respectively. (4) The runoff and its components in the Karuxung and Tuotuo river basins showed significant increasing trends while the Babao river basin showed no significant change trends. (5) In the Karuxung river basin with large glacier ratio, the increase in temperature mainly caused the increase of meltwater and runoff, showing a positive impact on runoff. For the Tuotuo and Babao river basin with small glacier ratios, the increase in temperature mainly caused increased evaporation and reduced runoff, showing a negative impact on runoff.

How to cite: Wang, L. and Zhang, F.: Response of Hydrological Process to Climate Change of Basins with Different Glacier Ratio in the Tibet Plateau, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-7867, https://doi.org/10.5194/egusphere-egu2020-7867, 2020.

The effects of soil seasonal freezing and thawing process on land surface heat fluxes were analyzed with two years observation data from 2013 to 2014 . The results showed that the sensible heat, latent heat and soil heat flux have no change significantly during the soil freezing stage. The sensible heat flux increased significantly, the latent heat flux decreased significantly, and the corresponding wave ratio increased during the frozen period. The soil moisture and soil heat flux increases rapidly, sensible heat flux and surface long wave radiation decrease rapidly, latent heat flux increases rapidly during the thawing stage. The thawing process of frozen soil has an obvious effect on the heat flux of soil, which increases the heat flux from surface soil to deep soil because of that the heat absorption of ice in thawing process.

How to cite: li, Z.: Study on the influence of seasonal frozen thawing process on the surface flux in the Loess Plateau, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-8643, https://doi.org/10.5194/egusphere-egu2020-8643, 2020.

A teleconnection pattern over the Eurasian continent in early spring and its impact on Bay of Bangle Monsoon onset, is investigated on the basis of reanalysis datasets and numerical test. It is revealed that this pattern shows Rossby wave activities that excited by the forcing feedback of the transient eddies over the exit region of the North Atlantic jet. The anomalous centers can manifest themselves as Rossby wave dividing into two branches and propagating towards Lake Baikal and south flank of the Tibetan Plateau. Meanwhile, asymmetric atmospheric response to vorticity forcing is characterized by weaker amplitude during positive phase than negative phase, which is caused by weaker positive vorticity forcing. Moreover, the anomalous cold cyclone locates on the Tibetan Plateau can bring more snowfall and correspond to anomalously wet soil condition, thereby decreasing surface heat flux and near-surface temperatures, leading to an anomalous cold cyclone can be maintained until April. Therefore, it can postpone Bay of Bangle Monsoon onset. Subsequently, the interannual variations of stationary wave can give a better explanation for late Monsoon onset under neutral ENSO condition. The simulated response to vorticity forcing also can reproduce the pattern of this stationary wave in Linear Baroclinic Model (LBM).

How to cite: Yang, Y., Liu, Y., Wu, G., Xie, Y., and Li, J.: A Teleconnection Pattern over Eurasian Continent in early Spring and its Impact on Bay of Bangle Monsoon Onset, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-8951, https://doi.org/10.5194/egusphere-egu2020-8951, 2020.

The Sichuan Basin is located in the eastern part of the Tibetan Plateau, and there is a rapidly developing urban agglomeration over there. Therefore, heavy air pollution events have frequently occurred over many cities in recent decades. In this study, We explored the effects of weather systems on winter heavy air pollution from more than 10 cases of heavy air pollution events occurred during 2006-2018. Most of them were affected by a dry low-pressure system at 700 hPa, at the same time , they were also influenced by the inversion with several layers in the lower atmosphere. It is interesting that the synergistic effects of synoptic patterns and inversions caused by topography on heavy air pollution events. When the urban agglomeration was in front of the low-pressure system and the weather conditions were controlled by a warm southerly air flow, a strong temperature inversion appeared above the atmospheric boundary layer acting as a lid. The local secondary circulation was forced by both of them and was confined within the atmospheric boundary layer. At that time, the horizontal wind speed in the lower atmosphere was low.  As a result, vertical mixing and horizontal dispersion in the atmosphere were poor, a heavy air pollution event was gradually caused. After the low-pressure system had passed over the urban agglomeration, the weather conditions over there were controlled by a dry and cold air flow from the northwest at 700 hPa, foregoing strong inversion layer gradually dissipated, the secondary circulation enhanced and uplifted, and the horizontal wind speed in the lower atmosphere also increased, resulting in a sharp decrease in the concentration of air pollutants. In sum, the strong inversion layers above the lower atmosphere were induced by the low-pressure systems at 700 hPa, both happened a synergistic effect and played a key role in the formation of heavy air pollution during the winter months in this urban agglomeration of The Sichuan Basin. Finally, it was presented that a new conceptual model is about meteorological causes of winter heavy air pollution  in the Sichuan Basin.

How to cite: Wang, S. and Fu, H.: Influence of the synoptic systems and inversion characteristics on winter heavy air pollution in the lower atmosphere over Sichuan Basin, China, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-9486, https://doi.org/10.5194/egusphere-egu2020-9486, 2020.

Stream water age is an essential indicator of stream water renewal and pollutant transport rates in the Qinghai-Tibet Plateau (QTP). Recently, the concept of a young water fraction (F_yw , calculated using stable isotopic data, was proposed as a measure of stream water age. The relative age of older stream in streams has yet to be quantified, however. In this study, we proposed a method to calculate the relative proportions of middle-aged and old-age water in runoff. The results revealed that in the Nagqu watershed, an average of 23% of the runoff was < 51.6 days old, whereas an average of 55% of the runoff had ages ranging from 51.6 days to 1. The change in stream water age is significantly influenced by the runoff composition, evaporation, air temperature, and soil moisture at a depth of 20 cm. The amount of stored glacial ice, soil ice, snow cover, groundwater, and other old water in the QTP appears to be decreasing under the influence of climate change. The results of this study are helpful for the study of runoff composition and stream water age, as well as their responses to climate change.

How to cite: Yang, Y. and Weng, B.: Using Stable Isotopes to Estimate Stream Water Age in the Qinghai-Tibet Plateau, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-12708, https://doi.org/10.5194/egusphere-egu2020-12708, 2020.

Lake surface temperature is a key parameter in understanding the variability of lake thermal condition and evaporation. MODIS-derived LST is widely used as a reference for lake-model validations and process studies in data-scarce regions. In this study, the accuracy and limitation of MODIS LST were examined on the Tibetan Plateau, where there are thousands of lakes. It is found that agreement between MODIS LST and in-situ subsurface (~1 m depth) temperature collected at six large lakes depends on the thermal phases. During lake turnover period (nighttime or from October to freeze-up date), the sink of surface water causes mixed with subsurface water. The MODIS LST was consistent with the in-situ data, indicating its high accuracy. During stratification period (from May to September), the lakes were thermally stratified due to intense solar heating and high salinity in some lakes; the daytime MODIS LST is systematically higher than the in-situ subsurface temperature, indicating it is credible. However, the MODIS LST has two limitations in this region. First, nighttime retrievals during monsoon season have considerable cold biases in monsoon-controlled region. This can be associated with shallow clouds or fog near the lake surface that occur frequently at night but are not well detected by MODIS. Second, the retrievals for narrow and small lakes have warm (cold) biases in the daytime (at night), perhaps due to proximity effect of mountains and land. The two situations are common across the Tibetan Plateau and thus severely restrict the applications of MODIS LST in lake studies.

How to cite: La, Z., Yang, K., Qin, J., Hou, J., Lei, Y., Wang, J., Huang, A., Chen, Y., Ding, B., and Li, X.: Applicability of MODIS lake surface temperature depends on season and lake size on the Tibetan Plateau, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-13134, https://doi.org/10.5194/egusphere-egu2020-13134, 2020.

Recently, there are many problems in urban area such as urban thermal island phenomenon, changes in urban green area, changes in urban weather and various urban types. And surface temperature data have been utilized in many areas to identify these phenomena. This means that surface temperatures is an important position in urban greenery and weather. High temporal and spatial resolution satellite data are needed to continuously observe the phenomenon in urban areas. In addition, the surface temperature varies from type of indicator, topography, and various factors, so there is a limit to the in-situ data for observing changes throughout the city. Therefore, various organizations around the world are currently conducting surface temperature measurements using satellites. However, the use of data in clear pixel is essential for accurate surface temperature calculations using satellites, but the accuracy of results will be reduced if the data from in the pixel which conclude clouds.

Therefore, we tried to solve these problems by analyzing the correlation between the air temperature data and the Landsat-8 LST data. The variables used in the correlation analysis are air temperature, Landsat-8 LST, NDVI and NDWI, and the study period is 2014 to 2016 and the study area is South Korea's five cities (Seoul, Busan, Daejeon, Daegu, Gwangju). For correlation analysis, the air temperature data points provided by the Korea Meteorological Administration and the Landsat-8 pixels were matched, and the correlation coefficient calculated by the correlation analysis was applied to the Landsat-8 satellite to calculate the LST. We validated by direct comparison the re-produced Landsat-8 LST with observed Landsat-8 LST. And the result of validation showed a high correlation of 0.9. It shows that compensation for the satellite's shortcomings from clouds by using the correlation between temperature and LST.

How to cite: Choi, S., Jin, D., Seong, N., Jung, D., and Han, K.: Correlation of air temperature and land surface temperature of Landsat-8 in cities of South Korea, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-13886, https://doi.org/10.5194/egusphere-egu2020-13886, 2020.

Surface broadband albedo is one of the climate variables that understand Earth’s radiation budget. Currently, the polar-orbit satellite-derived surface broadband albedo products are retrieved by several organizations. As there are many kinds, it is necessary to identify the characteristics of each products. In this study, we were to compare representative products for long-term that the albedo products based on polar-obit satellite such as moderate resolution imaging spectroradiometer (MODIS) and the Copernicus Global Land Service (CGLS). We studied the Northeast Asia region where the land type remains unchanged from 2000 to 2018. The overall trend of the two products was similar. However, differences occurred depending on the land types and season. The relatively high value of MODIS albedo was calculated in winter because it was sensitive to the snow. In other seasons, the CGLS albedo was higher than the MODIS albedo. The MODIS albedo was calculated higher than CGLS albedo for all land types except forest. The comparison results showed that caution should be given before operational use of the albedo data sets in these regions.

How to cite: Seong, N.-H., Choi, S., Jin, D., Jung, D., and Han, K.: Intercomparison of Surface broadband Albedo products from MODIS, CGLS over Northeast Asia, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-14114, https://doi.org/10.5194/egusphere-egu2020-14114, 2020.

Turbulent flux data observed in surface layer during growing seasons at Xilinhaote National Climatic Observatory and Jinzhou Agroecosystem Observatory and remote sensing data were analyzed to acquire main environmental factors and biological factors which drive the ecosystem respiration (R_eco). Then the key driven factors of R_eco were selected to optimize a semi-empirical ecosystem respiration model. Based on the new ecosystem respiration model, respiration part of Vegetation Photosynthesis and Respiration Model (VPRM) was optimized and its simulation effect of net ecosystem exchange (NEE) was validated in a semi-arid grassland ecosystem and a maize cropland ecosystem.

Compared to the linear temperature model, the nocturnal R_eco simulated by the new ecosystem respiration model agreed remarkably better with the observed R_eco (at Xilinhaote site, R² increased from 0.08 to 0.61 in 2010-2012; at Jinzhou site, R² increased from 0.13 to 0.55 in 2010). And the new ecosystem respiration model showed similar performance in predicting nocturnal R_eco (at Xilinhaote site, R² increased from 0.32 to 0.57 in 2013; at Jinzhou site, R² increased from 0.33 to 0.61 in 2011).

This study also indicates that optimization of the respiration part of VPRM can improve the simulation effect of NEE during nighttime of the growing seasons in a semi-arid grassland ecosystem and a maize cropland ecosystem, R² between the modeled NEE and the observed NEE increased from 0.30 to 0.57 in the semi-arid grassland ecosystem and increased from 0.03 to 0.48 in the maize cropland ecosystem. However, in the whole time of the growing seasons, little difference was found between the modelled NEE by the original VPRM model and that by our modified VPRM model, probably for the reason that daytime NEE is mainly dominated by vegetation photosynthesis.

How to cite: Hao, Y., Jiang, H., and Ye, H.: A MODIS-based ecosystem respiration model and its application in optimizing vegetation photosynthesis and respiration model: A case study of two terrestrial ecosystems in Northern China, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-14323, https://doi.org/10.5194/egusphere-egu2020-14323, 2020.

As one of the most important parameters in earth surface, soil moisture plays a crucial role in in many fields, such as agriculture, environment, hydrology, ecology and water management. With the development of earth observation technology, Synthetic Aperture Radar (SAR) provides a powerful method to estimate soil moisture at diverse spatial and temporal scales. However, in agricultural area, soil moisture estimated by SAR often obstructed by vegetation cover. Volume scattering and vegetation attenuation can complex the received SAR backscatter signal when microwave interacts with vegetation canopy. In this study, a model-based polarimetric decomposition and the two-way attenuation parameter in Water Cloud Model (WCM) were adopted to remove the effect of volume scattering and vegetation attenuation respectively. And a deorientation process of SAR data was applied to remove the influence of randomly distributed target angles before polarimetric decomposition. After that, the Dubois model was used to describe the underlying soil backscattering and retrieve soil moisture. Optimal surface roughness was adopted to parameterize the Dubois model due to the difficulty of soil roughness measurement under vegetation cover. This soil moisture estimation method was applied to soybean fields with time-series RADARSAT-2 SAR data. Validation based on in-situ measured soil moisture demonstrates that the proposed method is capable of estimating soil moisture over soybean fields, with Root Mean Square Errors (RMSEs) of 9.2 vol.% and 8.2 vol.% at HH and VV polarization respectively.

How to cite: Xiao, T., Xing, M., and He, B.: Soil Moisture Estimation over Soybean Fields Through A Model-Based Polarimetric Decomposition, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-16532, https://doi.org/10.5194/egusphere-egu2020-16532, 2020.

Geostationary remote sensing satellite can provide time-series mid-infrared (MIR) data at regional scale, which plays a significant role in many applications such as environmental monitoring, fire detection and temporal change of surface parameters. Therefore more geostationary remote sensing satellite missions for earth observation are carried out and focused on directional and high-temporal resolution. Given the complex nature of the data to be expected from these missions, it is essential for a thorough preparation, which can be accomplished by simulating the image data before the actual launch. The simulation can include the top-of-atmosphere (TOA) radiance data as well as all major process parameters such as land surface temperature/emissivity and atmospheric parameters. It can be used to evaluate the capabilities of target satellite observing the earth and optimize the system according to the further analysis. In addition, the development of the data simulation will provide a considerable support for the algorithms of quantitative application.

This work addressed a method for simulating the time-series mid-infrared data of geostationary satellite based on radiative transfer model. The simulation procedure, including directional emissivity, time-series LST, time-series atmospheric parameter, sensor performance, can be shown as follows. Firstly, an empirical Bidirectional Reflectance Distribution Function (BRDF) model, i.e., the Minnaert’s model, is introduced to describe the non-Lambertian reflective behavior of land surface. Then, the directional emissivity can be calculated based on the Kirchhoff’s law with the John Hopkins University (JHU) Spectral Library as the prior knowledge. Secondly, a semi-empirical Diurnal Temperature Cycle (DTC) model with six parameters (Göttsche, F. M., and Olesen, F. S., 2001) is used to simulate the time-series LST with the interval of 15min. Thirdly, the atmospheric profiles of pressure, temperature, relative humidity (RH), and geo-potential (GP) at 0.5° latitude/longitude spatial resolutions for 8 UTC times per day provided by European Centre for Medium-Range Weather Forecasts (ECMWF) are used for atmospheric parameters. A temporal interpolation method is proposed to obtain the time-series atmospheric parameters from the ECMWF 3-hour profile. Then, the MIR spectral radiance at the top of atmosphere can be simulated by MIR radiative transfer equation with the aid of MODTRAN 5 code. Finally, by convoluting the sensor’s spectral response function, the radiance received by the sensor can be got against the instrument noise. The results show that the time-series mid-infrared data for geostationary satellite of different surface types at any angle can be well simulated using the proposed method. More comparative analysis with the geostationary satellites, such as METEOSAT, GEOS, FENGYUN, GMS etc., will be done in the future work.

How to cite: Li, K., Qian, Y., Wang, N., Ma, L., Qiu, S., Li, C., and Tang, L.: The Time-series Mid-Infrared Data Simulation for High-temporal Resolution Geostationary Satellite, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-18717, https://doi.org/10.5194/egusphere-egu2020-18717, 2020.

Earth Observation (EO) when used synergistically with simulation process models provides a promising direction towards estimating key parameters characterising land surface interactions (LSIs). Some of the most commonly used techniques for this purpose are based on the physical relationships encapsulated in the feature space established when a satellite-derived land surface temperature (Ts) is plotted against a spectral vegetation index (VI).

The objective of this study has been two-fold: first to explore the effectiveness of one such Ts/VI technique, commonly called the “triangle” method, to retrieve soil moisture and evapotranspiration rates, when integrated with ESA’s Sentinel-3 satellite data. Secondly, to appreciate the ability of this technique to retrieve new biophysical parameters characterising LSIs, namely the Evaporative (EF) and Non-Evaporative (NEF) fractions, CO₂ & O₃ fluxes and Water Use Efficiency (WUE).

Predicted parameters were compared against co-orbital ground measurements acquired from several European sites belonging to the CarboEurope ground observational network. The main preliminary findings of the study are presented and the main challenges that still impede their accurate spatio-temporal estimation by the TS/VI domain are also highlighted.

To our knowledge, this study represents the first comprehensive exploration of the performance of this particular methodological implementation using Sentinel-3 EO and is the first investigation into the effect of extending this particular method to retrieve spatiotemporal estimates of other key LSI parameters from the TS/VI domain. As such, this study is of considerable value in regards to the future use of this inversion modelling scheme, opening up potentially new opportunities in future implementations of it in many practical applications and research investigation alike.

In the present work Dr Petropoulos participation has received funding from the European Union’s Horizon 2020 research and innovation programme ENViSIoN under the Marie Skłodowska-Curie grant agreement No 752094.

KEYWORDS: land surface interactions, Sentinel 3, Ts/VI domain, triangle, CarboEurope

How to cite: Petropoulos, G. P., Hristopulos, D., and Sandric, I.: Retrievals of Parameters Characterising Land Surface Interactions from the satellite-derived Ts/VI Feature Space, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-18760, https://doi.org/10.5194/egusphere-egu2020-18760, 2020.

Nitrogen is essential for the synthesis of key cellular compounds such as proteins and nucleic acids in all organisms, and it is one of the limiting elements in most terrestrial ecosystems. During past decades, terrestrial ecosystems nutrients availability have altered with nitrogen deposition increases rapidly so that under the soil microbial metabolism activities terrestrial ecosystem biogeochemical cycles are strongly affected. Therefore, maintaining the stability of soil carbon pools, especially microbial carbon pools has great importance for studying global carbon cycle and global climate change processes. Depending on whether soil microbial has already adapted to the environment nitrogen concentration, there exists different results, such as promotion, inhibition, and no impact. To date, how nitrogen will affect soil microbial respiration still has controversy. To determine the effects, we performed a 59 weeks incubation with the soil which has already treated with Urea for 9 years. The soil has been treated with four N addition levels in a semi-arid grassland where located in North-west part of China. We measured CO₂ effluxion under different treatments within the same temperature. Our results showed that during the first 8 weeks, soil microbial had strong responses about N addition and N9.2 showed greatest influence with soil microbial respiration. With the time passing, in the time of 9-59 weeks, N0 had highest soil microbial respiration rate while N2.3 was the lowest, this illustrated N2.3 had highest N use efficient (NUE), in order to meet soil microbial stoichiometry, microbial growth became strong C-limitation under the N2.3 treatment. What’s more, comparing with other studies which we shared same study area, we also found that the time of nitrogen application also had strong effect on soil microbial respiration. These results highlight the importance of microbial respiration and may also help us to have a better understand about how N deposition controls terrestrial C flows.

How to cite: Wang, Z., Liu, Z., Guo, B., Qi, Z., Niu, D., and Fu, H.: Soil microbial respiration responses of nitrogen addition: Evidence from a long-time semi-arid grassland soil incubation, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-20823, https://doi.org/10.5194/egusphere-egu2020-20823, 2020.

The acquisition of image data from satellite is performed by the satellite’s sensor after the light from the sun is reflected in object at the surface. In this process, light passes through the earth's atmosphere twice and is affected by the scattering, absorption and reflection by the atmosphere. This effect of the atmosphere reduces the power of the sun's light entering the sensor and consequently influences image data. The process of removing this effect is called atmospheric correction. Generally, the radiative transfer model (RTM) such as the Second Simulation of a Satellite Signal in the Solar Spectrum (6S) is used in the atmospheric correction methods for surface reflectance retrieval. In general, RTM have high accuracy. But, RTM processing takes long time to perform atmospheric correction. So, several studies have applied the Look-up Table (LUT) method based on RTM. However, LUT is not an exact method due to the increment and range of input variables. In this study, we used the Deep Neural Network (DNN) method to predict surface reflectance for KOMPSAT-3A data. To Build an effective DNN model, 6S-based LUT is used as training data and the hyper-parameters have been adjusted. To evaluate the surface reflectance retrieval, we compared the surface reflectance derived of 6S RTM, 6S-based LUT and DNN methods.

How to cite: Jung, D., Jin, D., Choi, S., Seong, N., and Han, K.: Estimation of surface reflectance using deep neural network with KOMPSAT-3A data, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-20972, https://doi.org/10.5194/egusphere-egu2020-20972, 2020.

According to the shortcomings of the land surface model, the new scheme is developed and applied to the simulating soil process at Madoi and Nagqu. Simulations show that gravel tend to reduce soil water holding capacity and enhance soil hydraulic conductivity, surface infiltration and drainage. As a result, the upper layer of soil mixed with gravel tends to drier due to the soil water move to deeper layer. The mean biases of soil moisture between the simulation and observation reduced by 25- 48% at two sites. Soil thermal conductivity is increased with gravel content and the soil thermal inertia was decreased with gravel content increasing. Therefore the deeper layer temperature of soil containing gravel is rapid response to air temperature change. The mean biases of soil temperature between the simulation and observation reduced by 9.1-25% at two sites. From the simulation results at Madoi and Nagqu, we find that the new scheme performed better than the original scheme in simulating soil temperature and water content and the land model implemented the new scheme is suitable for simulating land process in the QTP.

How to cite: lyu, S.: Effects of Gravel on Energy and Water Transport in the Soil of Qinghai-Tibet Plateau, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-20983, https://doi.org/10.5194/egusphere-egu2020-20983, 2020.

Accurate estimation of surface evapotranspiration (ET) with high quality and fine spatiotemporal resolution is one of the biggest obstacles for routine applications of remote sensing in eco-hydrological studies and water resource management at basin scale. Integrating multi-source remote sensing data is one of the main ideas for many scholars to obtain synthesized frequent high spatial resolution surface ET. This study was based on the theoretically robust surface energy balance system (SEBS) model, which the model mechanism needs further investigation, including the applicability and the influencing factors, such as local environment, heterogeneity of the landscape, and optimized parametric scheme, for improving estimation accuracy. In addition, due to technical and budget limitations, so far, no single sensor provides both high spatial resolution and high temporal resolution. Optical remote sensing data is missing due to frequent cloud contamination and other poor atmospheric conditions. The passive microwave (PW) remote sensing has a better ability in overcoming the influences of clouds and rainy. The accurate "all-weather" ET estimation method had been proposed through blending multi-source remote sensing data acquired by optical, thermal infrared (TIR) and PW remote sensors on board polar satellite platforms. The estimation had been carried out for daily ET of the River Source Region in Southwest China, and then the "All-weather" remotely sensed ET results showed that the daily ET estimates had a mean absolute percent error (MAPE) of 36% and a root mean square error (RMSE) of 0.88 mm/day relative to ground measurements from 12 eddy covariance (EC) sites in the study area. The validation results indicated good accuracy using multi-source remote sensing data in cloudy and mountainous regions.

How to cite: Ma, Y., Zhou, J., and Liu, S.: Monitoring of "All-weather" Evapotranspiration Using Multi-source Remote Sensing Imagery in Cloudy and Mountainous Regions in Southwest China, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-20997, https://doi.org/10.5194/egusphere-egu2020-20997, 2020.

Land surface temperature (LST) is an essential indicator of forest growth conditions, drought and fire. However, retrieved LSTs from satellite-based thermal infrared (TIR) observations prone to directional anisotropies, and a pixel-averaging temperature, that is usually aggregated by different components such as overstory canopy, tree trunk, understory vegetation and bottom soil, cannot directly reflect the temperature distribution inside a forest. Currently, existing analytical thermal radiative transfer models (RTM) can hardly fill this gap due to complicated structural and thermal variations in a forest stand. In this paper, a famous visible and near-infrared (VNIR) RTM, FRT, was introduced to the TIR domain, in which a themral emission term of components was added. Moreover, the effect of vertical heterogeneity of leaves’ temperatures on top-of-canopy (TOC) brightness temperatures (BTs) was also considered. Based on a simulated dataset, the effect of the tree trunk and understory vegetation on TOC BTs was found significant, and the temperature profile of leaves can increase the directional anisotropy of TOC BTs. An inter-comparison with a three-dimensional radiosity model indicated a stable performance of the modified thermal FRT model. The thermal FRT model was also validated using a measured dataset from an airborne sensor, and the evaluation result revealed a satisfactory performance with root mean squared error and coefficient of determination of 0.55°C and 0.74 in the solar principal plane (SPP), respectively, and the corresponding values were 0.21°C and 0.90 in cross-SPP. The thermal FRT model has capable of acting as not only a tool to link satellite TIR observations and component temperatures for a further sub-pixel inversion and an angular normalization study of LSTs, but also a supplement for combined applications using both VNIR and TIR remotely sensed observations.

How to cite: Bian, Z., Cao, B., Li, H., Du, Y., Xiao, Q., and Liu, Q.: Modeling directional anisotropies of forest emissions using a thermal FRT model, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-21009, https://doi.org/10.5194/egusphere-egu2020-21009, 2020.

Snow cover mapping is a form of precipitation that detects snow-covered pixels by observing snow accumulated on the ground. Snow is the largest single component of the cryosphere and has high reflectance compared to other index, so it plays an important role in maintaining heat balance between the Earth’s surface and the atmosphere, or in maintaining the balance of the Earth’s energy balance in terms of global or regional aspects. In case of snow cover mapping using satellite data, a wide range of data can be easily obtained and time series observations can be made periodically for the same area. Although the characteristics of snow appear in satellite data show differences in reflectance compared to snow-free, the reflectance change pattern depending on wavelength also has a unique pattern. We focused to the unique reflectance change pattern according to the wavelength of the snow, and used the Dynamic Wavelength Warping (DWW) method to perform the snow cover mapping using the unique pattern. The DWW is a method that determines the similarity of change patterns by using reflectance change pattern according to wavelength. in this study, daily composite snow cover mapping was calculated using snow cover data calculated using DWW method. In order to evaluate the accuracy of the synthetic snow cover data calculated from this study, we used the Global Multisensor Automated Snow/Ice Map (GMASI) data from the National Oceanic and Atmospheric Administration (NOAA) and conducted quantitative and qualitative evaluations. As a result, Probability of Detection (POD) was 97.14 % and False Alarm Ratio (FAR) was 1.96 %.

How to cite: Jin, D., Choi, S., Seong, N.-H., Jeong, D., and Han, K.-S.: Daily snow cover mapping based on Dynamic Wavelength Warping using geostationary satellite data, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-21136, https://doi.org/10.5194/egusphere-egu2020-21136, 2020.

Effective modeling of surface water and energy balance is crucial in planning and management of regional resources. However, the heterogeneous and clumped vegetation structure controls the portioning of land surface water and energy fluxes, which leads to large variations of local radiative and hydrological processes. The aim of this study is to characterize the land surface heterogeneity in East Africa and examine the impact of the spatially and temporally varying vegetation parameters on energy and water balance in the region.  We used MODIS datasets on Leaf Area Index (LAI), Enhanced Vegetation Index (EVI) and albedo to derive time-varying vegetation parameters for the period 2001 – 2011 period at 0.05° resolution. These parameters were integrated with the Variable Infiltration Capacity (VIC) model to characterize the effects of varying vegetation properties on surface water and energy fluxes. A twin simulation was also carried based on seasonally averaged vegetation parameters to isolate the effects of time-varying and spatially heterogeneous parameters on the water and energy fluxes. The simulation results were compared to rigorously validated global datasets on evapotranspiration and sensible heat. Results showed that the time-varying and spatially heterogeneous vegetation parameters provided surface water and energy fluxes which were more consistent with the validation datasets. The simulated evapotranspiration matched reasonably well with the observed values particularly in areas characterized by sparse vegetation and which are more prone to human influence. The improvements were highly noticeable in grassland and savanna land cover types. However, due to intensive human activities in region which affect not only the lad cover but also the vegetation structure, there is need for characterization of the land cover parameters based on high resolution data which can better capture the land surface heterogeneity in the region.

How to cite: Patil, S., Musau, J., and Marshall, M.: Modelling Regional Water and Energy balance in East Africa, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-21940, https://doi.org/10.5194/egusphere-egu2020-21940, 2020.

The exchange of heat and water vapor between land surface and atmosphere over the Third Pole region (Tibetan Plateau and nearby surrounding region) plays an important role in Asian monsoon, westerlies and the northern hemisphere weather and climate systems. Supported by various agencies in the People’s Republic of China, a Third Pole Environment (TPE) observation and research Platform (TPEORP) is now implementing over the Third Pole region. The background of the establishment of the TPEORP, the establishing and monitoring plan of long-term scale (5-10 years) of it will be shown firstly. Then the preliminary observational analysis results, such as the characteristics of land surface energy fluxes partitioning and the turbulent characteristics will also been shown in this study. Then, the parameterization methodology based on satellite data and the atmospheric boundary layer (ABL) observations has been proposed and tested for deriving regional distribution of net radiation flux, soil heat flux, sensible heat flux and latent heat flux (evapotranspiration (ET)) and their variation trends over the heterogeneous landscape of the Tibetan Plateau (TP) area. To validate the proposed methodology, the ground measured net radiation flux, soil heat flux, sensible heat flux and latent heat flux of the TPEORP are compared to the derived values. The results showed that the derived land surface heat fluxes over the study areas are in good accordance with the land surface status. These parameters show a wide range due to the strong contrast of surface feature. And the estimated land surface heat fluxes are in good agreement with ground measurements, and all the absolute percent difference in less than 10% in the validation sites. The sensible heat flux has increased slightly and the latent heat flux has decreased from 2001 to 2016 over the TP. It is therefore conclude that the proposed methodology is successful for the retrieval of land surface heat fluxes and ET over heterogeneous landscape of the TP area. Further improvement of the methodology and its applying field over the whole Third Pole region and Pan-Third Pole region were also discussed.

How to cite: Ma, Y.: The progress on the observation and modeling of surface heat fluxes and evapotranspiration over heterogeneous landscapes of the Third Pole region, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-1687, https://doi.org/10.5194/egusphere-egu2020-1687, 2020.

The energy non-closure near the land surface has been a key topic in the land surface processes research.  The energy closure rate is still not high even after considering heat storage and photosynthesis energy consumption, while the contribution of advective energy to the closure rate needs to be considered further under the non-uniform underlying surface. In this paper, the advective energy caused by thermal heterogeneity of underlying surface is calculated by using the energy budget data collected from the Flower-Lake observation site in the Zoige Alpine Wetland in 2017, and the contribution of thermal advection to energy closure near the ground is estimated. The result shows: In summer of 2017, the maximum value of the advective heat flux was 23.8w/m2 at the Zoige alpine wetland. When the contribution of advective heat flux is introduced into the energy balance equation, the energy closure rate increases from 72.0% to 79.4%. With considering the contribution of horizontal heat transfer, it has a certain effect on improving energy closure rate for the flat terrain and thermal inhomogeneous underlying surface. The near surface thermal inhomogeneity leads to the accumulation of heat, which is the basic reason for the heat advection to affect the energy closure rate, and also an important reason for the difference between the wetland characteristics of water and heat exchange of the wetland with the other regions.

Key words：Alpine wetland; eddy correlation; advective heat flux; energy closure rate; inhomogeneous land surface

How to cite: Wen, J., Lu, X., Yang, Y., Tian, H., Liu, W., Wu, Y., and Jiang, Y.: A Study on Contribution of the Advective Heat Flux to the Energy Closure near the Land Surface in the Zoige Alpine Wetland, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-3028, https://doi.org/10.5194/egusphere-egu2020-3028, 2020.

Over the past several decades, global climate change, particularly the rising temperature has caused public concerns. In the context of climate warming, many environmental and water problems such as decreasing runoff, shrinking glaciers and permafrost, vegetation degradation and desertification can be attributed to rapid climate change. Surface air temperature (SAT) plays a key role in land-atmospheric interactions and is an important parameter for climate change studies. Traditional SAT data are collected by ground meteorological observation. Nevertheless, such traditional measurements at ground stations cannot capture the spatial variations of SAT, especially over complicated areas such as the Tibetan Plateau, where meteorological stations are with large elevation variability and unreasonable spatial distribution. In contrast, satellite remote sensing provides an direct observation of land surface temperature (LST) and, thus, also provides an possible way to obtain SAT since LST and SAT are generally closely related to each other. The scientific communities have developed various methods to estimate SAT from LST through statistical or physical models. The widely used satellite LST, however, is derived from satellite thermal infrared remote sensing and thus, significantly affected by the clouds.

In this study, we report an examination of the estimation of daily 1-km SAT from the all-weather satellite LST over the Tibetan Plateau. The estimation of SAT is based on a noval method that dynamicall integrates the newly published 1-km all-weather LST data by merging satellite thermal infrared and microwave remote sensing observations based on the random forest. The matchups of the ground measured SAT at stations and the corresponding all-weather LST were separated into the training set and valiation set. In addition, independent SAT measured at experimental ground sites were used to evaluate the SAT method. Results indicate that reasonably integrating multiple LST terms provides daily average all-weather SAT with satisfactory accuracies over the Tibetan Plateau. The estimated SAT based on the proposed method has ignorable systematic error and low root-mean squared error when validated with ground measured SAT under all-weather conditions. Further comparison demonstrates that the SAT estimate agree well with other SAT estimated from satellite thermal infrared LST under cloud-free condition. In addition, the SAT method has the potential to be generalized and extended to various complicated areas. With this method, the daily 1-km SAT for the entire Tibetan Plateau from 2003 to 2018 were produced. This dataset is of great value to examine recent climate warming trend and the land-atmospheirc interactions in the entire Tibetan Plateau.

How to cite: Wen, X., Zhou, J., Zhang, X., and Ma, J.: Estimating daily 1-km surface air temperature from satellite all-weather land surface temperature over the Tibetan Plateau, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-3274, https://doi.org/10.5194/egusphere-egu2020-3274, 2020.