CL4.1
Orals: Thu, 27 Apr | Room F1
Leaves are the main interface between terrestrial ecosystems and the atmosphere. They govern the exchange of carbon, water and energy between vegetation and the atmospheric boundary layer. They are the surface designed to capture light and transform it to sugars via photosynthesis, but they also regulate how much water they transpire through their stomata. Their colour, density and orientation will affect their albedo, which determines how much energy is reflected back to the atmosphere, while their overall configuration within the canopy structure can affect the roughness length of the surface.
When we manage landscapes, be it by planting crops or cutting down forests, we are typically changing the quantity and type of leaves covering the surface of the land. By doing so, we can modify the land-atmosphere interactions and thereby have an effect on the climate. For instance, a substantial local cooling effect could be attained by using cover crops in winter, especially with highly reflective chlorophyll deficient mutants. Increasing forest cover appears to lead to more cloud cover, which itself could affect albedo at the top of the atmosphere. But the amount of leaves in the landscape can further affect extremes.
Here I will illustrate how leaves affect land-atmosphere interactions in the context of extreme events with two studies. The first study looks at the known biophysical effect of land use change on local surface temperature, but extends it to explore its sensitivity across the globe during the extremes observed in 20 years of satellite remote sensing records. The second study shows how much getting leaves right matters within the reanalysis records of ERA5 and ERA5-Land, where prescribed seasonal cycles of leaf area index (LAI) lead to biases in modelling land surface temperature (LST), thereby underestimating the intensity of heat waves over Europe.
How to cite: Duveiller, G.: Leaves, land-atmosphere interactions and extremes, EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-9777, https://doi.org/10.5194/egusphere-egu23-9777, 2023.
The diurnal air temperature range (DTR) is strongly shaped by solar radiation but is modulated by hydrologic cycling through changes in atmospheric (clouds) and land-surface (evaporation) characteristics. Here, we aim to determine the distinct patterns in DTR over dry and wet periods and identify their respective controls. To do this, we develop a simple energy balance model that constrains the land-atmosphere exchange using the thermodynamic limit of maximum power. In this framework, we explicitly account for changes in radiative conditions due to clouds and changes in boundary layer heat storage associated with surface water limitation, both of which affect the maximum power limit. Using observations of radiative forcings and surface evaporation, our model predicts DTR reasonably well across 81 FLUXNET sites in North America, Europe, and Australia. We show that DTR is primarily shaped by the trade-off between the heat gain due to solar absorption and heat lost at the surface due to evaporation. Radiation remains a primary control on DTR over very dry and wet conditions where evaporation is either close to zero or limited by available energy. Over these regions, changes in DTR are strongly modulated by clouds which alters the radiative conditions. DTR becomes coupled to the land surface during the transition regime where changes in surface water availability directly control the evaporation rates. Over these regions, increased soil moisture results in more evaporation and reduced DTR. These responses were consistent in both, observations and maximum power estimates. We then apply our framework to quantify the response of DTR to global warming. Our model projects a decrease in DTR by 0.18K for a 1K rise in global temperature, which is consistent with the current observed response. Our findings imply that the predominant controls on DTR are set by clouds and evaporation as they directly modulate the diurnal heating of the lower atmosphere and can be further altered by increased greenhouse forcing.
How to cite: Ghausi, S. A., McColl, K., and Kleidon, A.: Determining the radiative and hydrologic controls on the diurnal air-temperature range using the thermodynamic limit of maximum power, EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-7721, https://doi.org/10.5194/egusphere-egu23-7721, 2023.
The land surface is a key source of predictability for forecasts at the subseasonal-to-seasonal (S2S; 2 weeks to 2 months) timescale, since variables such as root zone soil moisture and leaf area vary more slowly than the atmospheric state. Previous work has mostly focused on the predictability gained from realistic soil moisture initialisations. Considering observable land surface variables, vegetation shows more persistent changes than surface soil moisture following subseasonal rainfall events, and therefore has the potential to provide predictability at longer lead times. We therefore perform the first investigation of vegetation feedbacks onto near-surface air temperatures using global daily data, to ascertain in which regions and seasons these feedbacks can provide S2S predictability. We use daily datasets of Vegetation Optical Depth (VOD, from the VODCA X-band product) and 2m temperature (from ERA5) at 0.25° horizontal resolution, and compute lagged correlations to identify where spatial structures in VOD anomalies are associated with similar structure in 2m temperature anomalies. Using daily data allows us to investigate how the correlations decay as a function of lead time within the S2S timescale. At zero lag, water-limited regions exhibit negative correlations, indicating that an increase in vegetation water content is associated with increased evapotranspiration and reduced sensible heat, leading to cooler near-surface air temperatures. We find extensive regions in the semi-arid tropics and sub-tropics where at certain times of year VOD anomaly patterns are anti-correlated with temperature patterns 2 weeks ahead. These periods tend to occur outside of the wettest time of year. In some regions, e.g. southern Africa in MAM, predictability of temperature from VOD anomalies extends to lags of 30 days, suggesting that incorporating vegetation variability can improve S2S forecasting. We develop a model for the strength and persistence of vegetation feedbacks to near-surface temperatures based on seasonal cycles of rainfall and vegetation.
How to cite: Taylor, C. and Harris, B.: Global observations highlight regions where vegetation can enhance S2S predictability, EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-15403, https://doi.org/10.5194/egusphere-egu23-15403, 2023.
Hot temperature extremes are changing in intensity and frequency. Quantifying these changes is key for developing adaptation and mitigation strategies. The conventional approach to study changes in hot extremes is based on air temperatures. However, many biogeochemical processes, i.e. decomposition of organic material and release of CO2, are triggered by soil temperature and it remains unclear whether it changes as does air temperature. Here, we demonstrate that soil hot extremes are intensifying and becoming even more frequent faster than air hot extremes over central eastern and western Europe. Based on existing model simulations, we also show that the increase in hot soil extremes could amplify or spread future heat waves by releasing sensible heat during hot days. We find an increase of 3 (7) % in the number of hot days with a contribution of heat from the soil under a warming level of 2.0 (3.0) °C than under a warming level of 1.5 °C. Furthermore, defining intensity and frequency extreme indices based on soil and air temperatures leads to a difference of more than 1 °C in intensity and 10% in frequency regionally during the last decades of the 21st century under the SPP5 8.5 emission scenario. In light of these results, maximum soil temperatures should be included in ecological risk studies as a complementary perspective to the conventional approach using extreme indices based on air temperatures.
How to cite: García-García, A., Cuesta-Valero, F. J., Miralles, D. G., Mahecha, M. D., Quaas, J., Reichstein, M., Zscheischler, J., and Peng, J.: Soil Hot Extremes are Increasing Faster than Air Hot Extremes Regionally, EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-5961, https://doi.org/10.5194/egusphere-egu23-5961, 2023.
Terrestrial vegetation is largely mediated by vegetation-climate coupling. Growing conditions control vegetation growth, which in turn feeds back to climate through changes in biophysical and biogeochemical properties and processes, such as canopy structure and carbon and water exchanges. The vegetation-climate coupling is thus highly variable in space and time. However, little is known on how the large-scale vegetation-climate coupling varies within growing season, and how vegetation responds to climate extremes. In this contribution, we present some recent findings on seasonal and intra-seasonal vegetation-climate coupling and vegetation sensitivity to droughts using multiple remote sensing products including MODIS EVI, GIMMS3g NDVI and VIP EVI2. We account for the differences in phenological stages of growing seasons affected by both climate and landscape heterogeneity. Based on a novel analytical framework incorporating meteorological and vegetation conditions to locally defined vegetation growing seasons, we analyse vegetation-climate couplings using both local climate conditions and teleconnection indices (e.g., Jet Latitude Index). In addition, vegetation sensitivity to droughts and post-drought vegetation changes are assessed. Our results highlight the importance of considering vegetation phenology in understanding sub-seasonal land-atmosphere interaction and vegetation dynamics. The developed analytical framework is suggested to be an effective approach for evaluating vegetation and climate dynamics simulated by Earth System Models.
How to cite: Wu, M., Messori, G., Vico, G., Manzoni, S., Cai, Z., Tang, J., Tagesson, T., and Duan, Z.: Vegetation-climate coupling and vegetation sensitivity to climate extremes in growing seasons, EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-9838, https://doi.org/10.5194/egusphere-egu23-9838, 2023.
Transpiration (T), the component of evaporation (E) controlled by vegetation, dominates terrestrial Evaporation, but measurements are highly uncertain. In the light of the importance of evaporation for studying the terrestrial water cycle, hydro-climatic extremes such as droughts and heatwaves and land-atmospheric interactions, there is a strong demand on novel approaches to reliably estimate T. Currently available approaches to estimate T mostly rely on its relationship with photosynthesis, but parameterizing this relationship is difficult and estimates of T strongly disagree among each other in terms of magnitude. Moreover, in-situ measurements are scarce and and evaporation cannot be measured directly from space.
We developed a hybrid Priestley-Taylor (PT) model using Deep Learning to learn the relationship between T and state variables such as soil moisture, vapor pressure deficit and the fraction of photosynthetic active radiation for different plant functional types (PFTs). We use globally available variables from reanalysis and remote sensing data as forcing to train an artificial neural network on the PT-coefficient α obtained by inverting the PT model on sap flow based ecosystem T. In this way, we can predict Transpiration at local scales independently from hard-to-obtain fluxes like E or vegetation parameters such as stomatal conductance. We evaluate our algorithm against T estimates from flux partitioning methods based on water use efficiency at eddy covariance sites for different PFTs and regions. Also, we compare our estimates with other available products of transpiration like GLEAM, PML-V2 and ERA5-Land. Preliminary results of this research showed that the developed model can learn the relationship between T and few influencing variables, without incorporating variables such as net radiation or GPP. Our findings contribute to dissolving the scarcity of T estimates in forest ecosystems based on actual observations. Future work is needed to apply our method to the larger scale for studying spatial patterns of T, e.g. across the European continent.
How to cite: Hannemann, M., García-García, A., and Peng, J.: Transpiration in forest ecosystems based on deep learning and sap flow observations, EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-14104, https://doi.org/10.5194/egusphere-egu23-14104, 2023.
Climate model predictions of land hydroclimate changes show large geographic heterogeneity, and differences between models are large. We introduce a new process-oriented phase space that reduces the dimensionality of the problem but preserves (and emphasizes) the mechanistic relations between variables. This transform from geographical space to climatological aridity index (AI) and daily soil moisture (SM) percentiles allows for interpretation of local, daily mechanistic relations between the key hydroclimatic variables in the context of time-mean and/or global-mean energetic constraints and the wet-get-wetter/dry-get-drier paradigm. Focusing on the tropics (30S-30N), we show that simulations from 16 different CMIP models exhibit coherent patterns of change in the AI/SM phase space that are aligned with the established soil-moisture/evapotranspiration regimes. Results indicate the need to introduce an active-rain regime as a special case of the energy-limited regime. In response to CO2-induced warming, rainfall only increases in this regime, and this temporal rainfall repartitioning is reflected in an overall decrease in soil moisture. Consequently, the regimes where SM constrains evapotranspiration become more frequently occupied, and hydroclimatic changes align with the position of the critical soil moisture value in the AI/SM phase space. Analysis of land hydroclimate changes in CMIP6 historical simulations in the AI/SM phase space reveal the very different impact of CO2 forcing and aerosol forcing. CESM2 Single Forcing Large Ensemble Experiments are used to understand their roles.
How to cite: Duan, S., Findell, K., and Fueglistaler, S.: Mechanistic patterns of land hydroclimate changes in a changing climate, EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-10118, https://doi.org/10.5194/egusphere-egu23-10118, 2023.
Large-scale anthropogenic revegetation has considerable climate, carbon, and ecosystem benefits by affecting ecohydrological and hydrometeorological processes. Previous studies have pointed out that large-scale vegetation restoration in non-humid areas significantly increases evapotranspiration (ET), resulting in the reduction of soil moisture and streamflow. However, the impact of vegetation-climate feedback on water balance was ignored in these studies. The Loess Plateau (LP) in China has the largest vegetation restoration area in the world since 1999. Here, we combined in-situ hydro-meteorological observation and coupled land-atmosphere model to analyze how vegetation reconstruction affects the water resource budget of the LP. Two simulation experiments were designed to achieve a quantitative evaluation, including a real scenario that reflects the actual vegetation restoration, and a hypothetical scenario without vegetation restoration. The net impact of vegetation restoration on local precipitation can be analyzed by comparing the two scenarios. We quantified the feedback effect of vegetation restoration on local precipitation and the underlying mechanisms. The observation results show that precipitation increased on the LP after the restoration, and the surface water production in most areas on the LP (82.3%) shows a strong robust growth trend (2.76 mm yr-2), although the ET has increased at the same time. Our simulations show that the annual average precipitation under the vegetation restoration scenario on the Loess Plateau is 12.4% higher than the non-vegetation restoration scenario. We found the enhancement of land-atmosphere interaction is a main reason for the rapid growth of precipitation. Such an enhancement is caused by vegetation restoration that greatly accelerates the local water cycle. The contribution of large-scale vegetation restoration to precipitation increase is about 37.4%. Our research emphasizes the importance of considering vegetation-climate feedback when assessing the impact of large-scale vegetation restoration and will provide guidance and theoretical support for ecological protection and sustainable vegetation restoration in water-scarce regions.
How to cite: Zhang, B. and Tian, L.: Feedbacks between large-scale vegetation restoration and regional precipitation over the Chinese Loess Plateau, EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-7219, https://doi.org/10.5194/egusphere-egu23-7219, 2023.
The response of vegetation canopy conductance (gc) to changes in moisture availability (ϒgc) during drought is a major source of uncertainty in climate projections. Representing ϒgc accurately in Earth System Models (ESMs) is particularly problematic because no regional scale gc observations exist with which to evaluate it. Here, we overcome this challenge by deriving an emergent constraint on ϒgc across ESMs from Phase 6 of the Coupled Model Intercomparison Project (CMIP6). We leverage an ensemble of satellite, reanalysis and station-based estimates of surface temperatures, which are physically and statistically linked to ϒgc due to the local cooling effect of gc. We find that models systemically underestimate ϒgc by ~50%, particularly in semi-arid grasslands, croplands, and savannas. Based on the mediating effect of gc on carbon, water and energy fluxes through land-atmosphere interactions, the underestimation of modeled ϒgc in these regions contributes to biases in temperature, transpiration and gross primary production. Our results provide a novel benchmark to improve model representation of vegetation dynamics and land-atmosphere feedbacks in these regions, thus improving forecasting ability of climate extremes under future climate change scenarios.
How to cite: Green, J. K., Zhang, Y., Luo, X., and Keenan, T.: An emergent constraint exposes widespread underestimation of drought impacts by Earth System Models, EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-9421, https://doi.org/10.5194/egusphere-egu23-9421, 2023.
This work presents the first observationally-based study over subtropical South America linking the spatial location of convection and drier soil patches of the order of tens of kilometers, as well as observational evidence of the control of background flow on the sign of SM-PPT feedbacks at convective scales. Using satellite data from multiple infrared and microwave radiometers, we track nascent, daytime convective clouds over subtropical South America and quantify the underlying, antecedent (morning), SM heterogeneity. We find that convection initiates preferentially on the dry side of strong dry-wet SM boundaries that are associated with spatially drier and warmer patches of tens of kilometers scale consistent with findings in other parts of the world. This preference maximizes during weak background low-level wind, high convective available potential energy, low convective inhibition and low vegetation density when analyzing surface gradients of 30 km length scale. On the other hand, surface gradients of 100 km length scale are significantly associated with afternoon convection during convectively unfavorable synoptic conditions and strong background flow, unlike previous studies. The location of the precipitation maxima following CI onset is most sensitive to the lower tropospheric background flow at the time of CI. The wind profile during weak background flow does not support propagation of convective features away from the dry regions and rainfall accumulates over the dry patch. Convection during strong background flow leads to greater rainfall hundreds of kilometers away from the CI location.
How to cite: Dominguez, F., Chug, D., Taylor, C., Klein, C., and Nesbitt, S.: Mesoscale Gradients in Soil Moisture over South America Lead to Enhanced Convection, EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-11538, https://doi.org/10.5194/egusphere-egu23-11538, 2023.
The land surface supplies heat and moisture to the atmosphere influencing the regional climate during the convective season. Availability of soil moisture for evapotranspiration, vegetation phenology and atmospheric conditions influence the strength of the land surface impact on the atmosphere, and the mechanisms predominating the heat and moisture exchange. As both the synoptic conditions as well as the vegetation state vary on sub-seasonal to interannual time scales, the strength of land-atmosphere (L-A) interaction is expected to fluctuate on these time scales.
Up to now, research typically either focuses on case studies to understand the mechanisms of how land surface and atmosphere interact, or on climatic time scales to quantify co-variances in the climate system based on a sufficient sample size. Timescales in between remain rarely considered in land-atmosphere feedback studies.
In our study, we applied various L-A coupling measures to evaluate land surface impacts on the atmosphere and quantify interactions associated with the triggering of convective precipitation and droughts for all summers between 1991 and 2022 over Europe based on ERA5 data.
Our results highlight that differently strong L-A interactions evolve in dependence of atmospheric wetness, temperature, and the circulation pattern, as well as the root zone soil moisture and vegetation cover. Under warm and dry conditions such as in 2003, 2018 and 2022, soil moisture availability imposed limits for evapotranspiration not only in Southern Europe, but also in Central and Eastern Europe, interfering with vegetation growth and atmospheric moisture supply. Limited moisture and excessive heat supply amplified the already high temperatures and low near-surface moisture, which finally aggravated the unfavorable conditions for local precipitation and caused extreme drought conditions. On the contrary, warm and wet conditions such as in 2021 provided well-suited conditions for vegetation growth, which enhanced the moisture supply to the atmosphere. Together with stronger atmospheric instability, this provided more favorable preconditions for convective precipitation. Generally, most L-A interactions perform as an intensifier of persisting anomalies, particularly under warm and dry atmospheric conditions over Europe.
How to cite: Jach, L., Schwitalla, T., Wulfmeyer, V., and Warrach-Sagi, K.: Interannual Variation of Land-Atmosphere Interactions and their Connection with Extremes over Europe, EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-12925, https://doi.org/10.5194/egusphere-egu23-12925, 2023.
China has shown a world-leading vegetation greening trend since 2000, which may exert biophysical effects on near-surface air temperature (SAT). However, such effects remain largely unknown because prior studies either focus on land surface temperature, which differs from SAT, or rely on simulations, which are limited by model uncertainties. As a widely used metric in climate and extremes research, SAT is more relevant to human health and terrestrial ecosystem functions. Therefore, it is necessary to explore impacts of greening on SAT and extremes based on observations. Here, we investigate the greening effects on SAT and subsequent extremes over 2003–2014 in China based on high-resolution SAT observations combined with satellite datasets. We find that greening can cause cooling effects on the mean SAT and more pronounced cooling effects on SAT extremes over semiarid regions. Such cooling effects are attributed to enhanced evapotranspiration caused by greening and strong coupling between evapotranspiration and SAT in semiarid regions. Semiarid regions in China are the transitional zone of both climate and ecosystem and deeply influenced by human agricultural and pastoral activities. These factors make the ecosystem of these regions fragile and extremely vulnerable to climate change. Our results reveal a considerable climate benefit of greening to natural and human systems in semiarid regions, and have significant implications for on-going revegetation programs implemented in these regions of China.
How to cite: Cao, Y., Guo, W., Ge, J., Liu, Y., Chen, C., Luo, X., and Yang, L.: Greening vegetation alleviates hot extremes in the semiarid region of China, EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-3780, https://doi.org/10.5194/egusphere-egu23-3780, 2023.
Numerous cyclones develop in the Bay of Bengal during the pre-monsoon and post-monsoon seasons. The heavy rain associated with these cyclones causes devastating damage to life and property during landfall. The modern numerical weather prediction models and high temporal satellite observation data have significantly increased the accuracy of cyclone prediction in recent years. However, accurately predicting rainfall intensity and its dissipation after landfall is still challenging. Previous studies have indicated that land-based evapotranspiration plays an essential role in determining the intensity and decay of cyclones post-landfall. In this study, we quantify the contribution of land-based evapotranspiration to the rainfall associated with cyclones and the impact of land conditions on the speed and track of cyclones originating in the Bay of Bengal. For this purpose, we employed the Weather Research Forecasting (WRF) model upgraded with Eulerian water tagging capabilities to track evapotranspiration from land. The tagging model will tag the evapotranspiration originating on land and track it throughout the atmosphere till it precipitates or moves out of the domain. We simulated six cyclones of varying intensities, with three during the pre and three during the post-monsoon seasons. We conducted sensitivity experiments with dry and wet initial soil moisture conditions to determine the impact of perturbed soil moisture on TC. To account for the model's internal variability, we simulated an ensemble with four members for the control simulation. The ensemble is created by changing each member's model initialization time by six hours. This ensemble helped identify the magnitude of the model's internal variability, which was less than the variability due to soil moisture changes. The study revealed that soil moisture conditions prior to TC formation have an impact on its evolution. By analyzing the latent heat, temperature, and wind pattern, we found that the initial soil moisture during the pre and post-monsoon seasons alters the synoptic features over the Indian subcontinent, resulting in variations in the TC evolution. The relatively low-intensity TC tracks are more sensitive to the initial soil moisture conditions. The rainfall originating from land-based evapotranspiration is more significant as the cyclone approaches land. Therefore, land-based evapotranspiration plays a crucial role in the end phase of the cyclone (from just before landfall till its decay). For post-monsoon cyclones, the rainfall from land-based evapotranspiration is as high as 20% to 30% after landfall, whereas, for pre-monsoon cyclones, the land contribution is around 5% to 10%. In addition to soil moisture, factors such as proximity to land, track length over land, and TC intensity also have a role in determining the quantity of precipitation originating from the land for a TC.
How to cite: Lanka, K. and Navale, A.: Influence of Soil Moisture on the Evolution of Landfalling Tropical Cyclones during pre and post-monsoon seasons, EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-15299, https://doi.org/10.5194/egusphere-egu23-15299, 2023.
Since late 1980s, warming trend intensifies strongly over Western Europe, resulting in an abrupt shift in air surface temperature over France (Sutton & Dong 2012; Reid et al., 2016). This rapid warming has modified the hydrological cycle with especially a significant decrease in runoff between January and July (Brulebois et al., 2015). As cumulative annual liquid precipitation didn’t significantly evolve after 1987/1988, evapotranspiration might be the main driver of the water cycle evolution.
Along with this abrupt warming, stagnation of crop yields is observed since the 1990s over France, especially for bread wheat (Schauberger et al., 2018). In addition to maize and grapevine, the impact of climate hazard and agro-climatic risk linked to water cycle on the evolution of bread wheat yields is a major issue for agricultural insurance companies (Fusco et al., 2018). In this context, two major concerns need to be assessed: what are the patterns of water balance responses to abrupt changes in temperature? How did this abrupt warming impact drought risk over crops of interest main production basins?
SIM (Safran-Isba-Modcou) dataset of reanalyzed surface meteorological observations offers the opportunity to address the complexity of processes leading to changes in local water cycle (Soubeyroux et al., 2008). Daily liquid precipitation and potential evapotranspiration on an 8km spatial resolution from 1959 to 2021 are used to quantify the evolution of climate hazard linked to water cycle on a continuous time-scale and over the entire French territory. A simplified two reservoirs water balance model is also used to compute daily water balance using agronomic parameters of crops of interest, taking into account crop cover stage (Jacquart & Choisnel, 1995). The evolution of frequency and intensity of drought risk is analyzed using Tweedie distributions (Dunn, 2004).
Our results suggest that the abrupt warming in air temperature in 1987/1988 had strong influence on water balance evolution. Potential evapotranspiration significantly increases after 1987/1988 over the whole French territory especially in spring and summer. The evolution of annual and seasonal cumulative liquid precipitation differs in space and time and is less pronounced, leading to an intensification of water cycle. Water balance displays various evolutions depending on the crop and the production basin studied. The exceeding of water stress threshold is more frequent or more pronounced, leading to modifications of intensity and/or duration of drought events that significantly modify the risk. Risk evolution depends on the crop cover and main production basin.
Evolving climate hazard linked to water cycle impacts agro-climatic risks, identified as one of the main factor affecting the evolution of crop yields. Both mean conditions changes and modifications of the spatio-temporal variability of water balance affect the probability to overcome risk threshold. This is of major concern for the agricultural sector, especially insurance companies, and may lead to adaptation process from managers.
How to cite: Laurent, L., Ullmann, A., and Castel, T.: Abrupt late 1980s surface climate warming effects on drought risk over main french crop production basins, EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-5624, https://doi.org/10.5194/egusphere-egu23-5624, 2023.
Heavy precipitation (HP) events can be preceded by moist heatwaves (HWs; i.e., hot and humid weather), and both can be intensified by urbanization. However, the effect of moist HWs on increasing urban HP remains unknown. Based on statistical analyses of daily weather observations and ERA5 reanalysis data, we investigate the effect of moist HWs on urban-intensified HP by dividing summer HP events into NoHW- and HW-preceded events in the Yangtze River delta (YRD) urban agglomeration of China. During the period 1961–2019, the YRD has experienced more frequent, longer-lasting, and stronger intense HP events in the summer season (i.e., June–August), and urbanization has contributed to these increases (by 22.66%–37.50%). In contrast, urban effects on HP are almost absent if we remove HW-preceded HP events from all HP events. Our results show that urbanization-induced increases in HP are associated with, and magnified by, moist HWs in urban areas of the YRD region. Moist HWs are conducive to an unstable atmosphere and stormy weather, and they also enhance urban heat island intensity, driving increases in HP over urban areas.
How to cite: Gu, X., Li, C., and Slater, L.: Urbanization-Induced Increases in Heavy Precipitation are Magnified by Moist Heatwaves in an Urban Agglomeration of East China, EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-1814, https://doi.org/10.5194/egusphere-egu23-1814, 2023.
Plant roots act as critical pathways of moisture from subsurface sources to the atmosphere. Moreover, deep plant roots allow vegetation to meet water demand during seasonally dry periods by taking up moisture from accessible groundwater. This is an important resilience mechanism in the Amazon, a hydrologically and ecologically significant region. However, most regional land-atmosphere computational models do not adequately capture the link between deep roots and groundwater. This study details the implementation of a dynamic rooting scheme in the Noah-Multiparameterization (Noah-MP) land surface model, a widely used tool for studying the exchange of energy and moisture between the land and atmosphere. The rooting scheme is a first-order representation of dynamic rooting depth based on the soil water profile and includes quantification of deep root water uptake (RWU). The scheme is easily scalable and ideal for regional or continental-scale climate simulations. It is used in conjunction with a groundwater scheme which captures high-resolution spatial groundwater variations, allowing us to capture the critical link between deep roots and groundwater. We perform 10-year simulations with and without the root scheme for a test region in the Amazon to validate the enhanced model. We analyze time series of soil moisture, RWU, and evapotranspiration for points with differing vegetation cover and elevation. This allows us to demonstrate functionality of the root scheme and ensure it behaves properly for varying conditions. Representation of deep RWU is critical for realistic simulation of the soil-plant-atmosphere system. As the land surface is an important component of atmospheric predictability, inclusion of deep RWU can contribute to improved prediction of atmospheric variables such as precipitation.
How to cite: Bieri, C., Dominguez, F., Miguez-Macho, G., and Fan, Y.: Exploring deep root water uptake, soil moisture, and land surface fluxes in the Amazon, EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-16444, https://doi.org/10.5194/egusphere-egu23-16444, 2023.
Summer 2022 has been the second hottest summer after 2003 in France since 1900, with 33 cumulative days of heatwaves. It has also been one of the 10 driest summers in France since 1959. The average precipitation deficit reached 20% compared to the 1991-2020 period, exceeding 60% in some regions, even though June 2022 broke the monthly record of storm occurrences.
These extreme climate conditions led to water restrictions and fostered the development of many wildfires. In particular, so called “megafires” burnt more than 28,000 hectares of the Landes forest in the Nouvelle-Aquitaine region, in the South-West of France.
Starting from the 18th century, this swampy region has been dried out by planting maritime pines and digging ditches to drain away excess water. Due to recent events, these land management practices are questioned : the record-breaking soil dryness of summer 2022 enabled fire to propagate underground and resurface further away, making firemen’s work extremely difficult.
By controlling ditch drainage, is it possible to reduce soil dryness and thus fire risk in summer, as well as mitigate heavy precipitation impacts in this flood prone area ? To answer this question, this work first aims at characterizing and interpreting local climate evolution during the last decades, in terms of trends, changes in the seasonal cycle and extreme events, using ERA 5 reanalysis, the E-Obs dataset, and MODIS satellite observations. CORDEX regional climate projections are also analysed. Nouvelle-Aquitaine will experience both more frequent and intense heatwaves and droughts and an increase in heavy precipitations. Landes forest management thus has to be adapted.
The perspective of this work is to develop a conceptual ditch drainage model and quantify the drought and flood risk reduction potential using storylines based on plausible short and long term climate conditions in Nouvelle-Aquitaine.
In a broader perspective, the objective of this work is to develop a methodology replicable in other regions of the world to analyse the impacts of climate change at a local scale and explore how climate science can provide quantitative information to help decision making.
How to cite: Lanet, M., Li, L., and Le Treut, H.: Characterisation and interpretation of local climate evolution in the South-West of France, EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-3211, https://doi.org/10.5194/egusphere-egu23-3211, 2023.
Posters on site: Fri, 28 Apr, 16:15–18:00 | Hall X5
Abstract:
The interaction of land cover and atmosphere can affect the climate patterns via biogeochemical and biogeophysical process. The afforestation contributes to increase the biogeochemical cycles like carbon sequestration. Meanwhile, the landcover change modify the biogeophysical parameters perturbs the energy and water fluxes. The latter will be the most direct process to affect the atmosphere and its effects from landcover change outweigh radiative forcing triggered off by CO2 emissions.
After the “Grain to Green Program”, the Loess Plateau (LP) has experienced a widespread forest expansion. Up to 2012, the extension of forest area in the central LP (Ningxia, Shanxi, and Shaanxi) accounted for 11.2 % of the area of the three provinces. The greening trend has changed the energy and water cycle, hence to a climate variability. The moist heat stress (a combined climate metric) has been recently investigated because it is directly related to human health. However, the affection of afforestation to moist heat stress is still unclear in LP.
In a recent study, we used the Weather Research and Forecasting (WRF) model to simulate the modulation of moist heat in LP caused by the afforestation. The result demonstrates that the intensive revegetation in LP shows a cooling effect on regional average near surface air temperature, especially in central LP. In addition, an increase of relative humidity caused by afforestation is detected. Driving by the near-surface temperature, sensible heat flux, and the subsidence of the planetary boundary layer the moist heat stress has obvious change after afforestation. The average moist heat stress decreases in central LP. While the decrease rate of moist heat stress is slower than near-surface temperature. It is worth noting that, an increased signal occurs in the maximum moist heat stress which might expose humans to the risk of moist heat stress. Our sensitivity results imply that the moist heat stress should be accounted for in climate change adaptation.
In ongoing work, we study the role of atmospheric VPD on mitigating land-atmosphere feedbacks over forest and non-forest land cover based on a global analysis of FLUXNET data. Preliminary results show a strong climate control on the effect of VPD on land-atmosphere exchange, in particular during heatwaves.
Reference: Zhang, S., Wang, W., Teuling, A. J., Liu, G., Ayantobo, O. O., Fu, J., & Dong, Q. (2022). The effect of afforestation on moist heat stress in Loess Plateau, China. Journal of Hydrology: Regional Studies, 44, 101209
How to cite: Zhang, S., Wang, W., and Teuling, A. J.: The role of atmospheric humidity in controlling land-atmosphere feedbacks over forest: regional and global-scale analyses, EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-799, https://doi.org/10.5194/egusphere-egu23-799, 2023.
In recent years, drought has become an increasing problem in agricultural production in many places where these problems did not exist in the past. The frequency and intensity of agricultural droughts are increasing, so it is very important to detect temporal and spatial variability of drought. This study analyzed the properties of agricultural drought (duration and intensity) in Bărăgan region (Romania) and Prekmurje region (Slovenia) between 1991-2020 based on the Standardized Precipitation Index (SPI) and the Standardized Precipitation Evapotranspiration Index (SPEI) at different time scales. The reasons for comparing the two regions are similar climatic conditions, the importance of maize cultivation for food security, and repeated droughts in the recent period in these regions. The meteorological data for Romania were provided from ROCADA database, and for Slovenia from SLOCLIM database. Furthermore, relationships between drought-sensitive phenological stages of maize (germination, formation of the first 2 leaves, and flowering), growing season length, thermal time above threshold 10 °C, standardized yields, and calculated drought indicators were calculated. Based on our analysis, we expect to be able to evaluate whether SPI and SPEI can be used to monitor conditions on a variety of time scales and to provide indicators at regional scales on the likely occurrence of drought during critical phenological phases of maize, as well as the differences and similarities between the two regions will be discussed.
How to cite: Kobulniczky, B., Holobâcă, I.-H., Črepinšek, Z., Pogačar, T., Jiman, A.-M., and Žnidaršič, Z.: Comparison of Standardized Precipitation Index (SPI) and Standardized Potential Evapotranspiration Index (SPEI) applicability for drought assessment during the maize growing period between Bărăgan (Romania) and Prekmurje (Slovenia) regions (1991, EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-499, https://doi.org/10.5194/egusphere-egu23-499, 2023.
The surface-air temperature difference (Ts-Ta) is the main contributor to the sensible heat flux, and also an important indicator for land degradation. However, as the main influencing factor, the effect of soil moisture (SM) on Ts-Ta at the global scale has not been well articulated. Here, based on the ERA5-land reanalysis data from 1981 to 2019, the impacts of SM on Ts-Ta were studied. It was found that Ts-Ta over 54% of the global land increased, and SM across 70.7% of the world land decreased. In the increased SM areas, the increased soil evaporation weakened the increasing trend of Ts resulting in smaller Ts-Ta. In the decreased SM areas, the latent heat flux increased with soil evaporation and Ts-Ta decreased when SM was relatively high, and the larger sensible heat flux due to decreased soil evaporation aggravated Ts-Ta when SM was relatively low. The effect of SM on Ts-Ta presented nonlinear relationship due to the different background value of SM and temperature. The variation of SM at low SM or low temperature areas had an amplification effect on Ts-Ta. These findings will provide new insights into the different regional characteristics of global changing climate and the improvement of land degradation assessment indicators.
How to cite: jiang, K.: Influence patterns of soil moisture change on surface-air temperaturedifference under different climatic background , EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-557, https://doi.org/10.5194/egusphere-egu23-557, 2023.
The EC-Earth earth system model is characterized by biases in various aspects of the simulated climate. Biases in precipitation result in biases in soil moisture, while biases in temperature and precipitation contribute to biases in vegetation. In this study, the extent to which the biases in soil moisture and vegetation contribute to the biases in the surface energy fluxes (which, in turn, lead to near-surface climate biases) in EC-Earth through interactions with the atmosphere is investigated.
The study is based on two simulations for the recent period 19719-2017: an offline simulation with the land-surface component of EC-Earth, combining the HTESSEL land surface model and the LPJ-GUESS dynamical vegetation model forced, by the meteorological conditions from the ERA5 re-analyses, and a simulation with the atmospheric version of EC-Earth, where the land-surface conditions, i.e., soil moisture and vegetation, are prescribed from the offline simulation.
The purpose of the study is twofold: By comparing the offline simulation with the land-surface component of EC-Earth with observational estimates of the surface energy fluxes, it is investigated to which extent the land-surface component, combing HTESSEL and LPJ-GUESS, is capable to simulate the surface energy fluxes under “perfect” climate conditions. And by comparing the simulation with the atmospheric component of EC-Earth with the offline simulation, the effects of the land-surface atmosphere interactions on the biases of the surface energy fluxes in EC-Earth are assessed. These effects are, to a large extent, related to climate biases in the atmospheric component of EC-Earth, e.g., the radiative fluxes, precipitation or the near-surface climate conditions.
How to cite: May, W.: The role of land-surface interactions for the surface energy fluxes in the EC-Earth earth system model , EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-1067, https://doi.org/10.5194/egusphere-egu23-1067, 2023.
Climate change has significant implications for macro-economic growth. The impacts of greenhouse gases and anthropogenic aerosols on economies via altered annual mean temperature (AMT) have been studied. However, the economic impact of land-use and land-cover change (LULCC) is still unknown because it has both biogeochemical and biogeophysical impacts on temperature and the latter differs in latitudes and disturbed land surface types. In this work, based on multi-model simulations from the Coupled Model Intercomparison Project Phase 6, contrasting influences of biogeochemical and biogeophysical impacts of historical (1850–2014) LULCC on economies are found. Their combined effects on AMT result in warming in most countries, which harms developing economies in warm climates but benefits developed economies in cold climates. Thus, global economic inequality is increased. Besides the increased AMT by the combined effects, day-to-day temperature variability is enhanced in developing economies but reduced in developed economies, which further deteriorates global economic inequality.
How to cite: Liu, S., Wang, Y., Zhang, G., Wei, L., Wang, B., and Yu, L.: Contrasting influences of biogeophysical and biogeochemical impacts of historical land use on global economic inequality, EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-1689, https://doi.org/10.5194/egusphere-egu23-1689, 2023.
Information about the energy and water exchanges between the land surface and the lower atmosphere (i.e. land-atmosphere interactions) is necessary for example to improve our understanding of the effect of land-atmosphere interactions on the exacerbation of temperature and precipitation extremes. Observations of energy and water fluxes at the land surface usually rely on the eddy covariance method. There is a wide network of these measurements providing data over all continents but with large spatial gaps in Africa, Asia, South America and Oceania. Additionally, other problems are associated with these observational methods such as the energy and water balance non-closure. To improve the spatial coverage of land-atmosphere interactions data considering the energy and water balance closure, we explore the combination of remote sensing data and a physical-based model. The High resOlution Land Atmosphere Parameters from Space (HOLAPS) framework is a one dimensional modelling framework that solves the energy and water balance at the land surface using remote sensing data and reanalysis products as forcings. Preliminary results from the evaluation ofHOLAPS outputs over Europe at 5 km resolution show an improvement in the simulation of latent heat flux when using remote sensing data in comparison with results using only reanalysis data as forcing. Additionally, we see a moderate improvement in HOLAPS latent heat flux estimates against energy-balance corrected eddy covariance measurements in comparison with other products that solve the energy and water balance equations, such as the ERA5Land product. The new HOLAPS product is available at hourly resolution for the period 2001 to 2016 and these estimates can be useful for agriculture and forest management activities and to evaluate the representation of land-atmosphere feedbacks in weather and climate models.
How to cite: Peng, J. and García-García, A.: A new satellite-based product for studying land-atmosphere interactions, EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-2078, https://doi.org/10.5194/egusphere-egu23-2078, 2023.
Global climate change with a predicted increase in weather extremes entails vulnerability and new challenges to regional agriculture. While the general impacts of climate change on global food security are a much studied topic, the implications for regional inter-annual yield variability remain unclear. In this study, we analysed the effects of weather trends on regional crop productivity within two agriculturally managed regions in different climate zones, simulated with the latest version of the Community Land Model (version 5.0) over two decades (1999-2019). We evaluated the models’ potential to represent the inter-annual variability of crop yield in comparison to recorded yield variability and different weather indicators, e.g., drought index and growing season length and evaluated which variables (i.e., temperature, precipitation, initial soil moisture content) dominantly drive changes in CLM5-predicted yield variability. The simulation results were able to reproduce the sign of crop yield anomalies, and thus provide a basis on which to study the effects of different weather patterns on inter-annual yield variability. However, the simulations showed limitations in correctly capturing inter-annual differences of crop yield in terms of total magnitudes (up to 10 times lower than in official records). Our results indicate that these limitation arise mainly from uncertainties in the representation of the subsurface soil moisture regime and a corresponding lack of sensitivity towards drought stress. Insights from this work were used to summarize implications for future analysis of CLM5-BGC simulation results over agriculturally managed land and allowed us to discuss and investigate possible technical model improvements.
How to cite: Boas, T., Bogena, H., Ryu, D., Vereecken, H., Western, A., and Hendricks-Franssen, H.-J.: Simulating regional inter-annual crop yield variability over multiple decades with the Community Land Model (CLM5) , EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-4818, https://doi.org/10.5194/egusphere-egu23-4818, 2023.
Land-atmosphere interactions are largely controlled by vegetation, which is dynamic across spatial and temporal scales. Most state-of-the-art land surface models do not adequately represent the temporal and spatial variability of vegetation, which results in weaknesses in the associated variability of modelled surface water and energy states and fluxes. The objective of this work is to evaluate the effects of integrating spatially and temporally varying vegetation characteristics derived from satellite observations on modelled evaporation and soil moisture in the land surface model HTESSEL. Specifically, model fixed land cover was replaced by annually varying land cover, and model seasonally varying Leaf Area Index (LAI) was replaced by seasonally and inter-annually varying LAI. Additionally, satellite data of Fraction of green vegetation Cover (FCover) was used to formulate and integrate a spatially and temporally varying model effective vegetation cover parameterization. The effects of these three implementations on model evaporation and soil moisture were analysed using historical offline (land-only) model experiments at a global scale, and compared to reference datasets.
The enhanced vegetation variability lead to considerable improvements in correlation of anomaly evaporation and surface soil moisture in semiarid regions during the dry season. These improvements are related to the adequate representation of vegetation-evaporation-soil moisture feedback mechanisms during water-stress periods in the model, when integrating spatially and temporally varying vegetation. These findings emphasize the importance of vegetation variability for modelling land surface-atmosphere interactions, and specifically droughts. This research contributes to the understanding and development of land surface models, and shows that satellite observational products are a powerful tool to represent vegetation variability.
How to cite: van Oorschot, F., van der Ent, R., Hrachowitz, M., di Carlo, E., Catalano, F., Boussetta, S., Balsamo, G., and Alessandri, A.: Improving the temporal and spatial vegetation variability in land surface models based on satellite observations , EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-6528, https://doi.org/10.5194/egusphere-egu23-6528, 2023.
Heatwaves have significant effects on ecosystems and human populations. Human habitability is impacted severely as human exposure to heatwaves is projected to increase. Future risk of heatwaves has demonstrated the need of effective measures for adaptation to persistent hot temperature extremes and ambitious mitigation to limit further increases in heatwave severity.
At local scales, forest management could be a potential approach of modifying surface energy budget and in this way alleviating heatwave impacts. In this study, open-site, below-canopy, and above-canopy climatic conditions from 4 different sites during the time period 1997-2020 in the Netherlands were compared to investigate canopy functions of affecting above-canopy macroclimate and as a thermal insulator to regulate understory microclimate and land surface ecology. Using high-resolution sub-daily data sets from Loobos, in which water vapor and heat fluxes were measured every half an hour by a combination of eddy covariance flux measurements and a profile system, we analysed temperatures at three levels of Loobos (23.5m, 7.5m, and soil litter layer) of the same profile and compared them with those measured at open sites in De bilt and Deleen.
Heatwave periods are defined as a sequence of at least five days during which the daily maximum temperature exceeds the climatological mean over the reference period 1997-2010 by at least 5 °C. During heatwave periods, the cooling effects of the canopy on surface temperatures are stronger compared to normal periods while the canopy may aggravate the temperature above it during certain hours. By contrast, temperature differences are higher during normal times than heatwave periods when considering temperature buffer effects of canopy on understory climate (7.5m).
Further study on heat fluxes, Bowen ratio, and canopy effects on heat stress during normal conditions and heatwaves will be conducted as well. Relative humidity will be incorporated in measuring heat stress to reflect real conditions living bodies experience.
How to cite: Zhou, J., Teuling, A. J., and van der Molen, M. K.: Diagnosing above- and below-canopy temperature impacts of forest in the Netherlands during heatwaves, EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-9767, https://doi.org/10.5194/egusphere-egu23-9767, 2023.
Land surface plays a fundamental role in the earth system, mediating the water, energy and carbon fluxes between the land and the atmosphere. The land surface physical and biophysical processes act on time scales ranging from sub-daily to decades with relevant impacts from weather forecasts to climate change. However, there are very few available in-situ observations of land surface state and fluxes extending for several years to decades, limiting an integrated validation of the models on the different time scales. The long time series of Cabauw (Netherlands) observations provides a unique opportunity to evaluate land surface processes and their representation in land surface model at time scales ranging from sub-diurnal to interannual. In this study, we take advantage of the uniqueness of Cabauw observational record to investigate the performance of the ECMWF land surface model ECLand for the period 2001-2020 (20 years). Emphasis is given to the summer season and to evaporation and evaporative fraction. An idealized simulation without canopy resistance is performed along with other model configurations with changes to the constraints of canopy resistance (soil moisture availability and atmospheric humidity deficit) and the vertical discretization of the soil layers.
Observational uncertainties impact the surface energy budget closure. For example, the model shows a large overestimation of the ground heat flux diurnal cycle. However, part of this can be attributed to observational uncertainties associated with the sinking of the temperature sensors. The default configuration of ECLand shows an underestimation of latent heat and evaporative fraction, which can be partially attributed to the model’s representation of canopy resistance. The increased vertical discretization of the soil layers has a neutral impact on the simulated turbulent fluxes, showing an improved representation of near-surface soil temperature. Our results show limitations in the representation of the summer interannual variability of the turbulent fluxes. These are associated with the representation of extreme events (droughts) and are not fully addressed in any of the model configurations tested. These results suggest that other processes relevant to the representation of evaporation in dryness stress conditions need to be further investigated.
This work was developed in the framework of the project NextGEMS funded through the European Union’s Horizon 2020 research and innovation program under the grant agreement number 101003470. Luis Frois was funded by the FCT Grant 2020.08478.BD. The authors also acknowledge the financial support of the Portuguese Fundação para a Ciência e a Tecnologia (FCT) I.P./MCTES through national funds (PIDDAC) – UIDB/50019/2020- IDL.
How to cite: Fróis, L., Miranda, P. M. A., and Dutra, E.: Diurnal to interannual variability in Cabauw simulated by the ECLand land surface model, EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-9920, https://doi.org/10.5194/egusphere-egu23-9920, 2023.
A credible assessment of spatial and temporal variability of the water and energy budget is of viable importance for the quantification of the observed changes and prediction of extremes in a changing climate. However, an accurate representation of feedback mechanisms between the land surface and the atmosphere is a key source of uncertainty in climate models.
WRF-CTSM (Weather Research and Forecasting model, WRF, and Community Terrestrial Systems Model, CTSM) is a state-of-the-art modelling tool that represents the forefront in the climate modelling community and unifies the recent model development activities across weather, climate, water and ecosystem research. This study is the first to provide a systematic regional scale assessment of the WRF-CTSM coupled climate model performance in the European context - in the high-latitude region encompassing Norway, Sweden and Finland.
A 10-year-long regional WRF-CTSM simulation (2010-2020) using meteorological boundary conditions from the ERA5 reanalysis is performed on a 10.5 km horizontal resolution to evaluate the representation of hydroclimatic variables through comparison against ERA5 and a range of observational datasets. Changes in boundary layer variables such as soil and near-surface air temperature, soil moisture and snowpack are essential for the assessment of the land-atmosphere feedbacks in this region and are thus selected as central for the analysis of the model skill. Besides the WRF-CTSM simulations using default CTSM settings, this study investigates the added value of including the recently developed Hillslope Hydrology model in WRF-CTSM runs that has the potential to improve the understanding of the role of topography and hydrology on the soil moisture and snowpack variability.
Preliminary results indicate the capacity of WRF-CTSM to identify the high-temperature susceptible areas in Norway, Sweden and Finland and reproduce the interannual variability and spatial patterns of hydroclimatic variables in the respective region.
How to cite: Mužić, I., Hodnebrog, Ø., Berntsen, T. K., Yilmaz, Y., Sillmann, J., Lawrence, D., Swenson, S., and Sobhani, N.: The relevance of coupled climate model WRF-CTSM for land-atmosphere interactions analysis, EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-11343, https://doi.org/10.5194/egusphere-egu23-11343, 2023.
With amplified climate warming, climate extremes over Europe become more frequent. Since the 2000’s, many years have been characterized by extreme events such as droughts and heat waves. For example, in Central Europe, extreme droughts and heat waves took place in the years 2003 and 2018. In comparison, Cyprus experienced strong droughts during 2003 and 2016-2018. Such extreme climate events can have severe impacts on agricultural yields, the productivity of natural vegetation, and on water resources. In this regard, long-term Earth observation (EO) time series are essential to quantitatively assess and analyse changes on the land surface, including vegetation condition. In this study, a joint analysis of geoscientific time series over the last two decades, including EO-based MODIS vegetation indices and meteorological variables is performed to assess drought events and analyse trends as well as potential drivers of vegetation dynamics in Cyprus. The analysis of drought events and vegetation trends is based on the full archive of MODIS imagery at 250 m spatial resolution covering the period 2000-2022. In detail, climate-related effects on vegetation were analysed by means of the deviations of MODIS 16-day vegetation index composites from their long-term mean. Next, trends of the MODIS vegetation index were calculated to evaluate spatial patterns of vegetation change over the investigated period. These analyses were additionally performed for geographically stratified regions, including diverse vegetation classes such as cropland and grassland. Furthermore, the application of a causal discovery algorithm reveals linkages within a multivariate feature space, in particular between vegetation greenness and climatic drivers. Preliminary analyses showed that drought patterns differ with respect to seasons and the investigated vegetation class. For example, the strong drought year 2008 is clearly reflected in the results, whereas forest areas appear to be least affected by the drought during the spring months. Moreover, considering the significant trends over the last two decades, an increase in vegetation greenness could be observed.
How to cite: Uereyen, S., Eisfelder, C., Gessner, U., Reinermann, S., Asam, S., Panagiotou, C. F., Eliades, M., Varvaris, I., Loulli, E., Pittaki, Z., Hadjimitsis, D., Kuenzer, C., and Bachofer, F.: Earth observation time series for the monitoring of droughts in Cyprus: Patterns and drivers of vegetation dynamics, EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-13277, https://doi.org/10.5194/egusphere-egu23-13277, 2023.
Heatwave and drought extremes can have significant impacts on vegetation, which can in turn lead to important effects on reactive trace gas fluxes at the land-atmosphere interface that can ultimately alter atmospheric composition. We present results from the EU-funded Sentinel EO-based Emission and Deposition Service (SEEDS) project, which aimed at developing upgrades to the existing Copernicus Atmospheric Monitoring Service (CAMS) component on European air quality. In this work, we used land surface modelling (SURFEX – Surface Externalisée) combined with data assimilation (Extended Kalman Filter - EKF) of satellite leaf area index (LAI) to deliver improved estimation of the land surface state. The land surface model is coupled with an online model for dry deposition and an offline model (MEGANv3.1) for biogenic volatile organic compounds (BVOCs) to estimate trace gas losses and emissions, respectively. This approach exploits methods at the forefront of land surface modelling (dynamic vegetation simulation and data assimilation) and combines them with the latest algorithms to estimate trace gas fluxes at the surface. We present findings from two extreme events in Europe: the 2018 drought and the 2019 June/July heat waves. SURFEX was forced using ECMWF meteorology at 0.1° × 0.1° resolution that captured both events. Both extreme events provoked strong responses in the models for dry deposition velocity and BVOC emissions. The 2018 drought began in spring and endured through summer, during which dry deposition velocities declined steadily beyond seasonal norms due to increased stomatal resistance forced by the vegetation response to drought. Over continental Europe, BVOCs initially increased in the early phase of the drought, but then sharply declined into July in the worst-affected regions in Germany, Denmark, and Poland. Meanwhile, BVOCs increased in Scandinavia relative to seasonal norms due to the warmer-than-average conditions. The first episode of severe heat in 2019 arrived in late June, which initially caused a large increase in BVOC emissions compared to seasonal norms. Then drought set in during July and despite a second large heat wave BVOC emissions were lower overall compared to seasonal norms. In fact, the European-wide BVOC emissions were higher in June compared to July due to the drought effects that commenced later in the heat wave cycle. This reverses the normal seasonal cycle in BVOC emissions, and drought impacts on vegetation were the primary driver behind this. Dry deposition velocities are reduced during both heat waves, but we see a larger decline in the second heat wave in July when drought conditions are more severe.
Our findings suggest that these impacts on trace gas surface fluxes would have a strong effect on atmospheric composition, and on photochemical ozone formation. We, therefore, conclude that these effects likely played a contributory role to the ozone pollution episodes that occurred coincidentally in time with the heat wave events in both 2018 and 2019. The project aim within SEEDS is to eventually test the BVOC emissions and dry deposition velocities within a chemical transport model participating within the CAMS regional ensemble (MOCAGE) and to therefore evaluate the impact on ozone.
How to cite: Hamer, P., Trimmel, H., Calvet, J.-C., Bonan, B., Meurey, C., Vallejo, I., Eckhardt, S., Sousa-Santos, G., Marecal, V., and Tarrason, L.: The Impact of Recent European Droughts and Heatwaves on Trace Gas Surface Fluxes: Insights from Land Surface Data Assimilation, EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-13932, https://doi.org/10.5194/egusphere-egu23-13932, 2023.
Semi-arid rangelands in Sub-Saharan Africa (SSA) are an important source of food security and nutrition but are under increased anthropogenic pressure by a growing population. These rangelands are characterized by nutrient poor soils and distinct wet and dry season(s). Due to the soil and climate combination, conventional crop agriculture is rarely feasible without irrigation and mineral fertilizer amendments, which in turn are limited by prohibitively high fertilizer prices and lack of water. Instead, pastoral livestock keeping is a valuable option to use these marginal lands and – under the right management – can be a sustainable form of food production and biodiversity protection given that most of these landscapes have co-evolved with megafauna over millennia. Despite the global role of livestock systems on climate change, there is still limited understanding on the role of SSA rangelands. At the same time, livestock systems emit greenhouse gases (GHG) and can promote global warming. But despite the impact of livestock systems on climate change, our understanding of the role of SSA rangelands is limited. To date, a thorough assessment that includes continuous GHG exchange measurement in combined wildlife-livestock systems on the African continent has not been undertaken. Here we provide the first eddy covariance (EC) measurements of CO2/CH4/H2O fluxes from the ILRI Kapiti Wildlife Conservancy - a benchmark rangeland site in East Africa that is grazed by livestock and wildlife. Our results show continuous ecosystem CO2 uptake from the wet to dry seasons with considerable CO2 emission pulses following precipitation events after long dry periods that turn the landscape into short-term net CO2 emitters. In contrast to CO2, CH4 fluxes are highly variable and depend particularly on wildlife and/or livestock being present in the fetch of the EC tower. In addition to EC measurements and given the need for scaling of our results, we relate CO2 and CH4 fluxes to simple remote sensing measurements of vegetation greenness derived from phenological cameras. Our results show good agreement between the two approaches. Yet, more observations across a climatic gradient and along varying management intensities are needed to reduce existing uncertainties in the effect of SSA rangelands on climate change. To build a complete GHG budget, hot spots of greenhouse gas emissions such as from livestock enclosures or water bodies as well as soil carbon sequestration have yet to be accounted for.
How to cite: Merbold, L., Odongo, V., Dowling, T., Fava, F., Glücks, I., Vrieling, A., Wooster, M., and Leitner, S.: Continuous observations of CO2 and CH4 exchange from East-African rangelands, EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-14158, https://doi.org/10.5194/egusphere-egu23-14158, 2023.
Soil moisture content is crucial for the representation and predictability of hydroclimatic extremes of different spatial/temporal scales such as heavy rainfall, droughts and heatwaves. In order to include these effects and the relevant feedback with the atmosphere in a regional climate model, the soil moisture initialization has to be adequate.
This study explores the soil moisture precipitation (SM-P) feedback, the soil moisture temperature (SM-T) feedback and the heat fluxes over the entire domain and 3 smaller regions of interest. A hydrostatic version of the Regional Climate Model 4.7 (RegCM4.7) with Arakawa B grid is used to run the simulations. The simulations are performed for the months February to May during the years 2008, 2009 and 2010 with a spatial resolution of 12 km and temporal resolution of 3 hours. The initial and boundary conditions(ICBC) are derived from the ERA5 data. We examine results from simulations initiated using three different soil moisture datasets, namely, the control, dry and wet datasets. The soil moisture data from the ERA5-Land reanalysis is used for the control simulation. A dry/wet simulation is run using dry/wet datasets derived from the ERA5-Land data. This is done by halving/doubling the soil moisture values from ERA5-Land data, giving rise to new soil moisture values with lower/higher soil moisture as compared to the control dataset (ERA5-Land). CMORPH (Climate Prediction Center (CPC) Morphing Technique (MORPH)) and CRU (Climate Research Unit) datasets are used as reference to evaluate the precipitation and temperature values resulting from the control simulation.
The results display the mean changes in the dry/wet simulation results with respect to the control simulation. Plots showing the vertical profile changes in relative humidity and air temperature, and changes in lower tropospheric wind and specific humidity, indicates the build-up of the observed precipitation events and temperature patterns induced by the initial soil moisture perturbation. Interestingly the simulation results show negative SM-P feedback. In other words, the average precipitation seemed to increase/decrease for the dry/wet cases with respect to the control simulation. This is contrary to the general expectation that dry/wet soil moisture decreases/increases precipitation. The possible reasons for the negative SM-P feedback and its distribution over the region include the proximity to the ocean, topography, and the pre-monsoon dryline. The SM-T and the heat fluxes on the other hand display expected behaviour with few exceptions in some regions in the dry simulation case.
How to cite: Vasukuttan, A., Sangelantoni, L., Shateesan, K., and Redaelli, G.: Sensitivity to soil moisture initialization in the simulation of Indian pre-monsoon season, using a regional climate numerical model, EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-14377, https://doi.org/10.5194/egusphere-egu23-14377, 2023.
Ground surface temperature (GST), measured at approximately 5 cm into the ground is a key parameter controlling all the subsurface biophysical processes at the land-atmosphere boundary. Despite the GST significant importance, the current observational network for GST is sparse, particularly in mountain regions. This work exploits the relationship between the GST and satellite-based land surface temperature (LST) derived from MODerate resolution Imaging Spectroradiometer (MODIS). The GST and LST were compared at 14 weather stations in Mazia Valley, North-eastern Italian Alps. The 1-km MODIS LST was downscaled to a spatial resolution of 250-m using the random forest algorithm. The LST dataset covers the years 2014-2017 during the phenological cycle, between April and October. The in-situ GST measurements were recorded using Campbell Scientific CS655 data loggers. LSTs were usually larger than GSTs with temperature differences ranging from 0.1 to 22 °C and an average of 7.9 °C. The lowest and largest average difference was 4.49 °C (1823 m, pasture, south slope) and 10.27 °C (1778 m, forest, north slope), respectively. GST was positively correlated with LST with an R2 ranging from 0.24 to 0.52 and was above 0.45 for 57 % of the stations. The RMSE ranged between 6.05 and 11.05 °C, while for 71 % of the stations was below 9.3 °C. The statistics were influenced by the number of available pairwise for comparison that were ranging from 110 to 377 due to cloud contamination or logger malfunction. Although the RMSE was relatively high, the LST closely followed the pattern of the GST variability suggesting the possibility of linking GST to LST products.
How to cite: Șerban, R.-D., Bartkowiak, P., Castelli, M., and Bertoldi, G.: Ground surface temperature linked to remote sensing land surface temperature in mountain environments, EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-5726, https://doi.org/10.5194/egusphere-egu23-5726, 2023.
Posters virtual: Fri, 28 Apr, 16:15–18:00 | vHall CL
Atmospheric humidity is usually drier in cities than the surrounding rural areas, a phenomenon known as the urban dry island (UDI) effect. However, the response of atmospheric humidity to hot weather in urban versus rural settings remains unknown. Using long-term summer (June-August) observations at 1658 stations over 1961-2020, we find that China is dominated by drying trends in atmospheric humidity (i.e., increasing vapor pressure deficit [VPD]). These drying trends are aggravated on hot days and amplified by urbanization, i.e., the UDI effect is stronger in hot weather. This amplification of the UDI effect on hot days is more prominent in humid than in arid regions. Attributions show that the stronger VPD-based UDI effect on hot days is explained by increased contribution of air temperature in southeastern China, and specific humidity in North China. We suggest that adaptations are required to mitigate adverse combined effects of urban heatwaves and UDIs.
How to cite: Luo, S. and Gu, X.: Hot weather amplifies the urban dry island effect, especially in wetter climates, EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-2064, https://doi.org/10.5194/egusphere-egu23-2064, 2023.
Flux partitions between surface water and energy terms are essentially important to the climate system. They can potentially affect assessments of climate risk projections in the future. However, the characterization of surface flux partitioning in numerical models is rarely evaluated due to the absence of large-scale observational evidence. Here, we use long-term satellite datasets and observational meteorological records to evaluate the flux partitioning regime presented in four widely-used Land surface models (LSMs) over two study regions (i.e., China and Continental U.S.). We show that the regime in LSMs differs significantly from satellite-based estimations, which can be due to unrealistic representations of land surface characteristics. The biases in models’ flux partitioning regime may lead to the underestimated potential for climate risks, especially over regions with typical land surface characteristics. The results highlight that particular attention should be paid to the calibration of surface flux partitioning regimes in LSMs. Large model spreads in surface flux partitioning strength and climate risk maps are also reported.
How to cite: He, Q., Lu, H., and Yang, K.: Observation-based assessments of surface flux partitioning regimes in 4 commonly-used land surface models , EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-333, https://doi.org/10.5194/egusphere-egu23-333, 2023.
Effective representation of soil heterogeneity in land surface models is crucial for accurate weather and climate simulations. The NOAH-MP land surface model uses dominant soil texture from State Soil Geographic (STATSGO)/Food and Agriculture Organization (FAO) datasets, considerably introducing uncertainty in the simulation of soil hydrothermal changes and terrestrial water and energy fluxes, at a fine scale. This study investigates the likely added value of incorporating an alternative high resolution soil grid data at different depths, for a better representation of soil hydrothermal dynamics in NOAH-MP v4.3. The model is set up at 1 km grid space over all Ireland domain and soil layer thicknesses of 0.07, 0.21, 0.72 and 1.55 m, with a cummulative soil depth of 2.55 m. The thicknesses are selected to match the layers of initial soil input fields. Model experiments are carried out based on two soil data options namely, (1) the STATSGO/FAO dominant soil texture and (2) the 250 m global soil grid textural compositions from the International Soil Reference and Information Centre (ISRIC), in combination with PedoTransfer Functions (PTFs). The current model integration is applied within the high resolution land data assimilation (HRLDAS) framework to simulate soil temperature and soil liquid water, and evaluated for wet and dry periods using observations from the newly established Terrain-AI data platforms (terrainai.com). Ultimately, the study highlights the importance of using realistic dynamic soil information, which could provide insightful scientific contributions to better monitor surface climate and the influences on land use and land management under climate change.
How to cite: Ishola, K., Sati, A., Demuzere, M., Mills, G., and Fealy, R.: The incorporation of 250 m soil grid textural layers in the NOAH-MP land surface models and its effects on soil hydrothermal regimes, EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-3549, https://doi.org/10.5194/egusphere-egu23-3549, 2023.
