Displays

Agricultural climate impact projections routinely rely upon temperature-based statistical models to characterize historical variability and project future crop yields, and exposure to extremely hot temperatures is associated with severe crop losses. However, high temperatures over land can be strongly influenced by land surface conditions, including shifts in evapotranspiration arising from variations in vegetation productivity and soil moisture. This talk will highlight the ways in which such land-atmosphere interactions should be considered in agricultural climate impact assessments. I will show how crop intensification of both rainfed and irrigated production modified extreme temperature trends in the US and around the world. I will then show how the coupling between soil moisture and temperatures can bias climate impact projections based solely on temperature. Shifts in soil moisture-temperature coupling will be examined using earth system models.

How to cite: Mueller, N.: Land-atmosphere interactions and agricultural climate impacts, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-11358, https://doi.org/10.5194/egusphere-egu2020-11358, 2020.

Seasonal snow massively impacts the surface energy budget through its high reflectivity and is therefore an important component of land-atmosphere models. It affects climate through Snow Albedo Feedback (SAF), a positive feedback mechanism between a reduced snow cover extent due to climate warming and the corresponding increase of shortwave absorption, which provokes a further reduction in snow cover extent. SAF has been shown to be the largest climate feedback over the extratropical Northern Hemisphere (NH) during the snow melt period. Yet, large biases in SAF projections are linked to snow-vegetation interactions.

This study aims at investigating uncertainties associated with the representation of wintertime Land Surface Albedo (LSA) of forested environments in global climate models, which is an essential aspect when studying SAF. UAV-based observations of LSA were used to assess corresponding LSA simulations in CLM5, the land component of the NCAR Community Earth System Model. Our measurements capture a wide range of forest structure and species found in seasonally snow covered environments, spanning from Swiss sub-alpine to Finnish boreal forests, and show a strong dependency of LSA on solar angle and canopy density. CLM5 simulations failed to capture a realistic range in LSA and shortcomings were identified particularly with regards to simulations at sparsely forested sites. In these environments, Leaf Area Index as the main descriptor of canopy structure was unable to explain observed LSA differences in space and time. This study emphasizes the need to improve the representation of canopy structure in land surface models with critical implications for simulations of Snow Albedo Feedback strength over the NH extratropics.

How to cite: Malle, J., Rutter, N., Webster, C., Mazzotti, G., Wake, L., and Jonas, T.: Effect of forest canopy structure on wintertime Land Surface Albedo: Comparing CLM5 simulations to in-situ observations , EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-16017, https://doi.org/10.5194/egusphere-egu2020-16017, 2020.

Heatwaves are a serious threat to society and can lead to grave consequences. It is well known that persistent large-scale circulation anomalies are the key to generating heatwaves. Vegetation plays a vital role in energy and water exchange between land and atmosphere, through its responses to incoming radiation and emission of longwave radiation, its imposition of surface friction and transpiration. However, its impact on surface energy exchange during heatwaves is largely unknown. In this study, we first analyzed the relationship between summer heatwaves and vegetation cover, based on the Global Heatwave and Warm-spell Record (GHWR) and leaf area index (LAI) products from satellites during 1982-2011. Our results revealed differences in the correlation between heatwave characteristics and summertime LAI in different regions. In particular, lower LAI over Central Europe is associated with more frequent heatwaves locally. Over the south to the southeastern part of North America, a similar negative correlation is found. However, in the northeastern part of the continent, the reverse tends to be true, with higher-than-normal LAI associated with an increase of heatwave occurrence. These findings are in general supported by composite analyses of extreme LAI years in these regions and heatwave characteristics therein.

We speculate that the difference between surface heat flux responses for different vegetation types during heatwaves may explain the results. Focusing on North America, and using various datasets including those generated by the Global Land Data Assimilation System (GLDAS) with three different land surface models (CLM, MOS, NOAH), three reanalysis datasets (MERRA-2, NOAA-CIRES-DOS, NCEP/NCAR), and also observations from an extensive network of flux towers, it was found that over coniferous forests (both boreal and temperate), the sensible heat anomalies increase significantly during heatwaves in high-LAI years. Also, during high-LAI years, over boreal evergreen forests (BEF), changes of latent heat anomalies are much smaller than positive sensible heat anomalies, so that BEF can prolong and amplify heatwaves significantly. On the other hand, for temperate deciduous forests (TDF) and grassland (GSL), both negative sensible heat anomalies and positive latent heat anomalies during heatwaves are found in all datasets; these response act to weaken the heatwave amplitudes. Model experiments were further carried out, in order to test the sensitivity of heatwaves to LAI forcings. It was found that heatwaves are most sensitive to BEF LAI variations, but the response of heatwaves are opposite between middle and high latitudes when BEF LAI increased. For TDF and GSL, heatwaves shortened slightly when LAI increased.

How to cite: Li, J., Tam, C.-Y., Tai, A. P. K., and Lau, N.-C.: Sensitivity of Summertime Heatwaves to Vegetation Cover in the Northern Hemisphere, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-5041, https://doi.org/10.5194/egusphere-egu2020-5041, 2020.

Land cover changes (LCCs) influence the regional climate because they alter biophysical mechanisms like evapotranspiration, albedo, and surface roughness. Previous research mainly assessed the regional climate implications of individual land cover transitions, such as the effects of historical forest clearance or idealized large-scale scenarios of deforestation/afforestation, but the combined effects from the mix of recent historical land cover changes in Europe have not been explored. In this study, we use a combination of high resolution land cover data with a regional climate model (the Weather Research and Forecasting model, WRF, v3.9.1) to quantify the effects on surface temperature of land cover changes between 1992 and 2015. Unlike many previous studies that had to use one unrealistic large-scale simulation for each LCC to single out its climate effects, our analysis simultaneously considers the effects of the mix of historical land cover changes in Europe and introduces a new method to disentangle the individual contributions. This approach, based on a ridge statistical regression, does not require an explicit consideration of the different components of the surface energy budget, and directly shows the temperature changes from each land transition.

            From 1992 to 2015, around 70 Mha of land transitions occurred in Europe. Approximately 25 Mha of agricultural land was left abandoned, which was only partially compensated by cropland expansion (about 20 Mha). Declines in agricultural land mostly occurred in favor of forests (15 Mha) and urban settlements (8 Mha). Relative to 1992, we find that the land covers of 2015 are associated with an average temperature cooling of -0.12±0.20 °C, with seasonal and spatial variations. At a continental level, the mean cooling is mainly driven by agriculture abandonment (cropland-to-forest transitions). Idealized simulations where cropland transitions to other land classes are excluded result in a mean warming of +0.10±0.19 °C, especially during summer. Conversions to urban land always resulted in warming effects, whereas the local temperature response to forest gains and losses shows opposite signs from the western and central part of the domain (where forests have cooling effects) to the eastern part (where forests are associated to warming). Gradients in soil moisture and local climate conditions are the main drivers of these differences. Our findings are a first attempt to quantify the regional climate response to historical LCC in Europe, and our method allows to unmix the temperature signal of a grid cell to the underlying LCCs (i.e., temperature impact per land transition). Further developing biophysical implications from LCCs for their ultimate consideration in land use planning can improve synergies for climate change adaptation and mitigation.

How to cite: Huang, B., Hu, X., Fuglstad, G.-A., Zhou, X., Zhao, W., and Cherubini, F.: Unmixing the regional climate response to recent historical land cover changes in Europe, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-4866, https://doi.org/10.5194/egusphere-egu2020-4866, 2020.

The properties of the type of surface covering the land have a direct effect on their surrounding atmosphere due to biophysical mechanisms. When the land cover type is altered, or when its properties change due to land use management, there can be a repercussion on the climate that goes beyond the associated changes in greenhouse gases. Satellite remote sensing observations have recently been instrumental to quantify and map these biophysical effects across geographical and seasonal gradients. The typical variable that is measured is temperature, as it integrates the combined effects of changes in surface albedo, soil moisture and vegetation state. Up-to-now, studies have generally focused on analyzing the mean response of land use and land cover change (LULCC) assuming a static climate. Here we revisit a proven methodology to infer the potential effects of LULCC on temperature based on a local space-for-time substitution, but we apply it annually across the globe for 15 consecutive years covering changing climate conditions. This opens the possibility to explore the inter-annual variability of the biophysical effects of LULCC, along with changes across climatic gradients. At specific look on extreme events enables us to assess how these dampen or amplify the biophysical effects of different LULCC transitions. Overall, this study establishes a first step towards inferring an observation-driven diagnostic that can provide guidance towards land-based mitigation strategies for a future and changing climate.

How to cite: Duveiller, G. and Cescatti, A.: Biophysical effects of LULCC in a changing climate, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-17927, https://doi.org/10.5194/egusphere-egu2020-17927, 2020.

The EUMETSAT Land Surface Analysis Satellite Application Facility (LSA-SAF) now offers a wide range of satellite-derived products for land surface monitoring. The catalogue comprises variables quantifying different terms of the surface energy balance (land surface temperature – LST - and emissivity, downwelling radiative fluxes and turbulent fluxes), as well as several vegetation-related indicators, such as the Leaf Area Index, Fraction of Vegetation Cover, Evapotranspiration, Net Primary Production and Fire Radiative Power. The availability of these datasets, especially taking into account that the time series now span nearly two decades,  already allows many interesting applications, overviewed in this presentation.

Comparisons of remote sensing data for land surfaces with corresponding model data have already been useful: the standard L2 (clear sky) LST has been used to diagnose a systematic cold bias of ERA5 skin temperature over the Iberian Peninsula. Offline simulations using H-TESSEL revealed that the bias could be alleviated using a more realistic representation of vegetation than what is currently used in ERA5. A recently developed product by LSA SAF allows LST retrievals for all-weather conditions, using a surface energy balance model to provide estimates under cloudy pixels. This product is compared to ERA5-Land skin temperature, showing that despite the increased level of detail of the latter (with respect to ERA5), it is still not representing the former correctly. ERA5 Land skin temperature shows large biases (of more than 10 K) and phase errors (with the satellite LST warming up prior to ERA-Land during the morning and cooling down earlier in the late afternoon). Comparisons of the different terms of the surface energy balance from ERA5-Land and LSA SAF are currently in progress to identify causes of the biases.

Another interesting application of LSA SAF products is the study of vegetation recovery over wild fire scars. Five wild fire events over Portugal were analyzed in terms of the long term anomalies introduced by the fire in 3 variables: LST, Albedo and Fraction of Vegetation Cover (all provided by LSA SAF). Results suggest that albedo returns to close-to-normal conditions in less than a year, while LST anomalies last much longer.  

Finally, trends in the land-ocean thermal contrast were evaluated over Western Iberia and Northwest Africa (due to its importance in generating coastal mesoscale circulations). The study used long time series from 1) satellite – LST from CM-SAF and SST from GHRSST; 2) ERA5 global reanalysis and 3) UERRA regional reanalysis. The results strongly depend on the used dataset and sub-region, with UERRA showing a sharp decrease of the thermal contrast over Iberia, while ERA5 shows a positive trend.

These results emphasize the need to improve the representation of surface processes in numerical models, particularly over land surfaces. This presentation shows that datasets such as the ones provided by the LSA SAF are key to such improvements.

How to cite: Martins, J., Trigo, I., Silva, M., Cunha, R., Johannsen, F., DaCamara, C., Ermida, S., Dutra, E., and Gouveia, C.: Overview of applications of Remote Sensing Data Records and Reanalysis for the study of surface processes, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-19613, https://doi.org/10.5194/egusphere-egu2020-19613, 2020.

Flash droughts can cause a short-term but severe devastating impacts to agriculture and the ecosystem. However, the mechanism and characteristics of flash droughts remain unexplored in the monsoon dominating climate over India. Here, we use the hydro-meteorological variables from ERA-5 reanalysis to derive surface vapour pressure deficit (VPD), and soil moisture (SM) from GLEAM to construct a copula based SM-VPD index [named as Evaporative Soil Moisture Index (ESMI)], which is used to identify flash droughts in India. First, we evaluate the land-atmospheric coupling, which suggests that SM-VPD has a strong negative correlation in both monsoon and non-monsoon seasons. Soil Moisture and evapotranspiration (ET) show a strong negative and positive relationship in the monsoon and non-monsoon season, respectively. Our results show that unlike ET based indices (e.g. evaporative stress index), ESMI captures flash droughts in both monsoon and non-monsoon seasons over India. We identified and evaluated six major flash drought that occurred during the 1980-2018 period using ESMI along with their driving mechanism.

How to cite: Mahto, S. S. and Mishra, V.: Mechanism and Characteristics of Flash Droughts in India and their Evaluation Using Evaporative Soil Moisture Index (ESMI), EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-12616, https://doi.org/10.5194/egusphere-egu2020-12616, 2020.

South East Australia is characterised by a diverse climate ranging from lush, temperate mountain ranges to hot and arid grasslands. The region is home to Australia's largest river system, the Murray-Darling. The Murray-Darling Basin is an important agricultural region, generating almost 50% of Australia's total irrigated agricultural production in 2018. Rainfall in this region is typically highly variable and subject to severe drought. The Millennium Drought (2001-2009), widely known as the worst drought on record and one of the most severe in the world, has now been superseded by a worse drought (2017-present), setting a new extreme in the drought record. During the current drought, rainfall, root zone soil moisture and water storages have reached record-breaking low levels. High temperatures have also broken historical records on multiple occasions since the drought began. Drought conditions and exceptionally high temperatures have dried the landscape, which has led to intense bushfires that have so far ravaged over 5 million hectares.

Yet the degree to which the land surface exacerbates drought in the Murray-Darling Basin remains unknown. In other words, the relative importance of local versus remote processes affecting rainfall, particularly during drought, is uncertain. Where does the moisture come from, and how strongly do local land surface processes attenuate or amplify this atmospheric moisture to affect local rainfall? Establishing the evaporative source regions that supply moisture for rainfall can help reveal the mechanisms driving anomalously low rainfall. In the case of drought, it can help reveal whether anomalous rainfall was due to a reduction in source evaporation, anomalous atmospheric circulation (i.e., the moisture was generated but transported somewhere else), land surface control on the atmosphere through feedbacks, or a combination of factors.

We used a Lagrangian back-trajectory approach to determine the long-term average evaporative source regions that supply Australia's rainfall, and the level of recycling that rainfall undergoes. The back-trajectory model tracked water vapour from the location of rainfall events backward in time and space and identified the evaporative origin. From this, we calculated the proportion of rainfall falling across the Murray-Darling Basin that originated as evapotranspiration from the Basin itself; that is, the rainfall recycling ratio.

By combining this long-term baseline of source region and rainfall recycling with anomalies of source region evaporation and local atmospheric boundary layer properties, we found that the drivers of low rainfall changed through time during the Millennium Drought. At the peak of the Drought the anomalously low rainfall was driven by a lack of atmospheric moisture advected from the identified typical source region; at other times the low rainfall was due to local conditions unfavorable for the precipitation of available moisture. Overall we found that land surface control on the atmosphere exacerbated the Millennium Drought by approximately 10%.

How to cite: Holgate, C., Evans, J., Van Dijk, A., and Pitman, A.: To what degree does land-atmosphere feedback exacerbate drought in South East Australia?, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-4313, https://doi.org/10.5194/egusphere-egu2020-4313, 2020.

The occurrence of extreme climate events such as droughts and heatwaves can have negative economic, environmental and social impacts. The simultaneous or sequential occurrence of these extreme events can increase these impacts, and their frequency is expected to increase in many regions of the world. Moreover, the occurrence of hot days/nights was shown to be correlated to drought conditions in Mediterranean areas. Recently the catastrophic fire seasons of 2019/2020 in Australia has been pointed out to be associated with a drought exacerbation of the summer hot conditions. Additionally, temperature trends In Australia since 1970 are positive in most of the territory, whereas annual precipitation presents a negative trend in the East and a positive trend in the West.

In this work, we propose to analyze the relation between summer hot days/nights and antecedent drought conditions in Australia. The Standardized Precipitation Evapotranspiration Index (SPEI) at time-scales of 1 to 6 months was used to assess drought conditions. The indices Number of Hot Days (NHD) and Number of Hot Nights (NHN) were computed as the number of days on each month that exceed the 90^th percentile of maximum and minimum temperatures, respectively. Data to compute these indices were retrieved from the ERA5 climate reanalysis dataset, and from the CRU TS4.03 dataset. Temperature data from the ACORN-SAT dataset was also used. A correlation analysis was performed between SPEI and NHD/NHH, using the concurrent months, and also the SPEI values on the previous 1 to 3 months. Significant negative correlations were obtained in southern regions. A probabilistic approach was also used, using copula functions, which allowed to estimate the joint probability of occurrence of dry and hot events.

Acknowledgements: This work was partially supported by projects FireCast (PCIF/GRF/0204/2017), and IMPECAF (PTDC/CTA-CLI/28902/2017). Andreia Ribeiro thanks FCT for the grant PD/BD/114481/2016.

How to cite: Páscoa, P., Gouveia, C., Russo, A., and Ribeiro, A.: Are the antecedent drought conditions magnifying the summer hot extremes in Australia, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-19581, https://doi.org/10.5194/egusphere-egu2020-19581, 2020.

Droughts can be studied from an atmospheric perspective by analysing the large-scale circulation resulting in a lack of water, or from a hydrological perspective by understanding the interaction of precipitation, evaporation, soil moisture and temperature at the land surface. Here, both perspectives are captured as we study the evaporative sources resulting in precipitation over the Rhine basin. These evaporative sources, being continental or oceanic, can give an indication of the vulnerability of a basin to ongoing and future land-use changes. We focus on the anomalous evaporative sources of the Rhine basin during the dry summers of 2018 and 2003, to understand what the contribution is of local recycling of precipitation versus advection of moisture into the basin to the total amount of precipitation over the Rhine basin. We do so by using ERA5 re-analysis data from 1979 to 2018 and the Eulerian moisture tracking model WAM-2layers.

During an average summer, the evaporative sources of the Rhine basin are mostly located over the Atlantic ocean. In addition there is a substantial contribution of continental evaporation, mostly from land regions west of the Rhine basin. During the summer of 2018 a persistent high pressure system (blocking) prevented moisture input from the Atlantic ocean and therefore relative more recycling of moisture over land took place (both continental areas outside the basin and within the Rhine basin). Due to the anti-cyclonic movement around the high pressure area, we also found a larger contribution of evaporative sources from continental regions east of the Rhine basin.

The amount of local recycling can be expressed in the precipitation recycling ratio, the local generated precipitation divided by the total precipitation in a region. We found higher than average recycling ratios during the dry summer months of 2018. Thus, due to the blocking more local evaporation resulted in precipitation over the Rhine basin, indicating the increased dependence on local land-surface processes. In general, we found a clear correlation between higher than normal recycling ratios and lower than normal precipitation in summer. An exception is the end of the dry summer of 2003, when low recycling ratios are found, probably indicating drying out of the soils and therefore lower evaporation rates.

To conclude, although the summer of 2003 and 2018 were both very dry, their characteristics in terms of moisture sources and thereby their dependence on the land surface were found to be rather different. In 2018, local recycling was important, contrasting to 2003 when the drying out of the soils made local recycling less important. These differences between two dry years over the same region highlight the important role of the land surface in precipitation feedbacks.

How to cite: Benedict, I., van Heerwaarden, C., van der Linden, E., Weerts, A., and Hazeleger, W.: Differences and similarities between the 2018 and 2003 droughts for the Rhine basin studied in terms of evaporative sources, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-20283, https://doi.org/10.5194/egusphere-egu2020-20283, 2020.

Northeast China (NEC) suffered its worst persistent drought event in recent decades from March to July of 2017 with devastating impacts on the environment and agriculture. Previous drought mechanism studies focused on the atmospheric remote response to Arctic sea ice and ENSO, while less attention was paid to synergistic effects of large-scale teleconnections and local land-atmosphere coupling. Here we show that a strong positive phase of Arctic Oscillation in March triggered the NEC drought, and a quasi-stationary Rossby wave train maintained the drought with an anticyclone located over the area south to Lake Baikal (ASLB) in April-July. By using a land-atmosphere coupling index based on the persistence of positive feedback between boundary layer and land surface, we find that the NEC and ASLB experienced a wet coupling in March while a persistently strengthened dry coupling in April-July. Over ASLB, the dry coupling and sinking motion increased surface sensible heat, decreased cloud cover, and weakened longwave absorption, resulting in a diabatic heating anomaly in the lower atmosphere and a diabatic cooling anomaly in the upper atmosphere. This anomalous vertical heating profile generated a negative anomaly of potential vorticity, indicating that the land-atmosphere coupling had a phase-lock effect on the Rossby wave train originating from upstream areas, and therefore maintained the NEC drought over downstream regions. Numerical simulations with and without surface sensible heating are being conducted to verify the influence of teleconnected land-atmosphere coupling, i.e., dry land conditions over ASLB in May can cause positive height anomaly over ASLB and NEC during June-July through heating the low level atmosphere. Our study suggests that upstream quasi-stationary wave pattern strengthened by land-atmosphere coupling should be considered in diagnosing persistent droughts especially over northern mid-latitudes.

How to cite: zeng, D. and yuan, X.: The Northeast China Persistent Drought in Spring-Summer of 2017: Joint Roles of Teleconnection and Land-atmosphere Coupling, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-7998, https://doi.org/10.5194/egusphere-egu2020-7998, 2020.

With an average height greater than 4500m and an area covering approximately 2.5 million km², the Tibetan Plateau (TP) plays a crucial role in determining the large-scale atmospheric circulation across South-East Asia. Substantial intraseasonal precipitation variability is observed across TP associated with the subtropical jet location and silk road pattern. A northward shift of the subtropical jet is associated with reduced precipitation over TP. Through analysis of weather station data and satellite observations, a diurnally-varying sensitivity of the land surface to intraseasonal precipitation variability is concluded. For example, a prolonged dry spell is associated with warmer ground temperatures and increased surface sensible heat flux. Using reanalyses the influence of anomalous surface conditions across TP, associated with intraseasonal precipitation variability, on the local and remote circulation is investigated.

During a dry spell increased surface sensible heat flux deepens the planetary boundary-layer and leads to the development of a localised heat low anomaly. In the upper-troposphere surface sensible heating forms an anticyclonic anomaly above TP which induces an upper-level Rossby-wave train. The induced Rossby-wave train is associated with an anomalous cyclonic circulation across central China and a westward extension of the west Pacific subtropical high. These circulation anomalies induced by TP surface warming are associated with climate extremes across South-East Asia including an increased risk of flash drought across central China and higher probabilities of extreme precipitation across southern China. The association between land-atmosphere interactions across TP and climate extremes in South-East Asia highlight the importance of land-atmosphere feedbacks in forecasting climate extremes.

How to cite: Talib, J. and Taylor, C.: The influence of Tibetan Plateau surface warming on climate extremes across South-East Asia, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-8971, https://doi.org/10.5194/egusphere-egu2020-8971, 2020.

Understanding changes in sub-daily precipitation extremes and its attribution is critical for urban planners to build more sustainable and reliant cities. Three major urban agglomerations have been formed in China as a result from fast economic development since about the early-1990s, namely, the Pearl River Delta (PRD) in coastal South China, the Yangtze River Delta (YRD) in coastal East China, and the Beijing-Tianjin-Hebei (BTH) region in northern China. In this study, the hourly precipitation data in 1971-2018 from national weather stations are combined with historical land-use change data to investigate changes in extreme hourly precipitation (EXHP) in the three regions. Also, a large ensemble of extreme rainfall events (EXREs) during 2011-18 are analyzed using observations collected by densely-distributed automatic weather stations and radar network combined with reanalysis data. The results suggest that the strong urban heat island (UHI) effect in these urban agglomerations is conducive to intensification of hourly precipitation. However, statistically insignificant changes in EXHP are observed over the BTH region. In contrast, significantly increasing frequency of EXHP occur over the other two coastal urbanized regions, with some distinct features in the evolution of EXHP-producing storms and the relevant synoptic situations between the two regions. The individual and combined effects of land-cover and land-use (LCLU) change and increasing anthropogenic aerosol emission are investigated by use of an integrated modeling approach. An ensemble of convection-permitting simulations is performed, combining two LCLU and aerosol emission scenarios. The influences of these two factors are discussed based on the simulations.

How to cite: Luo, Y., Furtado, K., and Gordon, H.: How and why has extreme hourly precipitation changed in the major urban agglomerations over China?, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-3980, https://doi.org/10.5194/egusphere-egu2020-3980, 2020.

Urban environments are known to be warmer than their sub-urban or rural surroundings, particularly at night. In summer, urban heat islands exacerbate the occurrence of extreme heat events, posing health risks to urban residents. In the UK where 90% of the population is projected to live in urban areas by 2050, projecting changes in urban heat islands in a warming climate is essential to adaptation and urban planning.

With the use of the new UK Climate Projections (UKCP18) in which urban land use is constant, I will show that both summer urban and sub-urban temperatures are projected to increase in the 10 most populous built-up areas in England between 1980 and 2080. However, differential warming rates in urban and sub-urban areas, and during day and at night suggest a trend towards a reduced daytime urban heat island effect but an enhanced night-time urban heat island effect. These changes in urban heat islands have implications on thermal comfort and local atmospheric circulations that impact the dispersion of air pollutants. I will further demonstrate that the opposite trends in daytime and night-time urban heat island effects are projected to emerge from current variability in more than half of the studied cities below a global mean warming of 3°C above pre-industrial levels.

How to cite: Lo, E., Mitchell, D., Bohnenstengel, S., Collins, M., Hawkins, E., Hegerl, G., Joshi, M., and Stott, P.: Emergence of opposite trends in daytime and night-time urban heat island intensities in England, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-5671, https://doi.org/10.5194/egusphere-egu2020-5671, 2020.

Extreme heat events are rising in nature over the Indian subcontinent under the stressed environmental conditions. Unprecedented event of extreme heat is threatening our socio-economic and ecosystem. April marks the start of summer with a clear sky; agricultural harvesting exposes the large land surface to solar heating, so the drying up of the surface causing loss of soil moisture and vegetations. Temperature anomalies become high during May and June, signifying possible role play local land-surface-atmosphere feedbacks involving dried soils in driving the heat extreme. Thus, the study of extreme heat and surface feedback process is conducted using a combination of ERA5 reanalysis data, GLDAS Noah Land Surface Model data, satellite-based observations (TRMM and MODIS), and in-situ India Metrological Department datasets. To address the bias present in datasets, we make use of IMD Datasets for bias correction. We use 2m air temperature to define the extreme heat events as per the IMD definition for the heatwave from 2001 to 2019. Parameters like surface net solar and thermal radiation and (also, clear sky) heat flux, total precipitation, land surface temperature, land use type and vegetation cover, soil moisture used to study the details of land surface conditions during the heatwave events. The examination of the above datasets in space-time provided the general view of heatwaves and suggest that late April and early May with clear sky increased net solar radiation started drying up the surface. Late May and early June with a clear sky and positive net solar radiation anomaly with positive heat flux anomaly and lack of soil moisture and rainfall developed local forcing on air temperature that catalyzed the heatwave events in terms of intensity and duration. The above conclusion is supported by the satellite-derived land surface temperature and heat flux. The results obtained establish the link between the local surface feedback and extreme heat events during the summer over the Indian subcontinent and can enhance in a dry environment with the large agricultural field with no standing crop barren land or land with dead or no shrubs over India leaving northern Himalayan part.

How to cite: Kumar, S. G. and Goswami, A.: Study of Land Surface feedback in catalysing the intensity and duration of Heatwave over Indian subcontinent, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-1103, https://doi.org/10.5194/egusphere-egu2020-1103, 2020.

Large parts of the earth’s land surface are modified by humans. Since the land surface and the atmosphere are constantly in energy exchange and in interactions with each other, anthropogenic modifications of the land’s surface can lead to effects on the climate. The objective of this study is to quantify and investigate the effects and feedbacks of irrigation on the local to regional climate. Irrigation is a land use practice, which does not change the land cover type but changes the biophysical properties of the land’s surface and the soil and thus alters energy and moisture fluxes. These local to regional process responses, detectable in different meteorological variables, are investigated using the regional climate model REMO. High resolution simulations at convection permitting scales will be performed in order to particularly investigate irrigation effects on the spatiotemporal behavior of moist convection. Newly developed parameterizations of different types of irrigation are tested on the example of a northern Italian model domain, where cropland and rice paddies are the dominating land cover. The focus of the sensitivity study is on the impact of the parameterizations on the surface moisture and energy balance as well as on heavy rainfall events.

How to cite: Asmus, C., Hoffmann, P., Rechid, D., and Böhner, J.: Modeling the effects and feedbacks of irrigation on the regional climate in Northern Italy, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-8913, https://doi.org/10.5194/egusphere-egu2020-8913, 2020.

Several recent studies have highlighted the importance of irrigation-induced changes in climate. Earth system models are a common tool to address this question, and to this end, irrigation is increasingly being represented in their land surface modules. Despite this evolution, currently, none of them considers different irrigation techniques. Here we develop and test a new parameterization that represents irrigation activities in the Community Land Model version 5 (CLM5) and considers three main irrigation techniques (surface, sprinkler and drip irrigation). Using global maps of the areas equipped by different irrigation systems, we will employ version 2 of the Community Earth System Model (CESM2) and its improved irrigation representation to detect the impacts of irrigation on climate. Two control experiments are designed, one with the new irrigation scheme and another with the original one. We will conduct an evaluation by comparing the simulated results against observed surface fluxes and meteorological variables. Subsequently, the differences between the experiments will be analyzed to quantify the impacts of irrigation on climate. We anticipate that our results will uncover whether considering different irrigation schemes is of value for exploring irrigate-induced impacts on climate.

How to cite: Yao, Y., Swenson, S., Lawrence, D., and Thiery, W.: Implementing irrigation techniques in CESM2, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-1120, https://doi.org/10.5194/egusphere-egu2020-1120, 2020.

Biogenic volatile organic compounds (BVOC) are emitted by trees. In the presence of NOx they can help to produce tropospheric ozone. During heat waves this can cause a critical additional stress for human wellbeing, especially in areas exhibiting high NOx concentrations. Heat wave intensity and frequency is expected to increase.

To estimate the potential threat, we simulate BVOC emissions over the Vienna region during an extreme heat wave using the Model of Emissions of Gases and Aerosols from Nature (MEGAN) (Guenther et al. 2012) in its latest version 3.  We adapted the model to directly ingest the files used and produced by the land surface model SURFEX8.1 (Surface Externalisée, in French) (Boone et al. 2017) and its preprocessors. In this poster we present our methodology and first results showing the spatial distribution and time series of selected BVOCs.

The chosen heat wave covers 5 days during August 2015, with an average daily 2 m air temperature of 36.3 °C, and represents a significant event with a 15 year return period (of the period 1988-2017).

The LAI and soil parameters field capacity and wilting point are taken from the physiographic fields derived from ECOCLIMAP,  soil moisture and temperature from the prognostic SURFEX output fields calculated for urban and non-urban areas, the 2m air temperature from the diagnostic output fields of SURFEX.

The meteorological forcing is used to create daily meteorology parameters and together with LAI maps run the canopy meteorology module. Further we use the soil emission activity module to calculate a soil temperature and soil moisture dependent isoprene soil emission activity factor. Using these datasets the emission activity factors are calculated. Finally, the emission activity factors are converted from 20 to 201 species and lumped according to the RACM2 mechanism. 

First results, show the strong dependence of isoprene emissions on incoming photosynthetically active radiation and LAI. In the course of the
heat wave isoprene emissions decline, which correlates with the decline in soil water availability and consqequent decreased stomatal opening. 

Boone, A., Samuelsson, P., Gollvik, S., Napoly, A., Jarlan, L., Brun, E., & Decharme, B. (2017). The interactions between soil–biosphere–atmosphere land surface model with a multi-energy balance (ISBA-MEB) option in SURFEXv8 – Part 1: Model description. Geoscientific Model Development, 10(2), 843–872.

Guenther, A. B., Jiang, X., Heald, C. L., Sakulyanontvittaya, T., Duhl, T., Emmons, L. K., & Wang, X. (2012). The Model of Emissions of Gases and Aerosols from Nature version 2.1 (MEGAN2.1): an extended and updated framework for modeling biogenic emissions. Geoscientific Model Development, 5(6), 1471–1492.

How to cite: Trimmel, H., Hamer, P., and Karl, T.: BVOC emission simulation for the Vienna region during an extreme heat event., EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-4228, https://doi.org/10.5194/egusphere-egu2020-4228, 2020.

Climate observations and projections for Australia show an increase in warm temperature extremes, including the frequency, duration and intensity of heatwaves. Recent global scale studies have suggested that agricultural land-use management options, such as increasing crop albedo, could reducing local warming. Australia has approximately 3,727,210 km² of cropland agricultural land-use, the majority of which is in southwest Western Australia and southeast Australia. This presents a potential opportunity to reduce regional warming via crop albedo enhancement. We use a regional climate model at 10 km resolution, to show that crop albedo enhancement of up to 0.1 could reduce monthly mean daily maximum temperatures by -1.0°C to -1.2°C, and monthly highest maximum temperatures by up to -1.4°C to -1.6°C during the cropping season. This cooling is approximately 3 times higher over Australia than global climate models predict. We highlight stronger cooling over southwest Western Australia as compared to southeast Australia, the opposite to global model studies which poorly resolve southwestern agricultural regions. The regional cooling was driven by a reduction in surface net shortwave radiation leading to a decrease in both sensible and latent heat flux of up to 50 W m^-2 and 20 W m^-2 respectively, when albedo is increased by up to 0.1. There were no cloud feedbacks or effects on precipitation. Our results highlight the importance of using regional climate models at a sufficiently high spatial resolution when investigating agricultural land-use management to reduce regional warming.

How to cite: Kala, J. and Hirsch, A.: Could crop albedo modification reduce regional warming over Australia?, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-4315, https://doi.org/10.5194/egusphere-egu2020-4315, 2020.

The Arctic is undergoing amplified climate change and forecasts predict increased warming and precipitation in the future. How changes in temperature and precipitation affect the partitioning of the Arctic land surface energy budget is not clear, despite the importance of both the Arctic region and the surface energy budget in earth system processes at local, regional, and global scales.

We will investigate the Arctic tundra energy budget and the relative importance of biotic and abiotic drivers. Specifically, we are experimentally testing effects of changing summer precipitation on the partitioning of the surface energy budget by simulating precipitation-based climate extremes – extreme drought and extreme precipitation totals.

We will present a literature-based synthesis of the expected impact of drought and extreme rainfall on the energy budget components of the tundra land surface and a description of the experimental design and treatments. The experiment has been established at a long-term Siberian tundra test site (71°N, 147°E). Extreme drought (precipitation) is being simulated by removing (adding) a predetermined fraction of ambient precipitation from (to) the test plots. Control plots, where ambient precipitation is not modified, are used as a baseline. Plot selection, soil sampling, and installation of below-ground sensors were performed during the past two summers, while setup of shelters and water-addition installations were completed early July 2019.

With our results on energy budget behavior change under future summer precipitation scenarios, we expect to inform mechanistic and statistic modeling of species distributions, ecosystem functions, and climate feedback in the Arctic tundra.

How to cite: Grysko, R., Plekhanova, E., Oehri, J., and Schaepman-Strub, G.: Tundra Energy Fluxes under Drought and Extreme Summer Rainfall Scenarios, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-5606, https://doi.org/10.5194/egusphere-egu2020-5606, 2020.

Uncertainties in the Noah with multiparameterization (Noah-MP) land surface model are assessed through physics ensemble simulations in four sparsely vegetated sites located in the central and western Tibetan Plateau. The simulated hydrological components are evaluated using observations at those sites during the third Tibetan Plateau Experiment from August 1st, 2014 to August 1st, 2015. By using natural selection, the crucial subprocesses impacting the hydrological component simulations are identified. The effects of precipitation uncertainties and soil organic matter on the energy fluxes and water cycles are analyzed through a set of sensitivity experiments based on an optimal scheme set. The uncertainty analyses indicate that the greatest uncertainties are in the subprocesses of runoff (RNF) and groundwater, surface-layer parameterization and frozen soil permeability, along with the subprocesses of snow surface albedo and the lower boundary of soil temperature for the bare ground site but the subprocesses of the canopy resistance and soil moisture limiting factors for evaporation for the three alpine grassland sites. The sensitivity analyses reveal that more precipitation can increase the annual total net radiation (Rn), latent heat flux (LE) and RNF but decrease sensible heat flux (SH). Compared to the insufficient precipitation, the relatively small increase in precipitation results in the LE increase during the growing season at the Amdo and Baingoin sites but an RNF increase at the Nagqu site (sandy soil). However, when more precipitation was added, a greater proportion of the added water was distributed to the RNF at the Nagqu site and to the soil liquid water at the Amdo and Baingoin sites. The organic soil increases the annual total LE but reduces the annual total Rn, SH, and RNF. The effect of the soil organic matter on the LE and RNF at the Nagqu site (sandy soil), is greater than that at the other three sites (sandy loam soil).

How to cite: Zhang, G., Chen, F., Chen, Y., and Li, J.: Evaluation of Noah-MP land-model uncertainties over sparsely vegetated sites on the Tibet Plateau, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-6261, https://doi.org/10.5194/egusphere-egu2020-6261, 2020.

Drought occurrence and drought severity are likely to increase in the future due to more extreme weather conditions. Drought preparedness and mitigation can be achieved with the help of skilful drought forecasts and accurate quantifications of both drought severity and drought impact. For that to be possible, we first need to be aware of the spatiotemporal evolution of agricultural droughts and their main effects on vegetation. Therefore, in this study, we evaluated patterns in soil moisture and vegetation during the large scale droughts that occurred in between 2000 and 2018.

Soil moisture data were obtained from the CCI v04.5 dataset. ­­­Vegetation was analysed using (1) the Normalized Difference Vegetation Index (NDVI), a common approach to quantify vegetation cover, and (2) near-infrared reflectance of vegetation (NIR_v), which has been shown to strongly correlate to Gross Primary Production (GPP) and canopy development. Both vegetation datasets were derived from MODIS reflectance data. All three datasets were normalized to allow for an in-depth comparison of drought patterns in both space and time.

Correlations were found between soil moisture and vegetation data, and showed the possibility to discern the occurrence of water- and energy- limited vegetation. In both North and South Europe, soil moisture dry anomalies show lower correlation with dry anomalies in vegetation compared to central Europe: the highest correlations were consistently found in between 55-60˚N. In Northern Europe, the lower correlations are likely due to vegetation being energy limited rather than water limited, even during soil moisture drought events. In Southern Europe, on the other hand, it can be argued that the vegetation is better adapted to drought conditions and, as a result, the drought has less impact on vegetation. This analysis shows that drought impacts are not only related to drought severity, but also to latitude and thus climate.

­­In addition, we look at time lags between soil moisture droughts and drought impacts on vegetation, a comparison between the different years in drought over the past two decades and a comparison between drought signatures per precipitation regime. The results of this study will provide insights on the evolution of different droughts and their effects on vegetation. They could be used in future efforts regarding agricultural drought forecasting, because main trends can be predicted.

How to cite: van Hateren, T. C., Chini, M., Matgen, P., and Teuling, A. J.: Spatio-temporal analysis of remotely sensed soil moisture and vegetation patterns during recent European droughts, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-7094, https://doi.org/10.5194/egusphere-egu2020-7094, 2020.

Studies on future precipitation trends in the Mediterranean region show a possible decrease in annual precipitation amounts with an intensification of extreme events in the coming years. A major challenge in this region is to evaluate the impacts of changing precipitation patterns on extreme hydrological events such as droughts and floods. For this, it is important to understand the effects of changing temperature and precipitation on soil moisture since it is a good proxy for drought monitoring and it plays a key role on flood runoff generation. This study focuses on 11 sites located in the South of France, with soil moisture, temperature, and precipitation observations over a 10 year time period. Soil moisture is simulated at the hourly time step for each site using a soil moisture model based on the Green-Ampt infiltration scheme. The elasticity of the simulated soil moisture to different changes in precipitation and temperature is analyzed by simulating the soil moisture response to temperature and precipitation changes, generated using a delta change method for temperature and a stochastic model (Neyman-Scott rectangular pulse model) for precipitation. Results show that soil moisture is more impacted by changes in precipitation intermittence than precipitation intensity and temperature. Although there is variability in the soil moisture response to the considered forcing scenarios, increased temperature combined to increased precipitation intensity and intermittency leads to decreased median soil moisture and an increased number of dry days.

How to cite: Mimeau, L., Tramblay, Y., Brocca, L., Massari, C., Camici, S., and Finaud-Guyot, P.: Sensitivity of soil moisture to climate variability in the Mediterranean region, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-7214, https://doi.org/10.5194/egusphere-egu2020-7214, 2020.

Land-atmosphere feedbacks, in particular the response of land evaporation to vapour pressure deficit (VPD) or the dryness of the air, remain poorly understood. Here we investigate the VPD response by analysis of a large database of eddy-covariance flux observations and simulations using a conceptual model of the atmospheric boundary layer. Data analysis reveals that under high VPD, forest in particular reduces evaporation and emits more sensible heat. In contrast, grass increases evaporation and emits less sensible heat. Simulations show that this VPD feedback can induce significant temperature increases over forest of up to 2 K during heat wave conditions. It is inferred from the simulations that the effect of the VPD feedback corresponds to an apparent soil moisture depletion of more than 50%. This suggests that previous studies may have incorrectly attributed the effects of atmospheric aridity on temperature to soil dryness.

How to cite: Teuling, R., Lansu, E., van Heerwaarden, C., and Stegehuis, A.: Atmospheric aridity and apparent soil moisture drought in European forest during heatwaves, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-7281, https://doi.org/10.5194/egusphere-egu2020-7281, 2020.

Evaporation is a key flux in both Earth’s water and energy balances. It is largely controlled by the transport of water from the subsurface to the atmosphere, through the roots of vegetation. The water storage capacity in the rootzone is a key parameter in predicting evaporation fluxes in land surface models. Drought predictions are of particular interest because the size of the rootzone-storage-reservoir determines how long into the dry season vegetation is able to evaporate. Whereas climate is the major driver of root development, the storage in the rootzone in the HTESSEL land surface scheme is only dependent on soil type and model soil depth. Moreover, the model describes root parameters by tables based on observations of individual plants that do not represent ecosystem scales. This research analyses the effect of implementing rootzone water storage capacities estimated with catchment-scale mass balances, in the land surface model HTESSEL on water and energy fluxes for 15 Australian river catchments.

This study found that the storage capacity in the vegetation’s rootzone represented in HTESSEL is larger than the mass-balance derived estimates. This leads to an underestimation of river discharge and overestimation of evaporation fluxes by the model, with significantly larger errors in the dry season. Implementation of the climate-based rootzone storage estimates in the current HTESSEL scheme leads to small model improvements regarding long term mean discharge predictions, but larger improvements in dry season discharge predictions. Transpiration fluxes in the dry season are directly linked to the size of rootzone water storage reservoir. The results indicate that inadequate rootzone representation could result in errors in modelled discharge and evaporation fluxes in the land surface model HTESSEL.

This study shows that investigating uncertainties in the representation of the rootzone in the HTESSEL land surface model is paramount. Future research is required to improve the representation of the rootzone in climate models.

How to cite: van Oorschot, F., Alessandri, A., van der Ent, R., and Hrachowitz, M.: A study on implementing catchment-scale rootzone water storage capacities, derived from climatic parameters, in the HTESSEL land surface scheme, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-9530, https://doi.org/10.5194/egusphere-egu2020-9530, 2020.

Quantifying contributions of errors in model structure and model parameters to biases in a land surface model (LSM) is critical for model improvement, but has not been done systematically for many global land surface models. This paper investigates the uncertainties in the Noah with multiparameterization (Noah-MP) LSM with dynamic vegetation by examining the interactions between imperfect parameterization schemes (PSs) and improper parameter values (PVs). A number of Noah-MP physical ensemble simulations were conducted at 92 eddy flux sites to quantitatively assess the impacts of the PS uncertainties on model performance, and then the key parameters in the two combinations of schemes with significant differences were calibrated. The results show that five subprocesses—the surface exchange coefficient (SFC), soil moisture threshold, radiation transfer (RAD), runoff and groundwater, and surface resistance to evaporation—have the most significant influence on the performances of simulated sensible heat flux, latent heat flux, net absorbed radiation and gross primary productivity in the Noah-MP LSM with dynamic vegetation, and that the interaction between SFC and RAD contributed up to 80% of the variation in the model performance at some sites. It is also shown that tuning the PSs and optimizing the PVs should be jointly applied to reduce the errors in the Noah-MP LSM, although compared to tuning PSs, parameter optimization happens to make less robust model improvement. Finally, this study emphasizes that reducing the significant uncertainties in soil parameters and exploring the errors caused by missing physical features are crucial to improving LSMs with dynamic vegetation.

How to cite: Li, J. and Chen, F.: Quantifying contributions of uncertainties in physical parameterization schemes and model parameters to overall errors in Noah-MP land modeling using observations from eddy flux sites, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-12296, https://doi.org/10.5194/egusphere-egu2020-12296, 2020.

Drought is arguably the climate phenomenon that most strongly impacts societies worldwide, causing severe socioeconomic and ecologic damage. While models unanimously project an overall increase in aridity and drought occurrence in the future, observational evidence has so far been inconclusive. The discrepancies between the various drought definitions and drought indices has been a major factor contributing to our low confidence in observed dryness trends. In this study we investigate global trends in meteorological dry spells using a simple, unambiguous and intuitive diagnostic: the maximum annual number of consecutive dry days (CDDs). In contrast to popular drought indices, the number of CDDs is a direct measure of the duration of rainfall scarcity, easy to quantify based on rain data, free of parametrizations, and independent from other proxies.

Because the time-span of available satellite-based precipitation data records is constantly increasing, current products are becoming an alternative to in situ rain gauges for studying long-term trends. In particular, the Tropical Rainfall Measuring Mission (TRMM) has now been operational for over twenty years, thus offering a unique opportunity to analyse temporally-coherent, single-platform precipitation data. Here, we use TRMM3B42 3-hourly data for 1998–2018 to calculate and analyse changes in the maximum annual number of CDDs worldwide. The robustness of the identified relationships among observational products is tested using recently-compiled gauge and satellite precipitation data from the Frequent Rainfall Observations on GridS (FROGS) database.

The results reveal that almost 70% of the continental land monitored by TRMM has experienced an increase in duration of the longest annual dry period over the past 20 years, and in 20% of these regions trends are found to be significant (p < 0.01). Agreement among various observational products is regionally dependent. However, most of the data sets suggest that the signal largely originates, not from arid regions (which would support the dry–gets–drier paradigm), but from monsoon areas. Further analysis shows that the same areas experience clear increasing (decreasing) trends in rain seasonality (amount), suggesting a link to the monsoon circulation dynamics. A preliminary analysis confirms this connection and additionally points to the potentially important role of land feedbacks, revealing a tendency for later moisture build up and, hence, a monsoon onset after more prolonged dry seasons. Altogether, our findings emphasize the vulnerability of global monsoon regions to climate change. An increasing length of dry spells as we progress into the future might lead to devastating socioeconomic and ecologic consequences in these regions.

How to cite: Petrova, I. Y., Miralles, D. G., and Wouters, H.: Satellites reveal the strongest increase in duration of extreme dry periods in global monsoon regions, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-17938, https://doi.org/10.5194/egusphere-egu2020-17938, 2020.

 Summer weather in Europe has become more extreme in recent years. Several studies have focused on unraveling the influence that this extreme weather may have on ecosystem dynamics. However, traditional optical indices characterise the state of vegetation in terms of greenness or structure, but fail to capture short term impacts on vegetation activity caused by water or heat stress. Being a byproduct of photosynthesis, solar induced fluorescence (SIF) represents an exception, since its dynamics may reflect an integral of the environmental stressors that have immediate influence on ecosystem water, energy and carbon exchanges during droughts or heatwaves. Spaceborne datasets of SIF have not only been used to monitor crop photosynthetic activity and GPP at global scales, but also as a proxy of transpiration dynamics, or even biogenic volatile organic compound emissions. Additionally, numerous case studies have indicated the potential of using SIF for early drought detection and monitoring of ecosystem impacts. 

However, as with most earth science applications, the majority of previous studies rely on correlations or linear regressions to establish these cause–effect relationships, which implies that the actual drivers of drought and periods of vegetation stress remain largely unresolved.

Here we examine the underlying causality and interactions between vegetation activity (represented by changes in SIF) and potential environmental drivers of vegetation stress over Europe during the summer months. Using satellite observations of  photosynthetically active radiation (PAR) and the fraction of absorbed PAR (fPAR), the SIF signal is decomposed into the component that relates to fPAR and the component that relates to the fluorescence yield, which represent different physical and biochemical responses to vegetation stress. Using recently developed methods for causal inference applications in Earth science (https://causeme.uv.es/), the dynamics of SIF and its deconstructed components are evaluated against satellite observations of soil moisture, vapor pressure deficit and temperatures. Common causal relationships and dynamics are observed when grouping regions by aridity index and fractions of vegetation cover. Results help establish direct and indirect links of potential drivers of vegetation activity during periods of heat and water stress.

How to cite: Martens, B., Pagán, B., Maes, W., Gentine, P., and Miralles, D.: Drivers of vegetation activity during European summers: A causal inference approach applied to solar-induced fluorescence observations, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-20451, https://doi.org/10.5194/egusphere-egu2020-20451, 2020.

In recent years, Europe has seen hot summers and drought conditions occur with increasing intensity and frequency. Drought and soil water limitations impact on the carbon uptake and release of forests. This study investigates the effect of recent drought events on carbon dioxide exchange of the unmanaged deciduous old-growth forest at the Fluxnet site Hainich (DE-Hai) in the years 2018 and 2019 and compares them to the previous century drought of 2003. During the 2018 event the Hainich site was at the intensity maximum of the Middle European drought event. In combination with shallow soils with low water holding capacity, this lead to severe limitations of available soil water and therefore a to a reduction in carbon fluxes. Comparing the 2003, 2018 and 2019 drought years, we find that anomalies in the annual carbon balances are not only affected by the intensity of the drought events itself but most importantly by the seasonal timing and the balance between anomalies in the carbon uptake and release. 2018 saw a significant reduction in the annual carbon uptake of the forest due to a drought starting early in Spring and limiting fluxes from May and June onwards. Contrary, 2019 experienced a less severe drought, however, the reduction in the annual carbon uptake of about 40% in 2019 was even more extreme than in the previous year. We are able to explain differences between years by two factors: firstly, the uptake deficit during the Summer and Autumn of 2018 was partially compensated by a positive uptake anomaly in Spring and early Summer, and secondly, the severe soil water limitation during the summer of 2018 lead to a decrease of ecosystem respiration, likely dominated by a decrease in soil respiration. Contrary, 2019 saw neither of the two compensating effects and therefore experienced the strongest reduction in net annual carbon uptake of the three drought years investigated. The further development of the carbon sequestration potential of the forest will remain a relevant question given the likely frequent occurence of droughts in the future and the consequences of significant forest damage already observed in 2019.

How to cite: Siebicke, L., Moyano, F., and Knohl, A.: Drought impacts on the carbon uptake of an old-growth deciduous forest in Central Germany, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-19659, https://doi.org/10.5194/egusphere-egu2020-19659, 2020.

The impact of deforestation on climate is mostly pronounced through net carbon emissions (biogeochemical effects), leading to a global warming. However, deforestation also alters the water and energy cycles (biogeophysical effects), which can cause a local warming or cooling depending on the region. This can potentially offset or even exacerbate the initial global warming signal caused by the biogeochemical effect. The results of earth system models show a large spread on the magnitude of biogeophysical effects and can even vary on the sign of these impacts for some regions. Thus, uncovering the uncertainty related to the biogeophysical effect of deforestation is crucial, to better understand the potential of afforestation as a means for land-based climate mitigation.

We investigate the biogeophysical effects of deforestation on climate by conducting idealised deforestation experiments consisting of a 150-year simulation. Greenhouse gas forcing is held constant at present-day levels to disentangle between the climatic effects from land use and from those due to anthropogenic climate change. The experiment is conducted by three different Earth System Models (MPI-ESM, EC-EARTH and CESM) to quantify inter-model uncertainty and potentially uncover specific model biases.

A recently-developed checkerboard approach is applied to disentangle the local and non-local effect (i.e. remote impacts of deforestation due to changes in atmospheric dynamics) from deforestation (Winckler et al. 2019). This enables us to better determine the uncertainties across the models as well as to validate the local biogeophysical effects of deforestation using observational datasets. This is the first time that the checkerboard approach is applied on multi-model climate simulations and thus serves as a benchmark for the applicability of this approach.

References:

Winckler, J., Reick, C.H., Luyssaert, S., Cescatti, A., Stoy, P.C., Lejeune, Q., Raddatz, T., Chlond, A., Heidkamp, M., Pongratz, J., Different Response of surface temperature and air temperature to deforestation in climate models, Journal of Earth System Dynamics, doi: https://doi.org/10.5194/esd-2018-66

How to cite: De Hertog, S., Vanderkelen, I., Havermann, F., Guo, S., Pongratz, J., Manola, I., Coumou, D., Davin, E., Seneviratne, S., Lejeune, Q., Menke, I., Schleussner, C., and Thiery, W.: Local biogeophysical effects of deforestation, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-1248, https://doi.org/10.5194/egusphere-egu2020-1248, 2020.

  Many socioeconomic changes have occurred in East Asia in recent decades. Due to the economic structural change and economic growth, a large population has been concentrated in the cities, resulting in rapid urban expansion. Besides, the surrounding agricultural land for food resources has also expanded, and deforestation has also been active at the same time. These land use/land cover change (LULCC) significantly alter the energy properties of the land surface. Although land surface characteristics that have vigorous variability over time, it is common in a numerical model to treat the information as a static condition. In a numerical weather prediction model aiming at short-term forecasting, the ground characteristics without temporal change are valid; however, in the numerical climate model integrated over several decades, consideration of such variability is essential.
   In this study, we examine the impact of LULCC using the GRIMs (Global/Regional Integrated Model system), which covered regional climate simulation. Temporal change LULC over East Asia, especially cropland and urban, is constructed based on Land Use Harmonization data. Through the comparison of sensitivity experiments considered the LULCC overtime or not, it is confirmed that land surface effect on regional climate change over East Asia. 

How to cite: Byun, U.-Y. and Chang, E.-C.: Impact of land use land cover change on East Asia, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-20915, https://doi.org/10.5194/egusphere-egu2020-20915, 2020.

Snow cover properties have a large impact on the partitioning of surface energy fluxes and thereby on near-surface weather parameters. Snow schemes of intermediate complexity have been widely used for hydrological and climate studies, whereas their impact on typical weather forecast time-scales has received less attention. A new multi-layer snow scheme is implemented in the ECMWF Integrated Forecasting System (IFS) and its impact on snow and 2-metre temperature forecasts is evaluated. The new snow scheme is evaluated offline at well instrumented field sites and compared to the current single-layer scheme. The new scheme largely improves the representation of snow depth for most of the sites considered, reducing the root-mean-square-error averaged over all sites by more than 30%. The improvements are due to a better description of snow density in thick and cold snowpacks, but also due to an improved representation of sporadic melting episodes thanks to the inclusion of a thin top snow layer with a low thermal inertia. The evaluation of coupled 10-day weather forecasts shows an improved representation of snow depth at all lead times, demonstrating a positive impact at the global scale. Regarding the impact on weather parameters, the use of the multi-layer snow scheme improves the simulated daily minimum 2-metre temperature, by decreasing the positive bias and improving the amplitude of the diurnal cycle over snow-covered regions. The analysis indicates that a more realistic representation of snow processes is essential to improve the simulation of low temperature extremes at high latitudes, where snow is a key component of the climate system. The work also highlights that other errors in polar regions still need to be addressed, such as cloud radiative properties, despite the improvements in the responsiveness of snow-covered surfaces with respect to the atmospheric forcing.

How to cite: Arduini, G., Balsamo, G., Dutra, E., Day, J. J., Sandu, I., Boussetta, S., and Haiden, T.: Impact of a multi-layer snow scheme on near-surface weather forecasts, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-22247, https://doi.org/10.5194/egusphere-egu2020-22247, 2020.