Climate over land is strongly shaped by the conditions at the land surface, particularly regarding the partitioning of energy, the availability of water, and the presence of vegetation. What we show here is that a number of key climatological fluxes and variables can be estimated quite accurately simply by applying basic physical constraints. First, heat fluxes are associated mostly with convective motion, which requires work to be done in the form of buoyancy. The generation of this work is subject to a first, physical constraint, the thermodynamic limit of a heat engine. Second, on land, the large differences in solar heating over the course of the day are buffered within the lower atmosphere, and not below the surface as is the case over open water surfaces. This sets a second constraint. Third, when hydrological aspects are involved, saturation, that is, the thermodynamic equilibrium state, sets another constraint to evaporation and the humidity of air. We focus on diurnal variations of the surface energy balance, temperature, and humidity over land and compare these to observations to show that these three constraints dominantly shape climatological variations across regions. What this implies is that physical constraints dominate the functioning of climate over land, and much of this is shaped by the prevalent radiative conditions, with secondary effects relating to soil water availability and advection. This, in turn, should help us to better distinguish between the important drivers from mere responses in shaping land-atmosphere interactions.
How to cite: Kleidon, A., Ghausi, S. A., and Chauhan, T. A.: How basic physical constraints shape land-atmosphere interactions, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-4968, https://doi.org/10.5194/egusphere-egu26-4968, 2026.
Potential evapotranspiration (ETp) is a variable driven by many factors and one which is heavily affected by climate change. In many cases, the observed increase in ETp is attributed to rising air temperatures in the past and temperature is used as the main prediction variable for future developments of ETp in climate change projections.
The climate station at the lysimeter station Brandis (Saxony, Germany) has been recording a wide range of climate variables since 1980. From the observations it is evident that, in addition to the increase in air temperature at the site, there has also been a significant increase of sunshine duration (average increase of 0,29h d⁻¹ decade⁻¹) and global radiation (average increase of 47,45 J cm⁻2 d⁻¹ decade⁻¹). This combination of higher temperature levels and increased energy availability leads to significant increases in ETP (average increase of 0,11 mm d⁻¹ decade⁻¹), which is a mayor driver of the local water balance and an important variable in describing the atmospheric demand in modeling studies. Based on the observed trend in sunshine durations we provide an analysis of the individual contributions of increases in global radiation and air temperature, to assess:
- the individual contributions to the overall increase in potential evapotranspiration (according to Turc-Wendling)
- the influence of global radiation and air temperature on the intra-annual course?
The individual contributions of increases in radiation and air temperature on the ETP was calculated using trend analysis over the period from 1980 to 2025. It shows that, according to the Turc-Wendling approach, 69% of the ETP increase at the site is radiation-driven, while air temperature only has an influence of 28%. Additionally, clear seasonal patterns are found in the individual contributions. Overall, the results show that global radiation increases are a mayor driver for the increase in potential evapotranspiration at the site and future developments of potential trends in global radiation should be considered in projections of potential evapotranspiration.
How to cite: Tiedke, A. and Werisch, S.: The influence of increasing radiation (sunshine duration and global radiation) on the increase in potential evapotranspiration, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-21187, https://doi.org/10.5194/egusphere-egu26-21187, 2026.
Canopy temperature (Tc) is a key regulator of plant physiological processes, growth, and productivity, and serves as an indicator of surface energy partitioning and plant water status. Despite its importance, many dynamic vegetation models implicitly assume Tc to be equal to air temperature (Tair); while land surface models calculate an effective surface temperature based on energy balance, but typically have not evaluated this calculation against data. Using satellite-derived land surface temperature as a proxy for Tc, in combination with ERA5-Land Tair, we assessed whether tropical rainforests actively thermoregulate Tc relative to Tair. We find that ΔT (Tc – Tair) follows a consistent diurnal cycle, which is primarily controlled by diurnal variations in net radiation. Forest canopies are cooler than air at night, warm early in the morning and cool again below Tair in late afternoon. During the hottest part of the day, the slope (β) of the canopy-air relationship indicates strong megathermy in dry forests, while humid forests show responses ranging from limited homeothermy to megathermy depending on their capacity to dissipate heat. Humid forests with sufficient water availability show buffering of Tc against Tair variability through evaporative cooling, whereas dry forests frequently experience canopy warming as aridity constrains evaporative cooling. In humid forests, this evaporative cooling persists through the wet season but weakens—or reverses to canopy warming—during the dry season as water stress intensifies. Together, these findings provide an observational benchmark for improving the representation of canopy temperature, evaporative cooling, and vegetation–atmosphere energy and water exchanges in land-surface models.
How to cite: Verma, A. and Prentice, I. C.: Tropical Forest Canopy Thermoregulation Observed from Space, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-4152, https://doi.org/10.5194/egusphere-egu26-4152, 2026.
How to cite: Cultra, E., Nanditha, J. S., Yin, J., Bartlett Jr, M. S., and Porporato, A.: The Role of Land-Surface Dynamics in Climate Persistence and Convective Extremes, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-19934, https://doi.org/10.5194/egusphere-egu26-19934, 2026.
Land-atmosphere interactions are key drivers of climate extremes, mediating the influence of soil moisture, vegetation, and surface energy exchanges on droughts, heatwaves, and compound events. Observed vegetation changes such as climate-induced tree mortality, phenological shifts, and large-scale deforestation can substantially alter these interactions by modifying surface energy and water fluxes. A critical challenge is to understand how soil water-energy feedbacks propagate through the atmosphere, which is essential for both predicting extremes and evaluating Earth System Models (ESMs).
To address this, we propose a unified causal and explainable framework to disentangle soil water-energy feedbacks from observational data, creating a benchmark for ESM evaluation. First, we construct machine learning emulators to represent the dynamical responses of land and atmosphere modules to external forcings, consistent with a structural causal model (SCM). These emulators act as efficient, process-aware surrogates, enabling the reconstruction of causal pathways (e.g., soil moisture/temperature → near-surface states) in a computationally tractable way. Using do-calculus combined with explainable AI (XAI), we then estimate the causal coupling strengths of water-energy feedbacks, isolating the direct effects of soil states from confounding atmospheric influences. By comparing these causal estimates against observational constraints, we can evaluate and benchmark ESM representations, revealing structural biases, deficiencies, and uncertainties in simulated pathways.
Bridging causal inference, machine learning, and observations, our framework provides a robust tool for process-level diagnosis, model benchmarking, and ultimately improving the physical fidelity of complex ESMs. It advances the mechanistic understanding of how land states drive atmospheric extremes, offering actionable insights for predicting droughts and heatwaves under current and future climates.
How to cite: Huang, F., Camps-Valls, G., Winkler, A., Reimers, C., Carvalhais, N., and Gavrilov, A.: Causal disentangling of soil moisture and temperature feedbacks on surface climate extremes under vegetation change, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-12361, https://doi.org/10.5194/egusphere-egu26-12361, 2026.
Soil moisture–precipitation (SM–P) coupling is a key component of land–atmosphere interactions, but its strength and sign remain highly uncertain in large-scale models. While high-resolution models that explicitly resolve convection offer a way to reduce these uncertainties, their impact on SM–P coupling is not yet fully understood. Here, we investigate global SM–P coupling across different spatial resolutions using the Nonhydrostatic Icosahedral Atmospheric Model (NICAM). We find that SM–P coupling strongly depends on model resolution. As resolution increases, precipitation becomes more localized, leading to a smaller rainy area and a more heterogeneous spatial structure of the coupling. These changes involve significant regional variations in both coupling strength and sign. At high resolution, coupling is strengthened in major land–atmosphere hotspots, driven by enhanced convection that produces higher precipitation and more active moisture exchange. Meanwhile, high-resolution simulations exhibit widespread sign reversals in SM–P coupling. These reversals are caused by the convection-driven redistribution of precipitation, where localized moisture convergence and divergence reshape the coupling relationships. Compared to FLUXNET and ERA5 data, increasing model resolution systematically reduces negative biases in SM–P coupling, bringing the simulation closer to observations. Our results show that high-resolution modeling helps reconcile simulations with observations and emphasize the importance of using high-resolution frameworks to represent land–atmosphere interactions accurately.
How to cite: Li, S., Tokuda, D., Hsu, H., Shih, C.-H., Hsu, J., Lo, M.-H., and Yoshimura, K.: Revisiting Land-Atmosphere Coupling Across Spatial Scales: From Coarse to Kilometer-Scale Simulations, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-12389, https://doi.org/10.5194/egusphere-egu26-12389, 2026.
The land subsurface stored around 6% of the Earth’s energy imbalance in the last five decades (of around 0.5 Wm-2, equivalent to 380 ZJ), being the second contributor to the energy partitioning after the ocean (90%). Previous studies have shown that state-of-the-art Earth System Models (ESMs) remarkably underestimate the observational land heat uptake values. This underestimation stems from Land Surface Models (LSMs) within ESMs imposing too shallow zero-flux bottom boundary conditions to correctly represent the conductive propagation and land heat uptake with depth. When realistically deep boundary conditions are prescribed, land heat uptake increases by a factor of five. However, changes in ground surface temperature are negligible. The reasons for this lack of impact of the LSM depth on surface temperatures are assessed herein.
An ensemble of eight historical and RCP8.5 land-only simulations with different subsurface depths was conducted with the LSM of the Max Planck Institute for Meteorology ESM (MPI-ESM), JSBACH. Simulation-derived latent (LHF), sensible (SHF), and ground heat fluxes (GHF) were compared across simulations, and GHF was additionally evaluated against estimates from a one-dimensional heat conduction forward model. Results show that, for a global warming of 1.5 ºC with respect to 1850-1900, GHF increases from 0.04 to 0.07 Wm-2 when deepening the LSM from 10 to 22 m, saturating at around 0.12 Wm-2 when the boundary condition is placed at approximately 100 m. The increase in the incoming GHF is mainly compensated by a global decrease in the outgoing SHF, a small decrease of the LHF in wet regions, and a decrease in the surface net radiation in arid and semi-arid regions. These quantities, yet small, evidence that an insufficient LSM depth induces to an inaccurate resolution of the long-term surface energy balance, which may have implications for land-atmosphere interaction. Their accumulation over time also produces biases in the terrestrial energy partitioning.
How to cite: González-Rouco, F., García-Pereira, F., Meabe-Yanguas, N., Jungclaus, J., Lorenz, S., Hagemann, S., Yagüe, C., Cuesta-Valero, F. J., García-García, A., and Beltrami, H.: An insufficient subsurface depth biases the long-term surface energy balance in Land Surface Models, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-13692, https://doi.org/10.5194/egusphere-egu26-13692, 2026.
Humidity over land is a key climate variable that is strongly coupled to mean and extreme temperatures, to precipitation and evapotranspiration, and to wildfires. Understanding the processes controlling the climatology of land humidity and its response to a changing climate is a fundamental scientific question with important societal implications. Here we use a global climate model with tagged water tracers to directly diagnose the sources of land specific humidity over a range of climate states. The simulations isolate the contributions to land humidity from water evaporated: (i) from the land surface ("terrestrial source"); and (ii) from the ocean surface ("oceanic source"). The control simulation reveals that land humidity in most regions and for most months of the year is dominated by the oceanic source, i.e. water evaporated from the ocean and advected over land. The terrestrial source is important in some inland regions, for example Eurasia, and during Jun-Jul-Aug, when advection is weaker in the northern hemisphere. Under climate change, the oceanic source dominates changes in land humidity at all latitudes but with a non-negligible contribution from the terrestrial source. The results are interpreted using a conceptual box model which predicts that the terrestrial and oceanic moisture sources scale equally with warming, implying equal fractional changes in land and ocean humidity. Implications of these new results for understanding the large biases in observed versus simulated land humidity trends over the historical period are discussed.
How to cite: Byrne, M., Chingos, A., Duffield, J., Laguë, M., and O'Gorman, P.: Oceanic-versus-terrestrial influences on land humidity: simulations and theory, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-1932, https://doi.org/10.5194/egusphere-egu26-1932, 2026.
Near-surface relative humidity (RH) over land is a key mediator of land-atmosphere interactions, influencing surface energy partitioning, evapotranspiration, wildfire risk, and both temperature and precipitation extremes. Despite its central role in regulating land climate, the response of land RH to climate change remains highly uncertain, with climate models projecting a wide range of historical and future trends. Notably, many models struggle to reproduce the observed decline in land RH over the recent warming period, raising concerns about their representation of land climate processes and future projections.
Here we develop a simple physical theory to constrain changes in land RH, grounded in an ocean-influence perspective on boundary layer moisture over land. The theory links fractional changes in tropical land RH to the land–ocean warming contrast. As land warms more rapidly than the ocean, the increase in the water-holding capacity of land air outpaces the supply of moisture imported from oceanic regions, leading to a systematic decline in land RH. This mechanism highlights how large-scale land-atmosphere interactions can be regulated by ocean-driven constraints on land boundary layer moisture.
The theory explains much of the inter-model spread in historical tropical land RH trends, as well as the drying evident in reanalysis data. Combining the theory with observational estimates of the radiatively forced land–ocean warming contrast, we obtain constrained projections of future tropical land RH change (-6.4 %/K and -4.4 %/K) which indicate substantially stronger drying compared to the unconstrained projections (-1.5 %/K). This emergent constraint highlights a systematic underestimation of future land drying by climate models and its physical basis, with important implications for land-climate impacts in a warming world.
How to cite: Chingos, A., MacGilchrist, G., and Byrne, M.: Amplified future drying of tropical land constrained by physical theory, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-5957, https://doi.org/10.5194/egusphere-egu26-5957, 2026.
Land–atmosphere coupling has long been recognized to modulate the surface fluxes partition in transitional evaporative regimes, where soil moisture anomalies control evapotranspiration. However, globally available in-situ observations for these variables remain limited. This study provides, for the first time, a comprehensive assessment of the similarities, dissimilarities, and limitations among observation-based datasets of surface soil moisture, evapotranspiration, potential evapotranspiration, and 2-meter mean air temperature across Europe. The analysis focuses on the IPCC-defined regions of Northern Europe, Eastern Europe, Western-Central Europe, and the Mediterranean during summer (June–August) for the recent 20-year period (2003–2022). In addition, the study evaluates and compares the representation of land–atmosphere coupling across the different datasets. The results show that most datasets exhibit strong agreement across most regions and effectively capture land–atmosphere interactions. The coupling analysis further reveals a clear north–south contrast: Northern Europe is energy-limited, where atmospheric coupling dominates, whereas the Mediterranean is water-limited, with stronger terrestrial coupling. Central and Eastern Europe show more variability within the season and across years. Overall, the findings highlight reasonable consistency among datasets in representing land–atmosphere processes, despite existing uncertainties.
Keywords: surface soil moisture, evapotranspiration, land-atmosphere coupling, summer
How to cite: Sahoo, M., Materia, S., and Donat, M.: Summer Land-Atmosphere Coupling over Europe: A Comparative Evaluation of Observation-based Datasets, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-17817, https://doi.org/10.5194/egusphere-egu26-17817, 2026.
The Mediterranean region is widely recognized as a climate-change hotspot, where rising temperatures and declining precipitation are expected to intensify hydroclimatic stress. Most Mediterranean countries already experience increasing drought frequency and persistent soil moisture deficits leading to changes in terrestrial water storage. However, projected changes in the seasonal structure of soil moisture and its joint behaviour with temperature and precipitation remain insufficiently quantified.
Here, we assess future projections of soil moisture dynamics and compound warm–dry conditions across the Mediterranean using a multi-model ensemble of EURO-CORDEX regional climate simulations. We analyse daily total soil moisture, precipitation, 2-m temperature, and potential evapotranspiration for a historical baseline period (1971–2000), and three future periods (2011–2040, 2041–2070, 2071–2100) under three emission scenarios (RCP2.6, 4.5 and 8.5). Seasonal amplitude and phase changes in soil moisture are examined, and joint probability density functions are used to quantify compound warm–dry conditions and their drivers.
The projections show a clear reduction of soil moisture throughout the entire annual cycle, in response to a significant decrease in precipitation and an increase in temperature, leading to a substantial rise in potential evapotranspiration. The overall total soil moisture decreases ranges from -5% for the RCP2.6 to -20% (-10%) for the RCP8.5 (RCP4.5), with relation to the present climate. Projections reveal that for the RCP4.5 (RCP8.5) for the mid-century soil moisture deficits up to 5x (6x) are projected to occur, and for the end-of-century even 7x for the RCP8.5. Our results show a robust amplification of soil moisture seasonal amplitude across all Mediterranean sub-regions, increasing with higher greenhouse gas emissions and toward the end of the century. The largest increases are projected over the eastern Mediterranean, reflecting enhanced seasonal contrasts driven by intensified summer drying. Despite these amplitude changes, the phase of the soil moisture annual cycle remains stable across scenarios, indicating that climate change primarily intensifies existing seasonal dynamics rather than shifting their timing. Joint probability analyses show a substantial increase in the likelihood of compound warm–dry conditions, particularly under RCP4.5 and, more pronounced under RCP8.5, during mid- and late-century periods.
Overall, our findings highlight that future Mediterranean hydroclimatic risk is driven not only by mean drying but also by a pronounced intensification of soil moisture variability and compound extremes. These projections have important implications for ecosystem, water resources, and climate adaptation strategies.
This work is supported by FCT, I.P./MCTES through national funds (PIDDAC): LA/P/0068/2020 - https://doi.org/10.54499/LA/P/0068/2020, UID/50019/2025, https://doi.org /10.54499/UID/PRR/50019/2025, UID/PRR2/50019/2025. The authors would like also to acknowledge the project “Elaboração do Plano Municipal de Ação Climática de Barcelos (PMACB). This work was performed under the scope of project https://doi.org/10.54499/2022.09185.PTDC (DHEFEUS). DCAL acknowledge FCT I.P./MCTES (Fundação para a Ciência e a Tecnologia) for the FCT https://doi.org/10.54499/2022.03183.CEECIND/CP1715/CT0004.
How to cite: Lima, D. C. A., Bento, V. A., Russo, A., and Soares, P. M. M.: Amplification of soil moisture seasonality and compound warm–dry conditions over the Mediterranean under future climate scenarios, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-13031, https://doi.org/10.5194/egusphere-egu26-13031, 2026.
Interactions between vegetation and the overlying atmosphere, mediated by changes in surface moisture availability and energy flux partitioning, exert significant influence on near-surface temperature and other atmospheric variables. At seasonal timescales, these vegetation-atmosphere interactions have the potential to enhance forecast predictability. However, current operational seasonal forecast systems, such as ECMWF’s SEAS5, prescribe vegetation to a fixed climatological state. This does not fully capture vegetation-atmosphere interactions and thus the potential predictability is not fully exploited. In this presentation, we investigate the atmospheric response to prescribing inter-annually varying Leaf Area Index (LAI) in seasonal hindcasts and assess its effect on seasonal forecast skill. This work focuses on Africa, where seasonal forecasts are crucial for agricultural planning and extreme weather preparedness.
A series of seasonal hindcasts run for the period 1993-2019 using ECMWF’s coupled Integrated Forecasting System are used. We compare two experiments – a control experiment, which uses climatological LAI and a non-varying land cover map, and an experiment which implements a dataset of inter-annually varying LAI and land cover maps produced by merging multiple satellite products. In general, prescribing inter-annually varying LAI increases African near-surface air temperatures by up to 0.2K compared to a fixed climatological LAI across Africa. To evaluate temperature changes associated with LAI variations, we perform a Seasonal-reliant Empirical Orthogonal Function analysis (see Wang and An, 2005) on the driving LAI dataset. We find a mode of variation that is correlated with the Indian Ocean Dipole (IOD) index for the September-November-December season (correlation coefficient of ~0.75); thus, we view this mode of LAI variation as the vegetation response to increased East African rainfall during active IOD events. Results show a consistent near-surface temperature response across East Africa when inter-annually varying LAI is prescribed. The temperature response is shown to be consistent with simulated changes in the surface energy balance. Forecast skill of temperature, measured as bias compared to ERA5 values, is shown to be improved when vegetation varies inter-annually. Improvements in bias are largest following extreme IOD events and for areas where the control hindcasts’ bias is largest, with a maximum in temperature bias reduction of 0.6K and an average bias reduction of 0.2K. Thus, we find that increased complexity in vegetation representation in seasonal forecasts leads to improvements in forecasted temperature through better representation of land-atmosphere interactions influenced by the IOD.
How to cite: Gangardt, D., Harris, B., Talib, J., Taylor, C., and Folwell, S.: Inter-annually varying vegetation improves seasonal forecasts of near-surface temperature in East Africa, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-10354, https://doi.org/10.5194/egusphere-egu26-10354, 2026.
Soil moisture is a key ingredient of humid heat through supplying moisture and modifying boundary layer properties. Soil moisture heterogeneity due to for example, antecedent rainfall, can strongly influence weather patterns; yet, its effect on humid heat is poorly understood. Idealized numerical simulations are performed with a cloud-resolving (Δx = 500 m), coupled land-atmosphere model wherein circular wet patches with diameter λ ∈ 25-150 km are prescribed. Compared to experiments with uniform soil moisture, humid heat is locally amplified by 1 to 4°C in experiments with heterogeneous soil moisture, with maximum amplification for the critical soil moisture length-scale λc = 50 km. Subsidence associated with a soil moisture-induced mesoscale circulation concentrates warm, humid air in a shallower boundary layer. Additional pairs of uniform-heterogeneous soil moisture simulations are performed to assess the influence of the background wind, the strength of the soil moisture contrast, and the vertical structure of the atmosphere, on the relationship between soil moisture length-scales and humid heat amplification. This study provides process-based insights into the effects of soil moisture heterogeneity on humid heat in various environments at fine time and space scales, challenging extreme humid heat outputs from coarser-resolution weather and climate models. Furthermore, these results will help to predict extreme humid heat at city and county scales across the Tropics based on observed soil moisture patterns.
How to cite: Chagnaud, G., M Taylor, C., S Jackson, L., Barber, A., L Burns, H., Marsham, J., and E Birch, C.: Mesoscale soil moisture heterogeneity can locally amplify humid heat, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-4802, https://doi.org/10.5194/egusphere-egu26-4802, 2026.
Chamoli district, located in the Garhwal Himalaya of Uttarakhand, functions as a critical ecological buffer connecting mountain environments with downstream river systems. Its complex terrain, diverse biota, and glacier-fed rivers play an essential role in sustaining regional water resources and enhancing climate resilience. Despite its importance, studies exploring the land–atmosphere coupling processes in this climate-resilient region remain scarce.
In this work, we employ an information-theoretic approach to examine seasonal land–atmosphere interaction networks using key variables: precipitation (P), temperature (T), latent heat flux (LH), sensible heat flux (SH), wind speed (WS), incoming shortwave radiation (SWL), and relative humidity (Q). The analysis is conducted for four seasons: pre-monsoon (MAM), monsoon (JJAS), post-monsoon (ON), and winter (DJF). The derived networks distinguish between two types of links: instantaneous (real-time) and lagged (memory-controlled). Entropy-based diagnostics indicate that MAM and JJAS exhibit the highest dynamical variability, DJF represents the most quiescent period, and ON behaves as a transitional regime for Chamoli. Wind speed exerts a dominant real-time control on precipitation and also shows delayed influences at higher altitudes. In general, real-time coupling is strongest during the monsoon season, whereas comparatively enhanced memory-driven relationships mark winter.
The pre-COVID and post-COVID periods are compared to assess changes in information flow; we find that entropy deviation decreased around 2019, then increased after 2021. These findings refine our understanding of land–atmosphere dynamics over Chamoli and provide a reference state for evaluating future changes arising from natural climate variability and anthropogenic forcing.
Keywords—Land-atmospheric interaction; information-centric method; real-time interaction; entropy.
How to cite: Jaiswal, R., Pandey, M. K., and Verma, S.: Fluxes, Feedbacks, and Memory: Untangling Chamoli’s Seasonal Land–Atmosphere Coupling, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-700, https://doi.org/10.5194/egusphere-egu26-700, 2026.
Land surface conditions are known to strongly influence the intensity and frequency of heatwaves; however, their role in governing the temporal evolution and spatial propagation of heatwaves remains insufficiently explored. This study investigates the impact of land surface conditions on the temporal evolution and spatial propagation of pre-monsoon heatwaves in northwest and central India. Analysis of surface energy budget components during heatwave events reveals two dominant patterns of land surface flux evolution. In northwest India, the development of heatwaves is typically associated with weak near-surface winds that promote localized heat buildup. This phase is often followed by a strengthening of winds, which enhances sensible heat fluxes and facilitates horizontal heat transport. The resulting advection of warm air from the upwind northwest region plays a crucial role in triggering heatwave conditions over downwind areas of northern and central India. We further find that the downwind propagation of heatwaves is strongly dependent on the initial land surface temperature in the upwind region. Elevated land surface temperatures in northwest India induce anomalously low surface pressures, resulting in intensified wind speeds that enhance heat transport. As a result, heatwaves having high initial land surface conditions propagate more rapidly and are more likely to extend into central India. These results highlight the predictive potential of upwind land surface temperatures for the occurrence of heatwaves in downwind regions.
How to cite: Dar, J. A. and Apurv, T.: Understanding the influence of land surface conditions on the temporal evolution and spatial propagation of heatwaves in India, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-10671, https://doi.org/10.5194/egusphere-egu26-10671, 2026.
Accurate representation of land surface characteristics plays a crucial role in improving regional monsoon simulations. Recent studies demonstrate that irrigation in croplands positively influences rainfall; therefore, explicitly representing irrigated regions can lead to more accurate rainfall simulations. In this study, we employ the Weather Research and Forecasting (WRF v4.5) model to evaluate the performance of two land surface models (LSMs), Noah and Noah-MP, in simulating Southwest (SW) and Northeast (NE) monsoon rainfall over an irrigation-intensive region of India. Here, three simulations were conducted Noah, Noah-MP without irrigation, and Noah-MP with irrigation, using the National Remote Sensing Centre (NRSC) land use land cover (LULC) dataset for 2018-2019, which provides an updated representation of land cover over India. We implement the FAO irrigated fraction map, which serves as the default irrigation dataset in WRF v4.5. The model outputs were compared with the high-resolution regional reanalysis from the Indian Monsoon Data Assimilation and Analysis (IMDAA) of 12km resolution using statistical metrics such as root mean square error (RMSE) and mean bias. The results indicate that both LSMs reasonably capture the broad spatial and temporal characteristics of monsoon rainfall, albeit with varying levels of accuracy. These findings underscore the strong sensitivity of WRF rainfall simulations to both the land surface parameterization and the underlying land use representation, highlighting the importance of accurate region specific high resolution LULC data and LSMs for accurate monsoon rainfall modeling. The results demonstrate that irrigation alters land atmospheric interactions by inducing surface cooling and atmospheric moistening, which modify upper-level humidity, geopotential height, and wind patterns. These changes regulate convective activity differently across space and seasons, leading to regionally and temporally complex rainfall responses. This study provides guidance on selecting appropriate modeling schemes for irrigation-intensive, monsoon-focused simulations over the Indian region.
How to cite: Khobragade, P., Murugesan, K., and Narasimhan, B.: Simulating Indian Monsoon Rainfall over irrigation intensive regions using updated LULC and irrigation representation in WRF model, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-13817, https://doi.org/10.5194/egusphere-egu26-13817, 2026.
Agricultural irrigation can strongly modify land–atmosphere interactions and regional climate, especially in densely irrigated areas. The North China Plain, the largest irrigated region in China, has experienced significant irrigation-driven changes in local temperature, precipitation, and extreme events. Previous studies often oversimplify irrigation by assuming constant application rates or neglecting water resource limitations, which can lead to biased estimates of irrigation-induced climate effects. To address this, we developed an enhanced irrigation module within a land surface model (Common Land Model, CoLM), coupled with the Community Regional Earth System Model (CRESM), explicitly representing irrigation demand, water availability constraints, and application methods. Using this framework, we successfully reproduced observed surface temperature, precipitation, irrigation amounts, and crop yields across the North China Plain. Our results show that accounting for water-limited irrigation reduces the overestimation of the intensity and frequency of extreme events found in simulations that ignore resource constraints. Furthermore, considering irrigation water limitations alters the simulated regional temperature and precipitation patterns, which in turn affects projections of future agricultural water demand. This study demonstrates that explicitly accounting for water–agriculture interactions is essential for accurately simulating irrigation impacts, supporting more informed strategies for sustainable water and agricultural management under climate change.
How to cite: Liang, H., Zhang, S., and Dai, Y.: Revisiting irrigation impacts on the North China Plain: Accounting for water resource limitations, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-20958, https://doi.org/10.5194/egusphere-egu26-20958, 2026.
Heatwaves pose serious risks to human health and lives, but how their occurrence patterns may change under global warming remains unclear. Here we reveal a systematic westward shift of heatwave hotspots across the northern mid-latitudes around the late 1990s. Both observational analysis and numerical simulation show that this shift is caused by intensified soil moisture–atmosphere coupling (SAC) in eastern Europe, Northeast Asia and western North America under recent background warming. The strengthened SAC shifted the atmospheric high-amplitude Rossby wavenumber-5 pattern westwards to a preferred phase position, which increased the probability of the occurrence of high-pressure ridges over these 3 hotspots by a factor of up to 39. Our results highlight the importance of SAC in shaping heatwave patterns and large-scale atmospheric circulation and challenge the conventional view that the land surface only passively responds to atmospheric forcing.
How to cite: Zhang, K., Zuo, Z., Mei, W., Zhang, R., and Dai, A.: A westward shift of heatwave hotspotscaused by warming-enhanced land–aircoupling, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-353, https://doi.org/10.5194/egusphere-egu26-353, 2026.
Year-to-year variability in summertime temperature has a large impact on drought, wildfire, and extreme heat across the Western United States. A recent study showed that warmer-than-average summertime temperatures in the Western US are often preceded by drier-than-average springtime soil moisture over the Southwest US. To examine the possibility that land-atmosphere coupling modulates summertime temperature variability over this region, we perform an ensemble of soil moisture depletion experiments within the Community Earth System Model (CESM2) and find that reducing March surface soil moisture over the Southwest US causes positive May-June temperature anomalies throughout the Western US and precipitation anomalies in the Northwest that are consistent with observations. In our experiments, daytime diabatic heating over anomalously dry land surfaces in early spring excites circulation anomalies that evolve into a hemispheric-scale pattern similar to that observed following anomalously dry springtime in the Southwest US. We show that the subsequent late spring and early summer circulation anomalies are associated with large-scale reductions in atmospheric moisture and cloudiness that contribute to the near-surface warming. Our results suggest that spring soil moisture variations are a source of seasonal predictability for summertime climate extremes, through their non-local impact on summertime temperature variability over the Western US.
How to cite: Zhang, L. and Battisti, D.: Land-atmosphere Teleconnections Between Spring Soil Moisture and Summertime Climate, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-8398, https://doi.org/10.5194/egusphere-egu26-8398, 2026.
Climate extremes have direct impacts on ecosystems, for example reduced productivity during heat-drought events, but often their impact is amplified by compounding ecosystem disturbances, such as wildfires or insect outbreaks. Through their impact on ecosystem functioning and structure, compound climate extremes and ecosystem disturbances modulate land-atmosphere exchanges of water, energy, and greenhouse-gases, which in turn influence atmospheric properties from local to global scales, thus feeding-back to climate change. Recent observations indicate that such feedbacks are, however, non-negligible and might result in a much weaker role of the biosphere in climate change mitigation, especially under high emission scenarios.
Currently, ecosystem disturbances are not appropriately represented in most Earth System Models, which implies that extreme-event induced climate-biosphere feedbacks are likely overlooked in future climate simulations. Here, we will examine observation-based evidence for extreme-event induced climate-biosphere feedbacks through CO2 and land-atmosphere water and energy exchanges at different scales. We will then showcase recent developments in simulating some of these feedbacks in a global land-surface model and discuss the resulting implications for climate change adaptation and mitigation.
How to cite: Bastos, A., Cuesta-Valero, F. J., Jornet Puig, A., Linscheid, N., Ma, Y., Mayer, L., Martins Basso, J., and Quaas, J.: Climate extremes and ecosystem disturbance feedbacks, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-3005, https://doi.org/10.5194/egusphere-egu26-3005, 2026.
In this contribution, we aim at assessing the detectability of atmospheric water vapor uptake by dry soils at a variety of spatial scales and methodologies, from the ecosystem scale via eddy covariance, through larger scales via earth system models, and gridded products.
Water vapor fluxes in the soil and at the soil-atmosphere interface are driven by vapor concentration gradients. Until today, it is mostly assumed that the soil pore air is roughly at 100% relative humidity (RH), resulting in vapor fluxes that are almost always towards the atmosphere. However, the vapor state in soil pore air is linked to the soil water (matric) potential. As the water potential becomes more negative, the equilibrium RH within the soil decreases substantially. Under these conditions, the soil behaves like a ‘thirsty material’: when the atmospheric vapor pressure exceeds that of the soil pores, vapor is adsorbed onto the solid soil particle surfaces, and the net vapor flux is directed towards the soil.
Using subdaily measurement data from a globally distributed network of eddy covariance stations, we show an emergent functional relationship between volumetric water content (VWC), RH, and latent heat (λE) flux direction at the ecosystem scale. Vapor fluxes towards the soil under dry conditions can be explained by the soil's sorptive forces inducing very low water potentials. Based on eddy covariance data, we find that soil vapor adsorption most frequently occurred in arid and semi-arid regions, particularly in ecosystems with sparse vegetation such as savannas and dry shrublands. On average, soil vapor adsorption occurs for 4 ± 1.1 hours per night, and may last up to 7 hours and on more than 150 nights per year in some drylands.
Furthermore, we demonstrate that the relationship between VWC, RH, and the vapor flux direction is evident in a wide range of in situ measurements in drylands, including lysimeter and humidity profile data. However, this relationship is absent in site-level runs of gridded observation-based data products and land surface models.
We demonstrate for the first time that the effect of adsorptive forces can be detected at the ecosystem scale, several meters above the ground. Our findings at the operating scale of flux towers can be used to evaluate and improve model representation of land-atmosphere exchange in dry conditions. Additionally, the results highlight the influence of sorptive forces on sub-daily soil-atmosphere interactions, particularly in sparsely vegetated drylands.
How to cite: Paulus, S. J., Migliavacca, M., Hildebrandt, A., Orth, R., Lee, S.-C., Carrara, A., Reichstein, M., Zeng, Y., and Nelson, J. A.: The underestimated thirst: detectability of atmospheric water vapor uptake in ecosystem measurements and global models, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-7376, https://doi.org/10.5194/egusphere-egu26-7376, 2026.
Land use/land cover changes (LUC) modify local land surface properties that control the land-atmosphere mass, energy, and momentum exchanges. Through soil moisture and vegetation exchanges, land-atmosphere coupling contributes significantly to the evolution of extreme events like heat waves and forest fires. However, these interactions are still unsatisfactorily explored at regional scales under future climate scenarios.
Here, we investigate these processes using newly performed Weather Research and Forecasting (WRF v4.5.1.4) simulations under the SSP3-7.0 scenario, conducted within the EURO-CORDEX and LUCAS Phase 2 regional climate simulation ensembles. Both simulations use the LANDMATE Plant Functional Type (PFT) land cover dataset for Europe, in the first the landcover is kept constant using the 2015 map, while in the second, the land-use evolves annually according to the Land Use Harmonization dataset protocol for SSP3-7.0 scenario.
The impact of temperature–evapotranspiration coupling is assessed using a coupling metric defined as the product of normalised variables, allowing differences across regions and simulations to be examined consistently. The analysis focuses on the coupling between extreme heat (TX90p) or heat waves (defined as TX90p persisting for at least five consecutive days) and evapotranspiration (LH) or soil moisture (SMOIS), expressed through the metrics TX90p×LH and TX90p×SMOIS. Values lower than −1 indicate concurrent deficits in LH (or SMOIS), corresponding to a decoupled land–atmosphere regime. Conversely, values greater than 1 indicate strong land–atmosphere coupling.
The compound effects of extreme coupled and uncoupled events on future meteorological fire danger indices (FWI and FWIe) are analysed for both simulations, enabling a quantitative assessment of the sensitivity of future fire danger to combined climate and land-use changes.
Acknowledgements
The authors wish to acknowledge the financial support from the Portuguese Fundação para a Ciência e Tecnologia (FCT, I.P./MCTES) through national funds (PIDDAC): LA/P/0068/2020 - https://doi.org/10.54499/LA/P/0068/2020, UID/50019/2025, https://doi.org/10.54499/UID/PRR/50019/2025, UID/PRR2/50019/2025.
L.C.S. and R.M.C. also acknowledge individual funding from FCT, I.P./MCTES grants https://doi.org/10.54499/UI/BD/154675/2023, and https://doi.org/10.54499/2021.01280.CEECIND/CP1650/CT0006.
How to cite: Cardoso, R. M., Santos, L. C., Navarro, J., Bustamante, E. G., González Rouco, J. F., Camara, C. C., and Soares, P. M. M.: How do future land-use changes jointly influence summer land–atmosphere coupling and fire danger across Europe?, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-20768, https://doi.org/10.5194/egusphere-egu26-20768, 2026.
The aim of this study is to investigate the effect of land surface conditions on cloud occurrence by quantifying how they modulate the influence of large-scale meteorological conditions.
The land surface can modulate clouds through its influence on surface heat fluxes, local moisture availability, and surface roughness. However, quantifying these effects from observations remains challenging, as the temporal and spatial variability of cloud occurrence is large and influencing factors covary.
Here, we employ a convolutional neural network (CNN) to predict satellite-observed cloud fraction over Europe for the period 1983–2020. Cloud fraction is taken from the CM SAF Cloud Fractional Cover dataset based on Meteosat First and Second Generation observations (COMET). Predictors are derived from the ERA5 reanalysis, including ERA5-Land as well as ERA5 fields on single and pressure levels. To delineate the land surface impact on cloud occurrence predictability, we develop two model configurations: one driven solely by large-scale meteorological conditions, and a second one that additionally incorporates land surface variables. Both models achieve high predictive skill (R² > 0.8), with a slight increase in performance when land surface conditions are included. Sensitivity analyses using permutation feature importance and partial dependency indicates that cloud occurrence is primarily controlled by large-scale meteorological drivers, while soil moisture and surface sensible heat flux emerge as the most influential land surface variables.
Future work will use this framework to quantify the impact of land cover change on cloud occurrence and extend the framework beyond Europe.
How to cite: Pauli, E., Andersen, H., Nowack, P., and Cermak, J.: Quantifying Land-Surface Effects on Cloud Occurrence Using Neural Networks, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-17132, https://doi.org/10.5194/egusphere-egu26-17132, 2026.
Terrestrial energy, water and carbon exchanges are regulated by the strength and sign of the coupling between the land surface and the atmosphere. Simulating this land-atmosphere coupling is crucial for realistic weather and climate projections and, especially, to anticipate the evolution of extreme events. After an exploration of the metrics and datasets available for studying land-atmosphere coupling at different temporal and spatial scales, we demonstrate that uncertainties in data products based on in-situ measurements, remote sensing data, and Earth System Model simulations remain large. The evaluation of model simulations according to a variety of land-atmosphere coupling metrics reveals large structural uncertainties in comparison with the small effect of internal variability on land-atmosphere coupling. We show that reducing uncertainties in available Earth Observations (EO) products for studying land-atmosphere coupling is also necessary. This could be done by collecting long-term measurements at the land surface and implementing more observational and physical constraints in the algorithms used to derive EO products. The availability of more accurate, physically consistent EO products with an accurate representation of land-atmosphere coupling will in turn help to develop the future generation of Earth System Models.
How to cite: García-García, A., Cuesta-Valero, F. J., Bastos, A., Orth, R., and Peng, J.: Uncertainties in land-atmosphere coupling still a big obstacle for accurate climate projections, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-19261, https://doi.org/10.5194/egusphere-egu26-19261, 2026.
The El Niño event exerts a profound influence on the global carbon cycle by perturbing terrestrial photosynthesis through environmental stress. Plant isoprene emissions respond rapidly to such environmental stress, yet it remains unclear whether isoprene can capture the spatiotemporal evolution of El Niño. Here, we used satellite-derived global isoprene emissions for the first time to assess their dynamical response to the 2015–2016 El Niño. We observed that isoprene emissions increase by up to ~30% relative to the climatological mean, with pronounced anomalies emerging across tropical ecosystems. The spatiotemporal evolution of these anomalies closely aligns with the El Niño progression, as indicated by sea surface temperature anomalies in the equatorial Pacific. In contrast, commonly used satellite vegetation products, including leaf area index (LAI) and solar-induced chlorophyll fluorescence (SIF), exhibit weaker and spatially incoherent responses. These results demonstrate that satellite-derived isoprene provides a sensitive and mechanistically grounded tracer of ecosystem stress, offering a complementary perspective for monitoring the impacts and propagation of extreme climate events on terrestrial ecosystems.
How to cite: Liu, H., Prentice, I. C., and Morfopoulos, C.: Satellite‐derived isoprene emissions trace the spatiotemporal evolution of the 2015-2016 El Niño across terrestrial ecosystems, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-2949, https://doi.org/10.5194/egusphere-egu26-2949, 2026.
Irrigation represents one of the most critical human interventions on the coupled water and energy cycles, driving substantial climate impacts via modifying surface energy balance and biogeochemical process. As irrigated farmland continues to expand, understanding the climate impact of extensive irrigation becomes increasingly important. Yet, the effect of irrigation on rainfall patterns, particularly extreme rainfall, at global scale remains poorly unclear. Here, using the “space-for-time” approach and global satellite precipitation datasets, we show that extreme rainfall events occur more often over irrigated lands than in surrounding rainfed areas. This signal is more pronounced in regions with more extensive irrigation, warmer temperatures, and higher precipitation. Our results improve mechanistic understanding of irrigation-precipitation interactions, which remain uncertain in climate and weather forecasting models.
How to cite: Liu, Y. and Li, Y.: Observational evidence of increased extreme rainfall due to irrigation practice, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-8906, https://doi.org/10.5194/egusphere-egu26-8906, 2026.
Since the 1980s, the central United States and southern-central Canada have experienced a notable lack of high temperature extremes, with many temperature record highs from the 1930s Dust Bowl period still standing. By contrast, atmospheric general circulation models (AGCMs) forced with observed sea surface temperatures consistently simulate exceptional warming over the central US during this period. What accounts for this discrepancy between observed and simulated temperature trends? We use ensembles of coupled and atmosphere-only climate model experiments to disentangle the influences of remote sea surface temperatures and local land-atmosphere interactions on historical temperature change in the central United States. Tropical Pacific teleconnections strongly impact central US temperatures: coupled general circulation models, which cannot reproduce observed trends in the tropical Pacific SST gradient, produce a moderate central US warming trend that is closer to observations than AGCMs prescribed with observed SSTs. Comparing seasonal latent and sensible heat fluxes in these experiments, we describe the central role of turbulent exchanges at the land surface on temperature trends. In a heavily irrigated area whose climate is known to be sensitive to changes in soil moisture, our results point to a possible role for agricultural irrigation in alleviating historical heat extremes, and in explaining the large difference between models and observations. We highlight the importance of understanding model-data discrepancies in tropical SST patterns and local land temperatures for predicting future climate extremes in the central US.
How to cite: Menemenlis, S., Vecchi, G., Fueglistaler, S., Yang, W., and Yang, Q.: Has agricultural irrigation masked intense warming in the central United States?, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-8485, https://doi.org/10.5194/egusphere-egu26-8485, 2026.
Energy fluxes between the surface and the atmosphere are known contributors to the genesis and the amplification of temperature extremes: a classic example is the enhancement of land-to-atmosphere sensible heat fluxes during heatwaves over dry soils, boosting the already high surface temperatures to extreme values. Recent work on the Lagrangian analysis of temperature extremes has pinpointed that, in some specific continental regions, diabatic processes do not just act as amplifiers, but play a dominant role in the genesis of positive and negative extreme temperature anomalies. This observation suggests a distinction between world regions where extremely warm or cold air masses are locally generated by non-adiabatic processes, acting as warm or cold air "reservoirs", and other neighboring regions where such extreme air masses are exported adiabatically by the large-scale circulation.
In this work we propose a methodology to identify, in the ERA5 reanalysis data set, the surface energy balance regimes that correspond to the local generation of hot and cold air during summer and winter, respectively, and to separate them from cold/warm air advection regimes. The generation of cold air during winter is favored during clear, calm nights over continental or ice-covered regions, that leads to sustained radiative cooling. The regions where such conditions are most frequent are Siberia and the Canadian Arctic, which can be depicted as the two "boreal cold air reservoirs" of the northern hemisphere. Hot air generation during summer is more geographically spread than cold air, but occurs more frequently in subtropical areas including regions surrounding the Mediterranean Sea.
The framework is illustrated in detail through two case studies. The first is a cold air outbreak that affected eastern Asia during January 2023, which led to the new absolute negative temperature record for China. This event was preceded by particularly favorable conditions for cold air generation over northern Siberia. The second is the July 2022 heatwave, that led to temperatures exceeding 40°C over central England. In this case, a Lagrangian analysis suggests that the extremely high temperatures were related to strong diabatic heating not over the British Isles, but over the Iberian Peninsula in the days preceding the event.
How to cite: Riboldi, J. and Schnyder, F.: A framework to characterize the contribution of upstream land-atmosphere interactions to cold spells and heatwaves, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-20181, https://doi.org/10.5194/egusphere-egu26-20181, 2026.
Posters on site: Tue, 5 May, 16:15–18:00 | Hall X5
Vegetation plays a crucial role during heatwaves by altering surface energy partitioning and influencing local to regional climate. In addition to the thermodynamic response of vegetation, the differential heating caused by sensible heat gradients across adjacent regions of vegetation and dry, bare soil can generate a mesoscale circulation akin to sea breeze-like circulation, known as a ‘vegetation breeze’1, which redistributes heat and moisture and affects downwind regions. While the impacts of large‑scale heterogeneities such as land-sea contrasts and topography are well established, the influence of finer‑scale vegetation heterogeneity remains uncertain. This gap is critical because semi‑arid forests, covering nearly 18% of Earth’s land surface, are highly sensitive to heat extremes. Differences in their Bowen ratios can substantially alter surface energy budgets, producing varying levels of hydroclimatic stress under similar atmospheric forcing. Yet, their potential to amplify or mitigate the impacts of extreme heat events is still poorly understood.
This study focuses on the semi-arid deciduous forests of the Eastern Ghats in Peninsular India, which are part of the Nagarjulam Srisilam Tiger Reserve and neighbouring protected areas located along the ecotone between the dry Deccan Plateau and the Eastern coast. It is spread over 5 districts in Andhra Pradesh and Telangana which are known to experience extreme heatwaves. Our previous observational analyses show that these transitional forests are highly sensitive to climatic stressors, particularly through their land surface temperature (LST) and evapotranspiration responses. During heatwave events, we observed pronounced LST gradients between forested and adjacent non-forested areas, indicating strong surface thermal contrasts arising from vegetation-atmosphere interactions. Given the heightened climate sensitivity of these transitional ecosystems, it is essential to understand not only how these ecosystems respond to extreme heat but also how they may influence local atmospheric dynamics.
To address this, we investigate how vegetation driven circulations such as the ‘vegetation breeze’ and the canopy convector effect2 emerge from land surface heterogeneity, and how these processes affect boundary layer processes and downwind thermal anomalies during heatwaves. Our approach combines atmospheric reanalysis data for large‑scale boundary conditions, satellite observations to characterize land surface and vegetation, and high‑resolution WRF simulations to resolve fine‑scale forest-atmosphere feedbacks. Through a series of forest‑configuration experiments, we assess the capacity of semi‑arid forests to alter boundary layer processes and explore the implications for local and regional modification of extreme events as well as downwind impacts. By isolating the role of semi‑arid forests during heatwaves, these experiments contribute to the mechanistic understanding of semi-arid forest-atmosphere interactions and their role in shaping hydroclimatic extremes under a changing climate.
References
[1] McPherson, R. A. (2007). A review of vegetation—atmosphere interactions and their influences on mesoscale phenomena. Progress in Physical Geography, 31(3), 261-285.
[2] Banerjee, T., De Roo, F., and Mauder, M.: Explaining the convector effect in canopy turbulence by means of large-eddy simulation, Hydrol. Earth Syst. Sci., 21, 2987–3000, https://doi.org/10.5194/hess-21-2987-2017, 2017.
How to cite: Sen, D. and Monteiro, J.: Vegetation-Driven Circulations and Their Modification During Heatwaves: Insights into the Downwind Impacts of Semi-Arid Forests in Peninsular India, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-945, https://doi.org/10.5194/egusphere-egu26-945, 2026.
Extreme heat stress events are marked by significant deviations in surface air temperature that surpass the typical climatological range, coupled with increased atmospheric humidity. These events are characterised by their intensity, duration, and spatial extent, often crossing thresholds critical for both human and terrestrial ecosystem functioning. At the local scale, land-atmosphere interactions during these heat extremes modulate stress on soil and vegetation by altering energy partitioning, boundary layer feedbacks, and soil moisture memory. During these episodes, evapotranspiration is constrained due to low soil moisture (SM) conditions, leading to increased sensible heat and temperatures, which serve as the primary thermodynamic pathway for heat amplification. In conditions characterized by high soil moisture (SM), light precipitation (P) occurs, with an increase in latent heat flux may elevate atmospheric humidity and exacerbate heat stress, underscoring the nonlinear and stress-dependent nature of SM–P interactions. Despite the centrality of these processes, the relationship between SM and P across diverse heat stress regimes in South Asia remains insufficiently explored.
In this study, the Weather Research and Forecasting (WRF) model is employed to simulate an extreme heat stress event that occurred in May 2015 in the Indo-Gangetic Plains of India, utilizing initial and boundary conditions from the ERA5 dataset. To examine the SM-P feedback relationship, the initial SM is perturbed by 25% and 50% to represent a full spectrum of heat stress conditions (no stress, caution, danger, and extreme danger). Under no-stress conditions, the SM-P feedback exhibits a typical convex-concave relationship on the E[PSM] curve. However, as the heat stress intensifies, this relationship is broken. Extremely hot and deeply mixed boundary layers inhibit the development of moist convection, raising the lifting condensation level (LCL). Although cloud formation may still occur, the environmental conditions are insufficient to trigger heavy precipitation. The presence of upper-level anticyclones during this time period further suppresses vertical motion, reinforcing atmospheric stability and preventing convective initiation. Overall, the analysis highlights that an intermediate soil moisture range of approximately 0.25–0.35 m³/m³ maximizes land–atmosphere coupling strength in the IGP during extreme heat events. Within this range, the surface is sufficiently moist to sustain strong evapotranspiration yet dry enough to produce high surface temperatures, creating a feedback loop that exacerbates heat stress. These findings underscore the importance of accurately representing soil moisture dynamics in regional climate models to improve predictions of heat extremes in South Asia.
How to cite: Saha, M., Dixit, V., and Lanka, K.: Analysis of the Relationship Between Soil Moisture and Precipitation Across Heat Stress Categories, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-1052, https://doi.org/10.5194/egusphere-egu26-1052, 2026.
Although urban irrigation can modulate local hydrothermal conditions and mitigate urban heat island effects, its impact on moist heat stress (MHS) is poorly understood. Employing the Weather Research and Forecasting Single-Layer Urban Canopy Model (WRF-SLUCM), we evaluated the effect of urban irrigation on the MHS in Beijing, China Using the CMA-RA V1.5 reanalysis dataset and CLDAS-V3.0 soil moisture as boundary conditions. Taking the hot and humid weather events that occurred in Beijing in May and August 2022 as examples,we found that the updated initial soil moisture (SM) field improved the simulation of temperature, relative humidity, and wind speed. Besides, urban irrigation reduced urban and rural MHS, and particularly reduced afternoon and evening MHS by up to 1.2 °C but increased morning MHS by up to 0.4 °C. In addition, the effect of different irrigation times on MHS showed that irrigation at 02 and 20 h increased urban and rural MHS, with the best cooling effect at 00 and 13 h, which reduced the MHS by up to 2.65 °C in urban areas and 0.71 °C in rural areas. The findings highlighted mechanistically the effect of urban irrigation on MHS and shed light on how to mitigate urban heat island effects on urban sustainable development.
How to cite: Sun, S., Shi, C., Zhang, Q., Zhang, T., and Gu, J.: Urban irrigation reduces moist heat stress in Beijing, China, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-4364, https://doi.org/10.5194/egusphere-egu26-4364, 2026.
The impacts of deforestation over the Maritime Continent (MC) have increasingly raised concerns due to its potential influence on extreme rainfall during the early summer monsoon. This study investigates how MC deforestation modifies extreme rainfall characteristics and associated large-scale circulation responses during May–June (MJ) using 100-year simulations from the Community Earth System Model (CESM1). A control simulation is compared with a deforestation experiment in which MC forests are replaced by grassland, and rainfall changes are quantified using indices defined by the Expert Team on Climate Change Detection and Indices (ETCCDI). Results show that deforestation substantially enhances extreme rainfall over the MC and induces a pronounced rainfall regime shift from weakened light rainfall toward strengthened heavy rainfall, driven by increased atmospheric instability and intensified deep convection. In contrast, rainfall over South China-Taiwan (SCTW) decreases significantly, with both light and extreme rainfall being suppressed. Mechanism analyses indicate that enhanced MC convection induces a meridional circulation response, characterized by anomalous ascent over the tropics and subsidence over SCTW. This subsidence causes tropospheric stabilization, reduced cloud cover, and weakened southwesterly monsoon moisture transport, creating unfavorable conditions for rainfall development over SCTW. Overall, MC deforestation drives a coherent redistribution of early summer monsoon rainfall, featuring an extreme rainfall-dominated regime shift over the MC and circulation-induced rainfall suppression over subtropical East Asia, highlighting the role of tropical land-use change in modulating extreme rainfall and monsoon circulation during the early summer monsoon.
How to cite: Chen, Y.-C. and Huang, W.-R.: Maritime Continent Deforestation-Induced Extreme Rainfall Regime Shifts During the Early Summer Monsoon Season, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-4627, https://doi.org/10.5194/egusphere-egu26-4627, 2026.
Heatwaves are becoming more frequent and intense worldwide under ongoing climate warming, posing substantial risks to the terrestrial ecosystem carbon sink. Although heatwave impacts on gross primary productivity (GPP) and ecosystem respiration (ER) have been widely investigated, their causal interactions remain poorly understood, particularly the physiological and biochemical mechanisms underlying these responses. Here, we combine near-surface air temperature from the ERA5-Land reanalysis with long-term carbon flux estimates from FLUXCOM-X to investigate ecosystem carbon responses to heatwaves across biome-diverse sites globally. We identify bidirectional causal relationships between GPP and ER using convergent cross mapping and apply multivariate causal inference to quantify heatwave-induced changes in ecosystem physiological and biochemical traits. Results suggest that the bidirectional causal coupling between GPP and ER is significantly strengthened during heatwaves but weakens during the post-heatwave recovery, indicating a transient reorganization of ecosystem carbon dynamics as a legacy effect of heatwaves. Correspondingly, net ecosystem productivity (NEP) typically declines during heatwaves, reflecting a widespread transient loss of carbon sink strength, driven by a disproportionately stronger increase in ER relative to GPP. Our findings illustrate the vulnerability of the land carbon sink to heatwaves consistent with previous studies, while explicitly unravelling the causal processes that govern ecosystem carbon responses and recovery. These results provide important insights for the management of the global carbon budget and for advancing the representation of terrestrial processes in land surface models.
How to cite: Ping, J., Lee, S.-C., and Li, W.: Asymmetric causal coupling between ecosystem photosynthesis and respiration underlies ecosystem carbon sink losses during heatwaves, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-6000, https://doi.org/10.5194/egusphere-egu26-6000, 2026.
Global warming is expected to increase the likelihood of the rapid onset of drought development. Yet the timescale and region of the emergence and disappearance of the anthropogenic flash drought remain poorly constrained. Here, we assess the time of emergence and disappearance of soil-moisture-based flash drought across five onset timescales using a large ensemble of climate simulations. Anthropogenic influence is quantified through the Signal-to-Noise Ratio, defined as the forced response relative to internal climate variability. Rapid-onset FDs of 1 and 2 pentads onset timescale emerge earliest, in the mid-20th century, and expand over increasing land areas by the late century under SSP3-7.0. In contrast, moderate- to slow-onset FD, 3 to 5 pentads onset timescale emerge later in more spatially confined regions and disappear by 2100. The Time of disappearance patterns show broader regional variability, especially for slow-onset flash drought. Globally, median ToE occurs in the 2020s for rapid-onset flash drought and in later decades for longer-onset events, while disappearance occurs between the 2000s and 2050s, depending on onset timescales. Both emergence and disappearance exhibit strong regional variability and occur earlier under higher forcing. Mechanistically, Flash drought onset is governed by region-specific land–atmosphere processes, driven either by short-term precipitation deficits or rapid increases in evaporative demand. These results indicate an increasing tendency toward rapid, climate-driven flash drought emergence, emphasizing the need for region-specific early-warning strategies.
How to cite: Ravinandrasana, P. V., Franzke, C., and Raible, C.: Climate Warming Favors the Early Emergence of Rapid Flash Drought, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-7512, https://doi.org/10.5194/egusphere-egu26-7512, 2026.
The spatiotemporal coupling between soil moisture and precipitation is a fundamental pillar of the global hydrological cycle. With the escalating risk of severe droughts and pluvial extremes, a critical question arises: whether observed variations in soil moisture and precipitation coupling are the result of anthropogenic Forced Response (FR) or Internal Variability (IV). While recent benchmarks, such as the Forced Component Estimation Statistical Method Intercomparison Project, have advanced the estimation of forced components from observational data, a significant gap remains: how to leverage these diagnostic tools to elucidate the non-stationary and non-linear interactions across the full moisture spectrum.
This study introduces a statistical attribution framework that reconciles stationary and non-stationary coupling regimes, allowing for a more robust characterization of shifting climate dynamics. We extend the analysis of direct impacts—where FR and IV drivers linearly alter coupled variables—to the assessment of indirect impacts, where drivers exert non-linear influence on mediating variables, which modulate the dynamic sensitivity and strength of the coupling mechanisms. By decoupling these pathways, we move beyond the simple attribution of trends in moisture states; instead, we identify how anthropogenic forcing and internal variability are fundamentally restructuring the feedback mechanisms of the hydrological cycle.
How to cite: Zhang, M., Huang, F., Gavrilov, A., Mankovich, N., Fernández-Torres, M.-Á., and Camps-Valls, G.: Identifying the Restructuring of Forced Responses and Internal Variability in Soil Moisture–Precipitation Coupling Mechanisms, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-8630, https://doi.org/10.5194/egusphere-egu26-8630, 2026.
A notable ecological phenomenon in northern terrestrial ecosystems, known as "the asymmetric response of vegetation to precipitation", has emerged over the past 20-plus years. However, it remains uncertain whether the response of northern terrestrial ecosystems to driving factors are temporally synchronous or has exhibit heterogeneity, and whether these impacts have been quantitatively evaluated. Here, we analyze the spatio-temporal patterns of vegetation sensitivity to precipitation (Sppt) across the NTML from 2001 to 2023, using two independent proxies of vegetation productivity–gross primary productivity (GPP) and solar-induced chlorophyll fluorescence (SIF). We confirm a pronounced asymmetry in Sppt trends between Eurasia and North America. Sppt increased significantly across Eurasia (GPP: +3.2×10-3 g·C·m-2·mm-1·yr-1) but decreased in North America (GPP: -3.8×10-3 g·C·m-2·mm-1·yr-1). Moisture budget diagnostics reveal asymmetric roles of zonal moisture transport in shaping precipitation trends over the two regions. This asymmetry is primarily driven by changes in hydro-thermal heterogeneity, which collectively modulate moisture availability and plant physiological processes. Crucially, further results from machine learning attribution analysis indicate that diurnal temperature range dominates Sppt changes across more than 23.5% of Eurasia, while precipitation is the key driver over 22.5% of North America. Our findings highlight the critical role of hydro-thermal heterogeneity in regulating vegetation–climate feedback and underscore the necessity of incorporate regional asymmetries into future Earth system models.
How to cite: Li, T., Zi, P., Zhang, W., and Yang, R.: Hydro-thermal heterogeneity contributes to the asymmetry of vegetation sensitivity to precipitation across northern mid-latitudes, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-8794, https://doi.org/10.5194/egusphere-egu26-8794, 2026.
Insect-driven forest disturbances are important contributors to tree mortality and biomass losses in temperate and boreal regions. With the rising temperatures and shifting precipitation patterns, insect induced tree mortality is expected to increase in many regions. Insect outbreaks not only influence tree cover and carbon stocks, but , through their impact on tree functioning, also influence land-atmosphere exchanges of water and energy, which in turn can impact atmospheric properties. While insect outbreaks can impact very large regions, most observational studies focus on small regions and individual events.
Here, we aim to provide an observation-based regional synthesis of the impact of insect-driven tree mortality on land-atmosphere water and energy exchanges, focusing on western USA. For this, we analyse satellite-based data (MODIS) on evapotranspiration (ET), albedo, land-surface temperature (LST) and snow cover for insect-affected regions between 2001-2022. Preliminary results indicate an increase in summer LST in areas affected by more severe insect-driven tree mortality, along with a decrease in ET, compared to the years before the mortality events. These differences can be partly explained by reduced snow cover in winter, which contributes to decreased winter albedo in insect-affected areas. These effects are not only limited to the outbreak event, but also show persistent trends in the subsequent years.
How to cite: Martins Basso, J. L., Cuesta-Valero, F. J., Quaas, J., and Bastos, A.: Impacts of insect-driven tree mortality on land-surface water and energy exchanges, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-10059, https://doi.org/10.5194/egusphere-egu26-10059, 2026.
Carbon fluxes play an important role in the Earth System, influencing climate, vegetation dynamics, and biogeochemical cycles. Accurately simulating these fluxes using Earth System Models is essential to understand and predict future climate change. However, these simulations depend on often poorly represented characteristics like small-scale landscape heterogeneities as well as small-scale variations in surface hydrology and temperature, which can impact carbon processes.
In this study, we analyze simulations performed with the ICON climate model, focusing on recent enhancements to its land surface component, ICON-Land. The modifications aim for a better represention of small-scale heterogeneities by introducing distinct tiles within each grid cell that represent local states of moisture and temperature and can exchange water and heat fluxes between each other. The characteristics of these tiles are derived from high resolution topographical data. These improvements are expected to capture soil moisture and temperature dynamics - which are key drivers of carbon processes - in a more realistic way.
Our preliminary results, which are derived from simulations with prescribed atmospheric forcing, indicate that the improved representation of landscape heterogeneities in ICON-Land affects its hydrology and carbon processes. Specifically, we see an increase in soil moisture and evapotranspiration as well as Gross Primary Productivity and soil respiration in our simulations. These changes demonstrate that the improved model has a significant effect on interactions between the land surface and the atmosphere, and thereby might affect the global carbon cycle.
This study highlights the importance of representing small-scale landscape features in climate models and demonstrates the potential of the enhanced ICON-Land model to improve the simulation of carbon processes. Further analysis is underway to comprehensively assess the impacts of these modifications on the global carbon budget and fully-coupled climate projections.
How to cite: Stacke, T., de Vrese, P., Gayler, V., Bergstedt, H., von Baeckmann, C., Kleinen, T., and Brovkin, V.: Enhanced Representation of Landscape Heterogeneities in ICON-LAND: Implications for Hydrology and Carbon Processes, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-10824, https://doi.org/10.5194/egusphere-egu26-10824, 2026.
Terrestrial carbon dioxide removal (CDR), including afforestation and reforestation (A/R) and other land-based approaches, is a key element of climate mitigation pathways consistent with the Paris Agreement. While the mitigation potential and Earth system responses to terrestrial CDR deployment have been increasingly explored, its influence on land–atmosphere coupling and temperature extremes remains underexplored, particularly at regional scales. Understanding these processes is essential for evaluating both synergies and trade-offs associated with land-based mitigation strategies, including potential implications for biogeophysical co-benefits, resilience, and permanence.
Here, we present a spatio-temporal explicit analysis of how terrestrial CDR pathways modify land–atmosphere coupling and associated hot extremes across regions and seasons. The analysis is based on emission-driven simulations from the fully coupled MPI Earth System Model and considers a range of future scenarios that include both stylized large-scale terrestrial CDR deployment and more realistic mitigation pathways developed within CDRSynTra, LAMACLIMA, and RESCUE projects. This scenario diversity allows us to explore the robustness, plausibility, and potential non-linearities of land–atmosphere responses to terrestrial CDR. The scenarios considered include large-scale A/R aligned with national pledges, transformation pathways characterized by global sustainability and global inequality, and climate stabilization pathways with and without temperature overshoot that rely on portfolios of multiple CDR approaches.
We apply various land–atmosphere coupling diagnostics, such as measures of soil-moisture control on latent and sensible heat fluxes, and relate these to hot-day and heatwave metrics over land to assess the processes linking surface fluxes, moisture availability, and temperature extremes. By explicitly focusing on regional responses, the analysis captures spatial heterogeneity in land–atmosphere feedbacks that is not apparent in global-mean assessments. Seasonal variability (e.g., during spring and summer) and different future time horizons (near-, mid-, and late-century; before and after overshoot), are considered to assess the sensitivity of land–atmosphere coupling processes to the timing and magnitude of the application of terrestrial CDR.
Identifying regions where terrestrial CDR strongly modifies land–atmosphere coupling and heat extremes can help highlight hotspots for targeted monitoring and evaluation by indicating where observations and diagnostics are most relevant for tracking biophysical responses and emerging risks. Analyses indicate that regions such as Scandinavia, West Asia, and Northeast China exhibit contrasting responses, where changes in heat extremes coincide with shifts in soil-moisture control and evaporative cooling, and where observational coverage of surface fluxes remains limited. Such regional insights can also inform the assessment of where terrestrial CDR deployment may be associated with co-benefits, and where land–atmosphere feedbacks could pose challenges or limitations, including adaptation-relevant impacts on heat stress and labor productivity. Overall, this work helps fill a key gap in current assessments by explicitly linking terrestrial CDR deployment to land–atmosphere coupling and heat extremes at regional scales, and by providing a process-based assessment framework that can support risk-aware evaluation of land-based CDR strategies and be extended to other terrestrial CDR approaches.
How to cite: Gupta, S., Moustakis, Y., Havermann, F., and Pongratz, J.: Regional perspective of terrestrial carbon dioxide removal on land-atmosphere coupling and heat extremes, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-12254, https://doi.org/10.5194/egusphere-egu26-12254, 2026.
How to cite: Giordano, V., Staal, A., Tuninetti, M., Laio, F., and Ridolfi, L.: Contribution of evaporative sources and atmospheric circulation to the spatiotemporal variability of moisture transport, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-13807, https://doi.org/10.5194/egusphere-egu26-13807, 2026.
Over the past three decades, the Mediterranean region has experienced an increasing frequency and duration of drought events, a trend that is projected to intensify as anthropogenic emissions continue to rise. Available evidence indicates that drought conditions can trigger extensive tree mortality, amplify wildfire risk, and drive a progressive shift from Mediterranean ecosystems toward vegetation characteristic of semi-arid regions. The role of vegetation and land-use change in climate modelling is fundamental for estimating surface energy fluxes and carbon budgets. Land-use and land-cover changes (LULCCs) can alter surface energy and water fluxes, potentially leading to different responses in mean and extreme temperature and precipitation based on different representation of the vegetation. Apulia, in southeastern Italy, is an ideal case study, having experienced massive olive tree die-off due to Xylella fastidiosa, an invasive pathogen detected in 2008. This vegetation loss is compounded by increasing drought impacts. This case offers a unique case study to assess the consequences of extensive olive trees die-off after the spread of the pathogen/bacteria Xylella fastidiosa. In order to assess potential impacts of significant change in vegetation covers, we investigated the effect of die-off and of massive replanting on the regional climate. The study involves two vegetation scenarios (deforestation and reforestation) performed with four sensitivity experiments at 12 km horizontal resolution with two different regional models: RegCM5 and CRCM/GEM4.8. Two experiments will serve as references for present-day (PD, 1990-2019) and future (2071-2100), while other two future experiments will be performed under both vegetation change scenarios. The percentage of plant functional types in the land component (CLM4.5) of RegCM was replaced with that used in the CRCM/GEM4.8 simulations. Preliminary results show that while temperature extremes can be exhacerbated by rewilding, increasing tree cover can help to keep soil moisturised, acting against the progressive aridification of the area. On the other hand, the deforested case leads to a decrease in daily maximum temperature, particularly in Fall and Winter and an increase in daily minimum temperature in Summer. These changes are driven by albedo feedback related to the land-use modification.
How to cite: D'Agostino, R., Ingrosso, R., Cozzoli, F., Sgrigna, G., Nestola, E., Pausata, F., Lionello, P., and Bordoni, S.: Vegetation–atmosphere feedback in the Mediterranean region from Regional Climate Model simulations: the Apulia case study, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-17634, https://doi.org/10.5194/egusphere-egu26-17634, 2026.
High temepratures can impose different effects on soil mositure drought development depending on their hit timing. Based on the reanalysis soil moisture data, we identified the duration of soil moisture drought onset (defined as the time period for moisture to transition from a normal state to below-average condition), and designed a random forest based experimental framework to measure how rapidly soil mositure drought develops under varied high temeprature conditions in China. Results show that the duration of soil mositure drought onset would be shorten by 10-50 days under high temperatures in relative to that of annual mean temperature scenarios. With regard to the timing of high temepratures, the associated impacts were the greatest for high temperatures of 1 month prior to soil moisture drought occurrence. In densely vegetated areas, pre-drought high temperatures played positively in accelerating the formation of soil moisture drought. In sparse vegetated areas by contrast, post-drought high temperatures contributed to the ongoing development of soil drought. The findings show the asymmetrical impacts of pre-drought and post-drought high temperatures on soil drought development, which may provide some references for improving the understanding of soil moisture drought mechanism in a warming future.
How to cite: Zhu, Y., Zhang, X., Liu, Y., Xu, B., and Zhang, L.: Impacts of high temperatures with varied hit timing on soil moisture drought, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-17995, https://doi.org/10.5194/egusphere-egu26-17995, 2026.
Rapid warming of the Arctic is increasingly being linked to climate extremes such as heat waves, droughts, and wildfires, which are fundamentally altering the functioning of ecosystems, the dynamics of the carbon cycle, and the interactions between land and atmosphere in the Arctic. Increasing evidence suggests that high-latitude extreme events rarely occur in isolation but are frequently embedded within compound climate extremes. These multivariate events can strongly modify land surface states, through changes in soil moisture, vegetation structure, surface energy balance, and fire disturbance, and thereby influence carbon exchanges between the land and atmosphere. However, the extent to which compound climate extremes amplify or modulate Arctic carbon-cycle extremes in the future remains poorly constrained.
In this study, we investigate how compound climate extreme events shape the evolution of Arctic carbon-cycle extremes under future Arctic warming. Using large ensemble simulations with the Community Earth System Model version 2 (CESM2), which has demonstrated skill in representing Arctic climate processes, fire dynamics, and fire-weather interactions, we assess the evolution of extreme events in gross primary productivity, ecosystem respiration, and net ecosystem carbon balance throughout the 21st century. A multivariate statistical framework is applied to explicitly characterise compound extremes involving fire activity, heat waves, and droughts, and to qualify and quantify their combined impacts on land-atmosphere carbon flux variability in the Arctic. By linking compound climate drivers to ecosystem carbon responses, this work advances our understanding of how land surface conditions regulate extreme carbon-cycle behaviour in a rapidly changing Arctic.
How to cite: Fiedler, L., Barkhordarian, A., Brovkin, V., and Baehr, J.: Multivariate Climate Extremes and Their Impacts on Arctic Land–Atmosphere Carbon Exchange under Future Climate Change, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-19185, https://doi.org/10.5194/egusphere-egu26-19185, 2026.
In recent decades, Europe has experienced a clear increase in the frequency and intensity of heatwaves, a trend projected to intensify under future climate change. Understanding the processes that modulate extreme heat is therefore critical. While land-use and land-cover changes (LULC) strongly affect surface energy and water exchanges, their role in shaping extreme temperatures at regional scales remains insufficiently explored, particularly under future climate scenarios.
Here, we investigate how LUC modulates extreme temperatures and heatwaves over Europe under the SSP3-7.0 scenario using high-resolution regional climate simulations performed with the Weather Research and Forecasting (WRF v4.5.1.4) model. The simulations analyzed contribute to both the EURO-CORDEX framework and the Flagship Pilot Study LUCAS (Land Use and Climate Across Scales). A standard EURO-CORDEX future experiment with fixed LULC is compared with a corresponding simulation following LUCAS Phase 2, in which LULC evolves annually, allowing the assessment of transient LULC effects under future climate conditions.
Extreme temperature days are identified using percentile-based thresholds of daily maximum temperature, and heatwaves are defined as periods of consecutive exceedances with varying durations. To enable a consistent comparison of event intensity across experiments, temperature and land-surface variables are normalized using seasonal interquartile ranges. Changes in the frequency, duration, and magnitude of extreme heat events are analyzed over Europe and across sub-regional domains.
This analysis aims to quantify the sensitivity of future extreme temperatures to LULC change and to assess the role of land-atmosphere interactions in modulating heat extremes under climate change conditions. The results will contribute to a better understanding of how land management choices may influence future extreme heat risk across Europe.
Acknowledgements
The authors wish to acknowledge the financial support from the Portuguese Fundação para a Ciência e Tecnologia (FCT, I.P./MCTES) through national funds (PIDDAC): LA/P/0068/2020 - https://doi.org/10.54499/LA/P/0068/2020, UID/50019/2025, https://doi.org/10.54499/UID/PRR/50019/2025, UID/PRR2/50019/2025.
L.C.S. and R.M.C. also acknowledge individual funding from FCT, I.P./MCTES grants https://doi.org/10.54499/UI/BD/154675/2023, and https://doi.org/10.54499/2021.01280.CEECIND/CP1650/CT0006.
How to cite: Santos, L. C., Cardoso, R. M., Navarro Montesinos, J., García Bustamante, E., González Rouco, J. F., DaCamara, C., and Soares, P. M. M.: How do land-use changes shape future extreme temperatures across Europe?, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-15125, https://doi.org/10.5194/egusphere-egu26-15125, 2026.
Tropical precipitation is closely linked to the land surface through the exchange of water and energy between the surface and atmosphere, regulating boundary layer moistening and convective instability. In Central Africa, particularly the Congo Basin, the extensive rainforest contributes a substantial amount of moisture to the atmosphere through evaporation, enhancing convective activity and shaping the region’s seasonal and daily rainfall. In this study, we evaluate the ability of the Community Earth System Model (CESM) can represent these coupled land-atmosphere-convection processes and their control on precipitation across Central Africa.
CESM estimates of rainfall over the past 30 years are compared with multiple observational products (including IMERG, CHIRPS, and MSWEP) to assess whether the model reproduces the magnitude, variability, and spatial distribution of rainfall at daily and seasonal timescales. The same evaluation framework is applied to evaporation, with CESM estimates assessed against L-SAF, CERES, X-base, and GLEAM across consistent spatial and temporal scales. Beyond surface rainfall and evaporation, we analyse CESM’s column-integrated atmospheric moisture budget over the Congo Basin, including diagnostics of convective mass flux, against ERA5, to quantify the contributions of local evaporation, large-scale moisture convergence, and convective transport to precipitation. This approach allows us to identify whether CESM rainfall biases originate from misrepresented land surface fluxes, deficiencies in hydrometeorological parameterisation, or errors in large-scale moisture transport.
The analysis is conducted on both daily and seasonal timescales, to separate fast land-atmosphere coupling from slower circulation-driven controls. By combining evaluations of precipitation and evaporation with a process-oriented decomposition of moisture supply and convective response, this work assesses whether CESM can reliably represent land-driven rainfall variability, moisture recycling, and the emergence of hydroclimatic extremes in Central Africa.
How to cite: Cabuy, M., Ruijsch, J., De Hertog, S., Miralles, D., and Thiery, W.: Evaluating land-atmosphere interactions controlling precipitation over Central Africa in CESM, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-16256, https://doi.org/10.5194/egusphere-egu26-16256, 2026.
In the U.S. Central Great Plains, intensive agriculture is not the only human activity that has modified the natural landscape and subsequently influenced the atmosphere. With rapid urban population growth, major cities in this region have undergone significant expansion over the past few decades. Urban surfaces interact with the lower atmosphere by altering radiative and turbulent fluxes due to their unique thermal and radiative properties, thereby affecting the urban boundary layer and precipitation processes. However, the collective influence of urbanization and surrounding irrigation on regional weather and climate remains poorly understood. In this study, we investigate the impacts of irrigation and urbanization on precipitation processes over the Central Great Plains, focusing on selected precipitation events near Omaha, Nebraska, which is the largest city in the state and one that lies adjacent to extensively irrigated agricultural regions to the west. The Weather Research and Forecasting (WRF) model is used to conduct sensitivity experiments for more than 20 summer precipitation events, when irrigation is most active, and land-atmosphere coupling is strongest. Results show that upwind irrigation significantly enhances precipitation intensity, while urbanization primarily affects the spatial distribution of precipitation. The magnitude of these impacts varies with synoptic conditions across events. Additionally, land-surface influences on the thermodynamic environment before and during storms highlight the role of rural-urban heterogeneity in shaping precipitation extremes in this region.
How to cite: Chen, L., Achugbu, I., and Mahmood, R.: Impacts of Rural-Urban Surface Heterogeneity on Precipitation Events in the Central Great Plains, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-5979, https://doi.org/10.5194/egusphere-egu26-5979, 2026.
Evapotranspiration (ET) is a key process in the land water cycle, with plant transpiration accounting for ~60% of land ET. Transpiration is regulated through both stomatal functioning and total leaf area. Stomata control the diffusion of water vapor from leaves to the atmosphere, while leaf area determines the total surface over which transpiration occurs. Both processes are expected to change under elevated CO2 (eCO2), with increased CO2 availability allowing plants to optimize carbon gain to water loss by closing their stomata and decreasing transpiration per leaf. At the same time, CO2 fertilization increases leaf area, which can contribute to increasing total transpiration, as well as increasing rain water interception and reevaporation. The combined influence of these opposite physiological responses creates uncertainty in the total plant-driven ET response to eCO2. Observations also reveal a range of stomatal function across and within plant types in varying environments, much of which is not represented in Earth system models, contributing to uncertainty in the magnitude of stomatal closure under eCO2 and its impact on future ET. We quantify how uncertainty in stomatal functioning propagates into ET responses under eCO2 using Community Earth System Model (CESM2) simulations, where we perturb stomatal function across the observed range for each plant type at preindustrial and doubled preindustrial CO2. We also compare ET responses driven by stomatal uncertainty with those from leaf area growth and identify regions where ET is most sensitive to stomatal function assumptions. The total plant-driven ET response to eCO2 is a combination of the opposing contributions from stomatal closure and leaf area growth. Of the two contributors, leaf area growth tends to have a larger ET response to eCO2 compared with stomatal closure in CESM2. However, we find that stomatal uncertainty drives ET changes of comparable magnitude to the total combined plant-driven ET response to eCO2. Further, about 32% of land has greater ET sensitivity to stomatal uncertainty than the ET response to eCO2 driven leaf area growth. This occurs particularly in wet regions where stomata can strongly regulate transpiration yet remain sensitive to water availability. These results improve understanding of how uncertainty in plant physiological processes propagates into future water cycle responses and climate projections, and identify where uncertainties may be most influential.
How to cite: Liu, A. X., Swann, A. L. S., and Kooperman, G. J.: How stomatal function shapes evapotranspiration in a rising CO2 world, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-8187, https://doi.org/10.5194/egusphere-egu26-8187, 2026.
Posters virtual: Fri, 8 May, 14:00–18:00 | vPoster spot 4
EGU26-19097 | ECS | Posters virtual | VPS7
Land-Atmosphere Drivers of Cloudburst EventsFri, 08 May, 15:12–15:15 (CEST) vPoster spot 4
Cloudbursts, defined as sudden, intense rainfall episodes, are increasingly frequent extreme weather events in the Indo-Himalayan region, causing widespread devastation to human life and property; yet understanding their causal mechanisms and improving predictability remains constrained by incomplete knowledge of atmospheric and land-based precursors. Particularly, the role of soil moisture as a vital land-surface component has been underexplored in the context of cloudburst formation. This study hypothesizes that increased soil moisture from agricultural irrigation amplifies atmospheric moisture fluxes via land-atmosphere coupling and contributes to enhanced cloudburst risk. The objective here is to attribute moisture source locations, identify critical pre-event land-atmospheric indicators, and assess soil–atmosphere coupling through the analysis of IMD-specified cloudburst events from 1991 to 2020 using the Indian Land Data Assimilation System (ILDAS) dataset. We employ NOAA's Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) back-trajectory model and create Integrated Vapor Transport (IVT) maps, composited with winds, surface pressure, and sea level pressure, to trace moisture source locations. Pre-event anomaly detection and change-point analysis are performed using the Pruned Exact Linear Time (PELT) algorithm on soil moisture, precipitation, evaporation, and runoff variables across nine spatially proximate grid cells per event. Additionally, extreme percentile threshold exceedances and non-parametric persistence metrics quantify the early-warning potential. Decadal NDVI trends contextualize Land Use/Land Cover (LULC) influences. Results reveal moisture source hotspots in regions undergoing land-use transitions, with steep pressure gradients establishing strong circulation patterns that contribute moisture to multiple cloudburst events. Significant temporal anomalies occur across all four variables, with threshold exceedances and change-point detections ranging from 2 to 10 occurrences per event and anomaly persistence spanning 2 to 8 days for soil moisture. Early warning lead times of 15 to 120 days are identified for soil moisture, precipitation, evaporation, and runoff anomalies preceding the cloudburst events. These findings suggest that further quantifying the causal links among these variables can better help understand soil–atmosphere coupling and substantially improve early warning systems for detecting extreme rainfall events.
How to cite: Kaushal, A., Saharia, M., and Rajagopalan, B.: Land-Atmosphere Drivers of Cloudburst Events, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-19097, https://doi.org/10.5194/egusphere-egu26-19097, 2026.
