Understanding future changes in temperature variability and extremes is an important scientific challenge. Here, the response of daily near-surface temperature distributions to warming is explored using an idealised global climate model. Simulations of a wide range of climate states are performed with a slab-ocean aquaplanet configuration and with a simple land continent using a bucket-style model for hydrology. In the tropics, the responses of temperature extremes (i.e., high percentiles of daily near-surface temperature) to climate change contrast strongly over land and ocean. Over land, warming is amplified for hot days relative to the average day. But over ocean, warming is suppressed for hot days, implying a narrowing of the temperature distribution.
Previous studies have developed theories based on convective coupling to interpret changes in temperature extremes over land. Building on this work, here the contrasting temperature distribution responses over land and ocean are investigated using a new theory based on strict convective equilibrium, which assumes moist adiabatic lapse rates. The theory highlights four physical mechanisms with the potential to drive differential warming across the temperature distribution: hot-get-hotter mechanism, drier-get-hotter mechanism, relative humidity change mechanism, and the free tropospheric temperature change mechanism. Hot days are relatively dry over land due to limited moisture availability, which drives the drier-get-hotter mechanism and amplified warming of the warm tail of the distribution. This mechanism is the dominant factor explaining the contrasting responses of hot days over land and ocean to climate change. An extended version of the theory, which relaxes the strict convective equilibrium assumption, is introduced and applied to the simulations to understand the influence of convective available potential energy (CAPE) on changes in the temperature distribution.
How to cite: Duffield, J. and Byrne, M.: Tropical temperature distributions over a range of climates: theory and idealised model simulations, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-1397, https://doi.org/10.5194/egusphere-egu25-1397, 2025.
A simple way to model Earth’s climate is to assume radiative-convective equilibrium (RCE), where surface fluxes transport heat and water vapor away from the surface, and radiative cooling balances this energy in the atmosphere. This framework has provided basic insight into the effect of warming on climate over oceans with both fixed and interactive surface temperatures, but it is seldom applied over land. Unlike oceans, land surfaces have a limited water supply and a small heat capacity, and may respond quite differently given these features. Here, we run a suite of cloud-permitting simulations in RCE over land both with interactive soil moisture and fixed at saturation. In contrast to the most relevant previous studies, our simulations span a wide range of climates, obtained by varying the top-of-atmosphere insolation and atmospheric CO2 concentrations. Several notable patterns emerge as surface temperatures rise including non-monotonic trends in precipitation and steady declines in soil moisture, neither of which can be explained with existing theory. The results demonstrate distinctions between land and ocean responses to warming, with implications for land climate sensitivity and hydrological sensitivity.
How to cite: Gallagher, T. and McColl, K.: Land climate under warming in radiative-convective equilibrium simulations, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-7299, https://doi.org/10.5194/egusphere-egu25-7299, 2025.
Recent occurrences of record-breaking heat extremes and their profound societal impacts on health, infrastructure, food systems, and the energy sector underscore the urgent need to improve our physical understanding and modeling capacities for future projections. In mid-latitude regions, persistent high-pressure systems and dry soils have been identified as key contributors to heatwave severity. Moreover, non-linear interactions between these two drivers and temperature have been suggested to play a critical role in some of the most extreme recent heat events, such as the 2021 Pacific-North America heatwave (Bartusek et al., Nat. Clim., 2022). However, the universality and regional significance of such non-linear interactions remain largely unquantified.
Using an explainable machine learning approach, we quantitatively decompose surface air temperature anomalies during heat extremes into three components: direct contributions from (i) geopotential height anomalies, (ii) soil moisture deficits, and (iii) the interaction between the two. Our analysis reveals that non-linear interactions make statistically significant contributions across 19% of the land area in the northern hemisphere mid-latitudes (40°N–60°N). In these regions, the interactive contribution increases with temperature at a rate of 0.1 K/K when temperatures exceed a critical threshold of 4.0 K above the local summer mean. Hotspots of such behavior are especially pronounced in Central Europe, where 40% of the land area exhibits significant non-linear interactions, amplifying the most extreme heatwave events by up to 13%.
Furthermore, we identify a 2.4-fold increase in the regional mean non-linearity of interactions in Central Europe over the past 45 years, accompanied by a 25% expansion in the affected area. This accounts for 18% of the observed widening in the temperature distribution’s upper tail reported in other studies (Kornhuber et al., PNAS, 2024). Additionally, our findings show that CMIP6 climate models underestimate the non-linearity of extratropical interactions by 80%, contributing to biases in projections of extreme heat changes. Our findings underscore the critical role of these non-linear physical processes in amplifying extreme heatwave events, emphasizing the need to account for these processes in climate models to better anticipate and mitigate the impacts of climate extremes in current and future climates.
How to cite: Tian, Y., Liu, J., Huang, Y., Gentine, P., and Kornhuber, K.: Nonlinear interactions amplify the most extreme midlatitude heatwaves , EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-1850, https://doi.org/10.5194/egusphere-egu25-1850, 2025.
Daily maximum air temperatures (Tmax) are shaped by radiation, advection, atmospheric circulation, and land-surface processes, all interacting through complex feedbacks but essentially reflecting changes in the local surface energy budget. Here, we use a land-atmosphere systems approach to derive an analytical expression for daily maximum temperatures that depends solely on observed radiative and surface-evaporative conditions, requiring no additional parameters. We do this by accounting for the surface energy balance, heat storage variations within the lower atmosphere and explicitly constrain vertical turbulent exchange using the thermodynamic limit of maximum power. This approach reproduces observations very well with residual errors comparable to the reanalysis data. We then applied it to understand variations in Tmax and found that its day-to-day variability is predominantly shaped by shortwave cloud radiative effects and longwave water-vapor emissivity in the humid tropics, while heat advection and storage effects are the primary contributors in drier subtropics and high latitudes. Hot extremes, however, are mostly shaped by anomalies in land-surface characteristics including soil water stress and turbulent fluxes, with secondary contributions from heat advection and radiative effects. Both variability and extremes in the tropics were linked to changes in moisture, while the heat-storage and advective effects dominate in dry subtropics and high-latitude regions. These findings reveal the regional radiative and hydrological drivers of temperature variations within the thermodynamic energy budget and provide a baseline for understanding biases and inter-model variability in climate models. It can further help in assessing first-order changes in daily maximum temperatures due to various aspects of global change.
How to cite: Ghausi, S. A. and Kleidon, A.: Identifying regional drivers shaping daily maximum temperatures and their extremes , EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-12438, https://doi.org/10.5194/egusphere-egu25-12438, 2025.
Droughts and heatwaves are inherently linked through land-atmosphere (L-A) coupling, where the interactions between surface energy and water availability play critical roles in their evolution. In energy-limited regimes, anomalously high surface air temperature (T) intensifies evapotranspiration (ET), leading to rapid depletion of soil moisture (SM). Conversely, in water-limited regimes, reduced SM suppresses ET, exacerbating surface warming. The transition between these two regimes, characterized by critical soil moisture thresholds, governs the progression of compound drought-heatwave events.
This study analyzed the spatiotemporal variability of L-A coupling mechanisms during six extreme compound drought-heatwave events. In all cases, SM exhibited a consistent negative temporal correlation with T, declining from the onset to the peak of the heatwave and recovering during the decay phase. However, the behavior of ET varied, with SM-ET coupling dominating in some cases and T-ET coupling prevailing in others. These distinctions in coupling regimes demonstrated regional heterogeneity, even within individual events. As regimes shifted from T-ET to SM-ET coupling, evaporative fraction (EF) on heatwave peak days significantly decreased, underscoring that the drivers of drought-heatwave interactions differ spatially. Furthermore, correlation analysis between SM and EF revealed that critical soil moisture thresholds are key determinants of these coupling behaviors. This highlights the role of critical soil moisture in modulating L-A feedbacks and controlling the transition between coupling regimes.
Using the GFDL SHiELD global 13-km model configuration, we evaluated the predictability of two prominent events in 2022 and 2023, which displayed contrasting dominant regimes. SHiELD effectively captured the spatial distribution and temporal evolution of L-A coupling regimes in both cases. Notably, the SM-ET coupling-dominated 2023 event demonstrated superior forecast skill for SM and TMAX compared to the T-ET coupling-dominated 2022 event. This result emphasizes the importance of soil moisture memory in water-limited regions for enhancing predictability in compound drought-heatwave scenarios.
How to cite: Yoon, D., Chen, J.-H., Hsu, H., and Findell, K.: Different Roles of Land-atmosphere Coupling in Compound Drought-heatwave Events, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-1648, https://doi.org/10.5194/egusphere-egu25-1648, 2025.
Severe heatwaves tend to strike during drought conditions, primarily considered a consequence of persistent, often quasi-stationary anticyclonic circulation. A key mechanism for heatwave intensification is the positive feedback between rapidly desiccating soils through elevated atmospheric evaporative demand and the associated enhanced surface sensible heating. The effect of such enhanced sensible heating is often quantified by comparing the evolution of heatwaves in climate model simulations with freely evolving soil water to additional simulations in which soil moisture is kept at climatological levels, and can reach up to several degrees Celsius. With this approach, one can gauge the effect of deviations from present-day average soil moisture, but this becomes increasingly hypothetical as we shift away from climatological norms and toward a future marked by widespread projected increases in agro-ecological drought during summer months. In such a climate change context, a general key question to address is: How does heatwave intensity depend on the initial state of soil moisture? To investigate this, we re-simulate historical heatwaves using CESM2, a state-of-the-art global Earth System Model, and examine how these events would have unfolded under different land surface conditions. We also explore the long-noted — yet never fully quantified — effect of soil drought on anticyclonic circulation itself.
How to cite: Schumacher, D. L., Bevacqua, E., Hauser, M., and Seneviratne, S. I.: Revisiting the link between soil moisture deficits and heatwaves, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-15489, https://doi.org/10.5194/egusphere-egu25-15489, 2025.
Dry soils are associated with low infiltration capacity and increased runoff due to surface crust formation. Therefore, the occurrence of heavy rainfall on dry soils poses a higher risk of flooding. In recent years, abrupt changes from extremely dry to extremely wet conditions have attracted the attention of researchers, and terms such as precipitation whiplash or precipitation volatility have gained currency to refer to these phenomena. Most studies have focused on investigating these episodes on seasonal or annual scales, i.e. changes from very dry to very wet seasons or years. Here, we focus on analysing these events on a daily scale, i.e. the change from very dry to very wet conditions from one day to the next. For this purpose, dry conditions are detected using a threshold in soil moisture and not the rainfall deficit, which would be meaningless on a daily scale. We argue that this approach is more closely related to flash flood risk. Our results based on reanalysis data show that the global frequency of extreme precipitation events on dry soils has increased dramatically in recent decades, at a rate higher than predicted by historical climate model simulations. Furthermore, we show that this trend will continue to increase based on future projections. Specifically, we estimate that the global probability of such an event will more than double by the end of the present century compared to the pre-industrial era under a high-emissions scenario. Finally, we shed light on whether this trend is dominated by an increase in the probability of occurrence of extreme precipitation and dry soils independently, or rather is related to an increase in the probability of concurrence of both, which could be indicative of a negative soil moisture–precipitation feedback.
How to cite: Insua Costa, D., M. Holgate, C., and G. Miralles, D.: Observed and projected increase of extreme precipitation events on dry soils, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-19778, https://doi.org/10.5194/egusphere-egu25-19778, 2025.
The vegetation-temperature feedback significantly influences local climate variability. While previous studies have assessed the responses of local temperature to vegetation biomass changes, they often suffer from the mix of long-term global warming trends and localized vegetation-temperature interactions. More importantly, the temporal evolutions of this feedback remain elusive. Here, we use a novel approach to analyze spatiotemporal variations of this local feedback while controlling for global warming trends. Our findings reveal a weakening role of vegetation in cooling the earth over the past four decades, with a nonlinear feedback change modulated by background climatologic conditions. Furthermore, an evaluation of state-of-the-art climate models shows a systematic overestimation of vegetation cooling effects, particularly in densely vegetated regions. This overly optimistic bias contributes to a significant underestimation of global warming, highlighting the need to improve the representation of vegetation-climate interactions in climate models.
How to cite: Liu, Z., Peng, X., and He, X.: Spatiotemporal dynamics in vegetation-temperature feedback and overly optimistic representations in climate models, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-3628, https://doi.org/10.5194/egusphere-egu25-3628, 2025.
The global land carbon sink is reduced by climate change, in particular by extreme events such as droughts, heatwaves, and fires1,2. Soil moisture, including its feedback on atmospheric conditions (SA), was identified as one of key drivers of these climate extremes3-6 and contributes to the negative climate effects on the land carbon uptake7,8. However, the extent to which the total climate impact on land carbon uptake can be explained by SA feedback remains unknown. Here, we develop an analytical framework utilizing multiple factorial model experiments to show that SA feedback contributes more than half (–61.6 ± 10.4%) of the total climate effect on land carbon uptake at a global scale during 1981–2014, with the largest contributions from hot and dry regions. The strengthened SA feedback has shifted the climate impact on land carbon uptake from near-neutral during 1981–1997 to largely negative during 1998–2014, primarily by weakening photosynthesis. By the end of the twenty-first century, projected reductions in land carbon uptake caused by the SA feedback could even double under a high emission scenario relative to the historical period, driven by increased soil moisture variability. Our findings highlight that SA feedback will potentially dominate the response of long-term land carbon uptake to climate change.
How to cite: Zeng, Z.: Soil moisture-atmosphere feedback controls more than half of total climate effects on land carbon uptake, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-10175, https://doi.org/10.5194/egusphere-egu25-10175, 2025.
Drought stress has profound impacts on ecosystems and societies, particularly in the context of climate change. Traditional drought indicators, which rely on integrated surface water budget anomalies at various time scales and thresholds derived from past climate variability, provide valuable insights but often fail to deliver clear and direct real-time assessments of drought stress on vegetation.
This study introduces the Cooling Efficiency Factor (CEF), a novel metric derived from geostationary satellite observations, to detect drought stress by analyzing daytime surface warming anomalies. The CEF is based on the principle that dry surfaces warm more rapidly than wet ones under identical radiative forcing due to reduced evapotranspiration caused by soil moisture limitation and by stomatal closure, altering the effective heat capacity of the land surface.
By leveraging high-frequency, high-resolution retrievals of land surface temperature (LST) and radiation data from geostationary satellites, this study demonstrates the CEF's ability to assess drought stress conditions. The CEF correlates strongly with evapotranspiration anomalies from established datasets, including GLEAM, ERA5-Land, and TerraClimate. Results underscore the CEF's sensitivity to vegetation type, soil moisture variability, and environmental conditions, illustrating its effectiveness in identifying drought stress compared to traditional indicators.
The CEF represents a promising tool for real-time drought monitoring and integration into early warning systems, particularly for arid and semi-arid regions. By complementing existing drought assessment methods, the CEF paves the way for advancements in land-surface process studies and improved drought risk management.
How to cite: Zampieri, M., Piccardo, M., Ceccherini, G., Girardello, M., Hoteit, I., and Cescatti, A.: Heat capacity, cooling efficiency and drought stress of vegetated surfaces, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-16957, https://doi.org/10.5194/egusphere-egu25-16957, 2025.
Evaporation (E) is a key process in land-atmosphere water and energy exchanges. Among the evaporation methods, the complementary relationship (CR) approach builds upon the dynamic feedbacks of water and heat fluxes between the land-atmosphere interface, providing a straightforward framework for estimating evaporation using basic meteorological inputs, without relying on complex land surface information. Although CR is a simple and effective method, traditional CR mechanisms/models still face two main challenges. First, the wet boundary condition of CR is inaccurately characterized. When the land surface is not water-limited, evaporation is defined as potential evaporation (Epo). However, Epo estimates using conventional methods often do not align with its fundamental definition, as meteorological variables observed under real conditions differ from those over a hypothetical wet surface. Here, we estimate Epo using the maximum evaporation approach (Epo_max) that does follow the original Epo definition. Our findings show that using Epo_max significantly reduces the asymmetry in the CR. Second, traditional CR mechanisms focus on the feedback between water vapor and temperature in the land-atmosphere system, while overlooking the impact of these changes on radiation. As the surface transitions from dry to wet, enhanced actual evaporation and reduced sensible heat flux lead to cooler and wetter air above the surface, reducing the vapor pressure deficit and further decreasing atmospheric evaporative capacity (or apparent potential evaporation, Epa). Building on this, we found temperature reduction overall increases the radiation term in Epa and partially offsets the traditional view that water vapor weakens the aerodynamic term. Based on the above modifications, we developed a physically-based, calibration-free CR model, which requires few input variables and thus facilitates evaporation estimation. More importantly, the CR method, grounded in land-atmosphere coupling, offers a simpler framework for studying the feedback of evaporation on climate, making it a promising tool compared to complex coupled climate models.
How to cite: Tu, Z., Yang, Y., Roderick, M., and McVicar, T.: A simple complementary framework for evaluating evaporation base on land-atmosphere coupling, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-2239, https://doi.org/10.5194/egusphere-egu25-2239, 2025.
Evapotranspiration (ET) is a crucial process liking the surface energy balance, the hydrological and the carbon cycles. However, ET often remains underexplored due to climate model limitations as well as sparse and poor observational coverage.
While mean ET projections of CMIP6 models are highly uncertain, we explore whether climate models are in clearer agreement in terms of extreme ET, similar to what has been shown for mean versus extreme precipitation. We first define extreme ET (ETxx) as the annual 7-day ET maximum and investigate the physical drivers behind such events in a mid-latitude region (Central Europe). Typically, extreme ET events are characterized by high temperatures and incoming surface radiation, characteristic of a heat wave.
We find an increase in extreme ET during the recent historical period and throughout scenario SSP5-8.5 in most CMIP6 models, together with a shift of these extremes from summer towards spring. We also find a higher degree of climate model agreement in the ET extremes, partially due to constraints in the boundary conditions of such an event, meaning that the drivers behind an extreme ET event are better constrained than the drivers of annual mean ET. This is a somewhat expected result due to the increase in vapor pressure deficit with higher temperature. The agreement also extends to all considered observational products, which agree on an increase in extreme ET, however the magnitude of this increase remains uncertain across observations-based products. We find that the observed trends lie outside the likely range of trends found in unforced climate simulations, indicating that the recent shift in observed extreme ET is attributable to climate change. We further find that records in extreme ET have been disproportionally set in more recent years, compared to what would be expected in a stationary climate in both observations and CMIP6 models.
Overall, mean ET projections and trends are complex and notoriously uncertain. Here we show that extreme ET events are better constrained than mean ET projections, making them a natural target for more robust inference from observations, attribution studies and emergent constraints. Our findings indicate an elevated risk for flash drought due to higher evaporative demand. The fact that future changes in peak water demand are less uncertain than changes in the mean demand is a highly relevant information for decision-makers and for the design of future water supply infrastructure (such as irrigation systems).
How to cite: Egli, M., Humphrey, V., Sippel, S., and Knutti, R.: Increases in extreme ET leading to a higher risk of flash droughts, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-17114, https://doi.org/10.5194/egusphere-egu25-17114, 2025.
Even though evaporation is a crucial component of the energy and water cycles, its extremes remain largely unexplored. To address this gap, this study introduces a statistical framework defining Extreme Evaporation Events (ExEvEs) as individual events with onset and termination. Despite their statistical definition, ExEvEs are shown to have a physical basis, as they relate to radiation and/or precipitation—the main energy and water sources for land evaporation. By applying this methodological approach over Czechia, we can see that ExEvEs tend to form clusters of heightened evaporation lasting several days which fluctuate differently than the average evaporation resulting to significant implications for water availability and regional water cycle's acceleration. The proposed event-based framework provides a systematic way to detect, characterize, and analyse evaporation extremes, which helps to improve our understanding of their drivers and impacts.
How to cite: Markonis, Y.: On the definition of extreme evaporation events, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-16372, https://doi.org/10.5194/egusphere-egu25-16372, 2025.
The land sector plays an important role in addressing global climate change: Land use, land-use change, and forestry (LULUCF) is currently responsible for about 10-15% of annual anthropogenic CO2 emissions, including the only notable origins of negative emissions to date; both emissions and removals aspects make LULUCF a key focus of future climate mitigation policies. However, LULUCF also acts via changing albedo, roughness and other surface properties and thus impacts the surface energy balance and water fluxes (the biogeophysical (BGP) effects). Through the BGP effects, LULUCF has a direct impact on local climate and may counteract global warming through local cooling and mitigate extreme weather events like heatwaves and droughts. LULUCF thus also plays a role in helping communities adapt to its effects.
However, decision-makers often focus only on direct emissions and carbon storage from LULUCF. These are called local biogeochemical (BGC) effects. To make sound climate policies, it is important to consider other processes of LULUCF as well: (i) Local BGP effects, which are BGP effects acting at the site the LULUCF happens; (ii) nonlocal BGP effects, which are remote climate changes caused by advection and large-scale changes in atmospheric circulation; (iii) nonlocal BGC effects, which are remote changes in carbon storage driven by the climate changes from nonlocal BGP effects.
The complexity of these LULUCF effects, with their different spatial scales and mechanisms, often prevents stakeholders from fully incorporating them into decision-making. In this study, we create a system that helps tailor the assessment of LULUCF effects to the specific concerns of different stakeholders. This system makes it possible to distinguish the combinations of LULUCF effects that should be considered in decision-making of different purposes: For example, the interest of a farmer will focus more on the local changes in climate (predominantly influenced by BGP effects) and additionally, if farmers get credits for emission reductions or CO2 removals, on local BGC effects. International negotiations under the UNFCCC, by contrast, focus predominantly on the combined local and nonlocal BGC effects.
In our study, we carefully identify different combinations of LULUCF effects exemplarily for 5 key stakeholders’ perspectives. We analyze model results from three advanced Earth system models to give an idea of how important the negligence or incorporation of one or the other LULUCF effect is. We do so for stylized large-scale scenarios of three common forms of LULUCF: global cropland expansion, global cropland expansion with irrigation, and global afforestation. We show that the answer to whether or not a LULUCF change brings desirable effects to climate and may help mitigation and/or adaptation is very much dependent on the perspective, with our system providing a tool to translate between the different perspectives.
This study gives a detailed look at how LULUCF affects both climate and the carbon cycle, providing a foundation for incorporating these impacts into policy at different levels. It helps guide climate action that balances land use with the Sustainable Development Goals, especially considering the growing interest in nature-based solutions for future climate strategies.
How to cite: Pongratz, J., Guo, S., Havermann, F., Windisch, M., De Hertog, S., Amali, A., Luo, F., Manola, I., Lejeune, Q., and Schleussner, C.-F.: Tailoring Land Use, Land-Use Change, and Forestry (LULUCF) Impacts for Stakeholder-Centric Climate Policy, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-12862, https://doi.org/10.5194/egusphere-egu25-12862, 2025.
Changing the properties of the land surface may be one of the most direct ways to modulate local (and possibly non-local) land-atmosphere interactions, which in turn is of great interest for designing proper land-based climate mitigation and adaptation strategies. When we change the type of vegetation across a landscape, the biophysical properties of that land surface will change, potentially altering both radiative and non-radiative fluxes. Land surface temperature (LST), as measured from remote sensing satellites, provides a useful diagnostic, integrating the effects of these changes in fluxes. When combined with space-for-time substitution approaches, it is possible to derive data-driven estimations of what a given land cover transition could lead to in terms of LST before the actual land cover change occurs. However, the interannual variability of such biophysical effects of land use and land cover change is still understudied, which is an important prerequisite to understand the role these effects may have in alleviating or aggravating the occurrence and impacts of extreme events.
In this study we present a global analysis of potential afforestation on local afternoon clear-sky LST across the MODIS Aqua record (from 2002 until 2024). This allows us to explore the interannual variability of local increases in forest cover on local LST, which in turns helps us estimate the sensitivity of the effects of afforestation in a changing climate. By combining these results with a dedicated dataset identifying hot and dry extremes from ERA5, we further explore how the effect of afforestation on LST changes under extreme conditions, which the trees would be increasingly more susceptible to encounter once they reach maturity.
Additionally, we take the opportunity to present the processing pipeline that has been developed within the Open-Earth-Monitor cyberinfrastructure (OEMC) project to make such analysis possible and reproducible. This includes improvements to better handle local topographic effects and testing the capacity to run the entire pipeline within a Discrete Global Grid System (DGGS) framework that preserves area and neighbourhood properties within the space-for-time moving window. We expect that these tools will facilitate data integration and model evaluation, thereby assisting research in land-atmosphere interactions and climate extremes.
How to cite: Duveiller, G., Pabon-Moreno, D. E., Caporaso, L., Loos, D., Xie, D., Weynants, M., Winkler, A. J., and Cescatti, A.: How much does afforestation’s impact on local land surface temperature vary in space, in time, and during dry and hot extreme events? , EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-16332, https://doi.org/10.5194/egusphere-egu25-16332, 2025.
Through soil moisture and vegetation exchanges, land-atmosphere coupling contributes significantly to the evolution of extreme events. Land use/land cover changes (LUC) modify local land surface properties that control the land-atmosphere mass, energy, and momentum exchanges. The Flagship Pilot Study LUCAS (Land Use & Climate Across Scales) provides a coordinated effort to study LUC using an ensemble of 11 regional climate models (RCMs). In the first phase of the project, three reanalyses-driven experiments were performed for continental Europe: eval (with each RCM using its standard land use / land cover distribution), forest (maximised forest cover), and grass (trees replaced by grassland. An analysis of the impact on the coupling between temperature and evapotranspiration is performed using the usual correlation metric, while a new coupling metric based on the product of normalised variables was developed to analyse the coupling between extreme heat (TX90p) or heat wave (TX90p for at least five consecutive days) and evapotranspiration (LH) or soil moisture (TX90p*LH or TX90p*SMOIS). Whenever its values are lower than -1, then LH (SMOIS) is concurrently in deficit, and soil is uncoupled from the atmosphere. Conversely, when its values are greater than 1, then land-atmosphere coupling occurs.
For all RCMs, a positive correlation between near-surface maximum temperature and latent heat prevails over northern Europe, while the negative correlation dominates over southern and southeastern Europe. Forestation (forest-grass) will lead to higher correlations between latent heat and near-surface maximum temperature due to the different transition zone belt locations and weaker correlations in the grass experiment.
Extreme heat and evapotranspiration are positively coupled in forests across the whole continent except in the Mediterranean. In the grass experiment, the Mediterranean areas are negatively coupled in most models, whilst northern Europe is positively coupled. This coupling (positive/negative) is amplified under heat wave events. Overall, forestation induces increased coupling in central Europe. In the forest experiment, extreme temperature and soil moisture are negatively coupled across Europe, indicating that the increase in evapotranspiration is associated with the ability of the trees to source water from deeper soil layers. In the grass experiment, the ensemble mean shows very weak un/coupling in central/ southern Europe, indicating the inability of grasses to source water in deeper soil layers and a broadening of the transition zone.
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): UID/50019/2025 and LA/P/0068/2020 (https://doi.org/10.54499/LA/P/0068/2020), DHEFEUS (https://doi.org/10.54499/2022.09185.PTDC), and through project references https://doi.org/10.54499/UIDB/00239/2020, https://doi.org/10.54499/UIDP/00239/2020 , LS, RMC, AR, and DCAL are supported by FCT, financed by national funds from the MCTES through grant UI/BD/154675/2023, and https://doi.org/10.54499/2021.01280.CEECIND/CP1650/CT0006, https://doi.org/10.54499/2022.01167.CEECIND/CP1722/CT0006, and https://doi.org/10.54499/2022.03183.CEECIND/CP1715/CT0004, respectively
How to cite: Cardoso, R. M., Santos, L. C., García Bustamante, E., Lima, D. C. A. L., Soares, P. M., Camara, C. D. C., Rechid, D., and Russo, A. and the Lucas Team: What is the compound effect of re/af-forestation and extreme heat on summer land-atmosphere coupling across Europe? , EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-13687, https://doi.org/10.5194/egusphere-egu25-13687, 2025.
The Amazon rainforest, a crucial global carbon sink, plays a vital role in the global climate system. As ongoing climate change and local deforestation push the Amazon toward a critical tipping point, understanding the region's changing climate patterns becomes increasingly important. In this study, we reveal a significant expansion of the dry-hot season across the Amazon rainforest from 1980-2022, creating prolonged adverse climate conditions for the ecosystem and local communities. A machine learning clustering algorithm is used to define the dry-hot season automatically by considering the temperature, precipitation, and soil moisture simultaneously.
The land-atmosphere interaction predominates the dry-hot season expansion in the Amazon. During the dry season (Aug-Oct), the daily maximum temperature has warmed by ~1 degree per decade, much faster than that in the wet seasons (~0.4 degree per decade). By the surface heat budget analysis, we found that intensive dry-season warming is predominantly driven by reduced evapotranspiration, leading to decreased surface latent heat flux and increased shortwave radiation due to diminished cloud cover. The declining evapotranspiration rates stem from a combination of increasing soil moisture deficits and local deforestation.
By large-ensemble climate model simulations, we further demonstrate that this dry-hot season expansion is highly unlikely to occur without anthropogenic climate change and this expansion will exacerbate under future warming scenarios. By single-forcing experiment, we further confirm the critical role of local deforestation in amplifying this expansion. These findings emphasize the urgent need for targeted mitigation and adaptation strategies to protect this vital ecosystem from the compounding effects of climate change and deforestation.
How to cite: Pan, M., Hu, S., Janko, M. M., Zaitchik, B. F., and Pan, W. K.: Expanding Amazon dry-hot season under anthropogenic climate change, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-16565, https://doi.org/10.5194/egusphere-egu25-16565, 2025.
Tropical regions have undergone extensive deforestation in recent decades, significantly impacting local, regional, and global water cycles; however, detailed studies on their hydroclimatic effects remain limited. This study employs a regional climate model coupled with a water vapor tracking tool to investigate the effects of deforestation on local and regional precipitation from 2000 to 2020 in three major tropical deforestation hotspots: the Amazon, Africa, and Southeast Asia. Results indicate that deforestation affects precipitation with distinct scale-dependent and seasonal variations. In the Amazon, contrasting precipitation responses to deforestation were observed between wet and dry seasons (Yingzuo Qin et al., Nature, 2025, in press). During the wet season, deforested areas exhibited a notable increase in precipitation (0.96 mm month-1 per percentage point of forest loss), primarily due to enhanced mesoscale atmospheric circulation (i.e., nonlocal effects). These nonlocal effects weakened with distance from deforested areas, resulting in significant precipitation reductions beyond 60 km. Conversely, during the dry season, precipitation decreased in deforested areas and across all analysis buffers, with local effects from reduced evapotranspiration (ET) dominating. In Africa, due to the dispersibility of deforestation across the continent, the scale-dependency and seasonality of precipitation effects caused by deforestation are influenced by elevation and deforestation patch size. In Southeast Asia, under the strong influence of oceanic water vapor, deforestation-induced positive precipitation effects prevail throughout the year. These findings underscore the complex interplay between local and nonlocal effects in driving tropical deforestation-precipitation responses across different seasons and scales, highlighting the urgent need to address the rapid and extensive loss of forests in tropical regions to mitigate their nonnegligible climatic impacts.
How to cite: Qin, Y.: Tracking tropical deforestation impacts on local and regional hydroclimate, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-2431, https://doi.org/10.5194/egusphere-egu25-2431, 2025.
The increasing frequency and magnitude of compound dry–hot events (CDHEs) pose significant risks to natural and managed systems. While the role of land–atmosphere coupling in determining the magnitude and evolution of CDHEs has been highlighted, the causal interactions between variables within the coupled system under external forcing remain poorly understood. This study investigates the causal relationships between soil moisture and 2m air temperature, as well as between absorbed shortwave solar radiation and 2m air temperature during CDHEs, based on information flow theory. Using two fully coupled simulations with the Terrestrial Systems Modeling Platform (TSMP), one with and one without irrigation, the information flow analysis provides an interpretable framework to characterize the spatiotemporal variability of the land–atmosphere coupling strength in response to the perturbations such as CDHEs and irrigation.
The results show that concurrent dry and hot conditions are characterized by temporal shifts in the evaporative regime towards increased soil moisture–temperature information flow driven by the shift in surface energy partitioning, such that decreases in soil moisture lead to increased temperatures. Meanwhile, irrigation can significantly reduce the frequency and magnitude of CDHEs by directly increasing soil moisture variability and indirectly affecting surface energy fluxes, and thus altering land–atmosphere coupling. However, the impact of irrigation in Europe is predominantly local and limited by the volumes applied. These findings highlight the potential of targeted, region-specific irrigation strategies to attenuate dry and hot extremes. In addition, the information flow framework provides a robust and interpretable tool for diagnosing the functional performance of regional climate models under perturbations, offering new insights for analyzing the impacts of human interventions on the climate system and enhancing our understanding of extreme hydroclimatic events in future studies.
How to cite: Zhang, Y., Hagan, D., Miralles, D. G., Goergen, K., and Kollet, S.: Causal Dynamics of Land–Atmosphere Coupling under Compound Dry–Hot Events, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-7752, https://doi.org/10.5194/egusphere-egu25-7752, 2025.
Recurring and co-occurring extreme climate events exacerbate adverse effects on human livelihoods, regional and local economy, and the environment. Previous studies have extensively researched on the frequency, intensity, and duration of single climate extremes. However, recurring and co occurrence compound extremes remain scantly addressed in the East Africa Region. Here, we examine spatial variations of the precipitation and temperature extremes events from 1991 to 2022 (32 years) in East Africa, where agriculture is the main economic mainstay. We used high-resolution (0.25° x 0.25°) precipitation and temperature ERA5-reanalysis data. Three agriculturally relevant precipitation events: consecutive dry days (CDD), consecutive wet days (CWD), annual total precipitation that is wet-days annual amount (RR ≥ 1 mm)(PRCPTOT), and three core temperature metrics: summer days with temperature > 25°C (SU25), extremely hot days with maximum temperature > 35°C (SU35) and diurnal temperature range (DTR) are examined. Our results show that the mean annual CDD ranges between 0 and 240 days in DR Congo, Uganda, Kenya, and the Ethiopian Highlands. The CWD annual averages were the longest, and the maximum was observed in some parts of DR Congo, Ethiopian, and Kenya highlands (365 days). However, minimum CWD events were experienced in the whole of Somalia and arid and semi-arid lands (ASALs) of Kenya, Southern Sudan, and Tanzania. The highest PRCPTOT was experienced in high altitudes and rainforest biomes. Mean annual SU25 were low, predominating in mountainous regions with less than 100 days. Most parts of Kenya show the annual DTR between 10 °C to 12 °C, and few areas with values between 8 °C to 10 °C and between 12 °C and 15 °C. Rwanda and Burundi had values between 8 °C and 10 °C while Tanzania experienced values between 8 °C to 10 °C and between 10 °C and 12 °C. These agriculturally relevant climate extremes threaten people’s livelihood, which is highly dependent on rainfed agriculture. Therefore, contextual-specific adaptation strategies are imperative in minimizing socioeconomic loss and damaging adverse effects in the agriculture and water sectors. Early warning systems should be enforced over East Africa to minimize compounded climate risks.
Keywords: Climate Extremes; East Africa region; ERA5; Precipitation; Temperature.
How to cite: Musyimi, P. K., Weidinger, T., Kalmár, T., Mumo, L., and Székely, B.: Recurring and Co-Occurring Climate Extremes in Eastern Africa. A Normalcy?, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-5959, https://doi.org/10.5194/egusphere-egu25-5959, 2025.
A wealth of studies exist analysing the feedback between soil moisture and convective precipitation across a broad range of time and space scales, encompassing theoretical, numerical modelling and observational approaches. A critical step in this feedback is an understanding of how soil moisture, via its control on sensible and latent heat fluxes, influences the initiation of deep convective clouds. Knowledge of where soil moisture conditions favour triggering of new storms is also important for short-term weather forecasting. Whilst many analyses consider how soil moisture affects the vertical profiles of temperature and humidity (1-D perspective), other studies examine the role of spatially-varying soil moisture on convective initiation via surface-induced mesoscale circulations. Here we use a 20-year observational dataset of convective initiations across sub-Saharan Africa to draw more general conclusions about how soil moisture impacts convective initiation and subsequent rainfall across a diversity of hydro-climatic, topographic and wind conditions.
We use cloud-top temperature data from the geostationary Meteosat Second Generation (MSG) series of satellites to identify afternoon convective initiations for the period 2004-2023 and relate these to pre-storm observations of land surface state (land surface temperature from MSG, and surface soil moisture from the Advanced Scatterometer). Both datasets reveal a consistent Africa-wide picture of initiations favoured at the downwind end of elliptical dry soil structures, as found in previous analyses over the Sahel (Taylor et al, Nature Geoscience, 2011). The soil moisture signal weakens with stronger topographic variability, and in wetter climates and times of year, but outside of the Congo Basin and East African Highlands, the signal of initiation over locally dry soils is clear. Moreover, we show that the along-wind length scale of the dry soil feature increases with low-level wind speed. Our results, valid on scales of up to ~200km, fit with understanding of mesoscale circulations driven by soil moisture heterogeneity, and cannot be explained by 1-D consideration of thermodynamic profiles alone. We also show how the overall soil moisture-precipitation feedback from these events is influenced by wind conditions at storm steering level. In regions (including the Sahel) where winds at low and steering levels are in opposing directions, the feedback is strongly negative. Alternatively, when low and mid-level winds are aligned, the negative feedback weakens, and can become positive.
How to cite: Taylor, C., Klein, C., and Barton, E.: Soil moisture controls on convective initiation across the diverse landscapes and hydro-climates of Africa, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-3078, https://doi.org/10.5194/egusphere-egu25-3078, 2025.
The skill of regional climate models partly relies on their ability to represent land–atmosphere feedbacks in a realistic manner, through the coupling with a land surface model. However, these models often suffer from insufficient or erroneous information on soil hydraulic parameters. In this study, the fully coupled land–atmosphere model WRF-Hydro driven with ERA5 reanalysis is employed to reproduce the regional atmospheric conditions over Central Europe with a horizontal resolution of 4 km for the period 2017–2020. Simulated soil moisture is compared with data from cosmic-ray neutron sensors (CRNS) at three terrestrial environmental observatories of the TERENO network. Soil hydraulic parameters from the European digital soil dataset EU-SoilHydroGrids, together with hydraulic conductivity functions from the Campbell and van Genuchten–Mualem models, are used to test the impact of different representations of soil infiltration on modeled land–atmosphere feedbacks. An updated method to disentangle the proportion of convective precipitation being favored over wet, dry and mixed soils is provided, in order to shed more light on the soil moisture–precipitation feedback mechanism. It is found that WRF-Hydro with van Genuchten–Mualem and EU-SoilHydroGrids best reproduces CRNS soil moisture daily variations, in association with enhanced soil moisture in the root zone and a larger proportion of convective precipitation favored over wet soils. This study demonstrates the importance of adequately considering infiltration processes to realistically reproduce land–atmosphere feedbacks.
How to cite: Arnault, J., Fersch, B., Schrön, M., Bogena, H. R., Hendricks Franssen, H.-J., and Kunstmann, H.: Soil moisture–precipitation feedbacks in Central Europe: Fully coupled WRF-Hydro simulations evaluated with cosmic-ray neutron soil moisture measurements, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-4252, https://doi.org/10.5194/egusphere-egu25-4252, 2025.
Soil moisture (SM) is a crucial factor in land-atmosphere interactions and climate systems, affecting surface energy, water budgets, and weather extremes. In the Three Rivers Source Region (TRSR) of China, rapid climate change necessitates precise SM monitoring. This study employs a novel UNet-Gan model to integrate and downscale SM data from 17 CMIP6 models, producing a high-resolution (0.1◦) dataset called CMIP6UNet−Gan. This dataset includes SM data for five depth layers (0-10 cm, 10-30 cm, 30-50 cm, 50-80 cm, 80-110 cm), four Shared Socioeconomic Pathways (SSP1-2.6, SSP2-4.5, SSP3-7.0, SSP5-8.5). The UNet-Gan model demonstrates strong performance in data fusion and downscaling, especially in shallow soil layers. Analysis of the CMIP6UNet−Gan dataset reveals an overall increasing trend in SM across all layers, with higher rates under more intense emission scenarios. Spatially, moisture increases vary, with significant trends in the western Yangtze and northeastern Yellow River regions. Deeper soils show a slower response to climate change, and seasonal variations indicate that moisture increases are most pronounced in spring and winter, followed by autumn, with the least increase observed in summer. Future projections suggest higher moisture increase rates in the early and late 21st century compared to the mid-century. By the end of this century (2071-2100), compared to the Historical period (1995-2014), the increase in SM across the five depth layers ranges from: 5.5% to 11.5%, 4.6% to 9.2%, 4.3% to 7.5%, 4.5% to 7.5%, and 163.3% to 6.5%, respectively.
How to cite: Luo, S. and Li, Z.: Trend Analysis of High-Resolution Soil Moisture Data Based on GAN in the Three River Source Region During the 21st Century, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-5586, https://doi.org/10.5194/egusphere-egu25-5586, 2025.
The representation of snow in land surface models is critical for accurate seasonal forecasting, yet traditional single-layer snow schemes fail to capture the full insulating properties of deep snowpacks. These limitations result in pronounced seasonal biases, including excessive winter cooling and springtime warming. This study explores the impact of introducing a multi-layer snow scheme within the Global Seasonal Forecast System (GloSea) to address these biases. Using 24 years of retrospective forecasts (1993–2016), we compare the latest version, GloSea6, incorporating the multi-layer scheme, with GloSea5, which relies on a single-layer approach. The multi-layer snow scheme in GloSea6 improves the onset of snowmelt, delaying it by approximately two weeks. This delay moderates spring soil moisture depletion, promoting greater latent heat flux and surface evaporative cooling. The wetter surface reduces the overestimation of water-limited processes and mitigates near-surface warming biases during summer. Additionally, the enhanced representation of snow improves the simulation of precipitation, particularly in snowmelt-driven regions such as the Great Plains, Europe, and South and East Asia, leading to substantial error reductions. These findings highlight the critical role of a multi-layer snow scheme in advancing seasonal forecast accuracy, not only for temperature and precipitation during snowmelt but also for subsequent summer climatic conditions through improved land-atmosphere feedback processes.
How to cite: Seo, E. and Dirmeyer, P.: Unveiling the influence of multi-layer snowpack in seasonal forecast system on model climatological bias, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-5714, https://doi.org/10.5194/egusphere-egu25-5714, 2025.
Human activities have a significant impact on the climate by altering vegetation types and modifying surface properties, resulting in more frequent and intense extreme weather events, which pose a threat to the sustainable development of the environment. However, the specific effects of vegetation change on extreme temperature events are not fully understood. To address this gap, we conducted evaluations with both in-situ observations and the regional climate model to determine the contributions of different vegetation transitions to extreme temperature changes over China. Our findings indicate that vegetation plays an important role in local heatwaves. Cropland have a stronger heating effect than grassland and forests in lifting the daily maximum temperature but present shorter hot day durations. Uncertainties are high in grassland than those of forest due to more diverse background climatic conditions of grassland sites. Numerical simulations revealed a decrease in extreme temperatures such as a 0.85℃ decrease in the daily maximum temperature and 2.65 fewer hot days, which can be attributed to changes of cloud radiation and sensible heat flux resulting from large-scale deforestation in the southern region and cropland expansion in central China. Converting forests to woody savannas led to a significant reduction in leaf area index and latent heat flux in the southern and northeastern regions. Changes in surface property have a stronger relationship with the average temperature changes than with extreme temperature changes. Overall, our study quantitatively evaluates the impact of different vegetation types and their property changes on regional extreme temperature changes, which have important implications for ecological protection and policy-making in China.
How to cite: Dong, N. and Liu, Z.: Comparing responses of summer extreme temperature to vegetation changes in China between satellite observations and numerical simulations, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-14702, https://doi.org/10.5194/egusphere-egu25-14702, 2025.
Eurasian spring snowmelt (ESS) significantly influences climate, yet its effects on climate extremes and their dynamic variations remains poorly understood. This study investigates the dynamic impact of ESS on summer heat extremes in Northern East Asia (NEA) during 1979–2018 and examines the underlying mechanisms driving long-range links between snowmelt and temperature anomalies. We find that ESS has a notable positive impact on NEA summer heat extremes, primarily driven by snow-hydrological effects (soil-moisture). Increased ESS drives positive local soil-moisture anomalies in summer, which cool the near-surface atmosphere, facilitating the eastward propagation of anomalous wave patterns. This process strengthens the anomalous anticyclone over NEA, amplifying summer heat extremes. We also find that the Atlantic Multidecadal Oscillation modulates this impact, with its positive phase significantly enhancing the ESS effect by altering atmospheric circulation, strengthening the coupling between spring snowmelt and summer soil moisture, and intensifying NEA heat extremes. This study underscores the critical role of ESS in driving atmospheric circulation over wide regions, and highlights the coupled impacts of multi-scale and multi-temporal climate variability.
How to cite: Yang, Y., You, Q., and Smith, T.: Dynamic Impacts of Eurasian Spring Snowmelt on Summer Heat Extremes in Northern East Asia, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-8597, https://doi.org/10.5194/egusphere-egu25-8597, 2025.
Under a warmer scenario, several monsoon regimes are projected to have a delayed onset
of the rainy season. We employ state-of-the-art convection permitting regional climate
model (CPRCM) simulations performed at the UK Met Office to explore potential drivers of
this projected delay over South America. The simulations correspond to a present-day
climate (CPRM-PD) and an RCP8.5 scenario (CPRCM-2100). CPRCM-PD is downscaled
from an atmospheric general circulation model (AGCM) simulation forced with sea surface
temperatures (SSTs) for the period 1998-2007. CPRCM-2100 is driven by an AGCM
simulation forced with SSTs and greenhouse gas concentrations corresponding to an
RCP8.5 scenario. In CPRCM-2100, the onset of the rainy season is delayed, with several
regions exhibiting a delay of up to one month. The rainfall during September and October
shows approximately 50% decline over Central East Brazil, accompanied by coherent
changes in atmospheric thermodynamics. A larger relative increase in near-surface moist
static energy (MSE) is required of atmospheric destabilization in the RCP8.5 scenario, which
however, crosses the necessary threshold for significant rainfall to begin only in late
October/early November. The increase in MSE is primarily due to low-level moisture
enhancement during the onset phase which is also found to be delayed in the RCP8.5
scenario. Precipitation-moisture relationship over the region during the onset phase
indicates a 20% increase (relative to present-day) in near-surface specific humidity
requirement for a daily rainfall rate of 5 mm/day in the RCP8.5 scenario. However, there is a
substantial reduction in evapotranspiration during September and October, in addition to
the absence of any significant changes in moisture flux convergence. This hampers the
moisture build-up and delays the transition to the rainy season in these months. The decline
in evapotranspiration is despite larger soil moisture content in the soil column which
suggests reduced plant transpiration. An increase in stomatal closure in the future
environmental conditions leads to this decline in the RCP8.5 simulation. These changes are
also accompanied by changes in both surface and top of the atmosphere energy fluxes. The
results call for the urgency to develop land use policies to mitigate climate change effects,
given the increasing intensity of droughts in Brazil during recent times. The findings also
highlight the role of local processes in modulating climate projections and the necessity to
improve their representation in climate models.
How to cite: Samuel, J. B., Zilli, M. T., Hart, N. C. G., and Morris, F.: The delayed onset of South American monsoon under global warming in convection-permitting regional climate simulations., EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-13001, https://doi.org/10.5194/egusphere-egu25-13001, 2025.
Riparian forests in tropical and temperate regions often act as climatic microrefugia for many species and taxa, buffering climate extremes relative to their surroundings. For example, during a summer heatwave, maximum air temperatures can vary by several degrees between the edge and the core of the riparian forest understory. This buffering of climate extremes within riparian corridors is well documented, but the processes behind it are not well understood because they involve complex turbulent air flows throughout the convective atmospheric boundary layer interacting with the forest canopy and landscape microtopography. To better understand how forest cover and microtopography influence the microclimate within and above riparian corridors, we performed in silico experiments using a 3-dimensional Large Eddy Simulation (LES) vegetation-atmosphere model to simulate air flows and microclimate below and above the trees, and across the entire convective boundary layer. Simulations were performed for different atmospheric stability conditions, and for different corridor widths. The tree species composition in the riparian corridor and its microtopography (slope, aspect) were chosen to be representative of an old-growth temperate riparian forest known to act as a climate refugium for European beech in south-west France. In this context, we first investigated the effect of microtopography alone on the air flows below and above the forest canopy during a typical summer heatwave. We also investigated the impact of replacing maritime pine plantations on the plateau with a strip of deciduous trees extending beyond the riparian corridor, with the aim to evaluate the minimum strip size required to mitigate climate extremes in the riparian understory.
How to cite: Grulois, M., Dupont, S., Bidot, C., Lemaire-Patin, R., and Ogée, J.: Buffering of climate extremes within riparian forest corridors: a theoretical study with practical applications, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-12031, https://doi.org/10.5194/egusphere-egu25-12031, 2025.
Soil moisture (SM) is a critical Earth system variable that regulates the cyclicity of water, energy, and carbon, through which SM determines the evolution and thermodynamic state of the atmosphere. Land and atmospheric is tightly coupled in the water-limited regime (WLR), while the coupling strength diminishes in the energy-limited regime (ELR). Specifically, in response to progressive SM drying in the WLR, SM fractionates the net insolation into a greater proportion of sensible heat flux (SHF) and a smaller amount of latent heat flux (LHF), owing to the depletion of moisture. This phenomenon results in reduced land surface cooling, increased air temperature, expansion of the boundary layer, and subsequently enhances the land-atmosphere feedback. Further continuation of SM depletion leads to dry hydroclimatic extremes such as droughts and heatwaves. Consequently, understanding regime-specific coupled water-energy dynamics is fundamental to comprehending such extremes.
We propose a new metric called Land Feedback Strength (LFS) that combines three indices: sensitivity index (SI), variability index (VI) and regime persistence index (RPI). This formulation over the past attempts facilitates to effectively characterise the important components of LFS, which holistically quantify the terrestrial leg of land-atmospheric coupling. SI quantifies the responsiveness of SM to surface energy partitioning and is defined as the slope between SM and EF (LHF/LHF+SHF) in the WLR. Specifically, we observe higher SM sensitivity in semi-arid and sub-humid regions than in wet regions, indicating that the landscape rapidly responds to SM losses and begins influencing the atmosphere instantaneously. In addition, VI quantifies the sufficiency of SM to act as a dominant forcing and is calculated as the ratio of the standard deviation of SM in the WLR to WLR and ELR. While strong coupling is expected where higher sensitivity and sufficient SM variation are present, the coupling strength is exacerbated with the increasing persistence of the WLR. Thus, the RPI is formulated to indicate the likelihood of a landscape remaining in the WLR within a certain period. Furthermore, to quantify the LFS, we initially delineate global regimes using the coverability of SM and EF data pairs during drydowns.
This study’s findings indicate the following: (1) the highest sensitivity is observed during the dry seasons, whereas sensitivity is lowest during the summer; (2) SM variability is predominantly confined to WLR during winter and spring, with approximately equal variability in both regimes noted during autumn, and variability predominantly occurring in ELR during summer; (3) ELR is prevalent during summer in response to precipitation pulses, WLR and ELR demonstrate comparable likelihood in autumn, and WLR becomes predominant during winter and spring; (4) consequently, LFS is at its lowest during summer, increases in autumn, and further intensifies in winter; (5) LFS has facilitated the identification of two groups of strong coupling hotspots – with relatively higher intensity over the western USA and Austrian shrubland, African and Brazilian savannah, and lower intensity over Sahelian grassland, and peninsular India (6) LFS is found to be higher in semi-arid and sub-humid regions or savanna and grassland areas than forested or humid regions.
How to cite: Paul, S. and Lanka, K.: A Holistic Multi-Index Approach to Quantify Land Feedback Strength Across Evapotranspiration Regimes, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-16413, https://doi.org/10.5194/egusphere-egu25-16413, 2025.
Heatwaves present serious challenges to ecosystems, human health, and a wide range of socioeconomic activities. As the frequency and intensity of heatwaves increase, understanding the mechanisms driving their dynamics and interactions with land surface processes become more important. While extensive research has investigated the influence of various land and atmospheric parameters on heatwaves, less is known about how groundwater depth influences heatwave dynamics through their effects on soil moisture and surface evaporative fluxes (Vogelbacher et al., 2024, Sadeghi et al., 2012). To address this knowledge gap, we investigated how the groundwater depth affects the key parameters controlling heatwave dynamics on a global scale. Specifically, we developed more than 200,000 localized Artificial Intelligence (AI) models to represent the spatial distribution of heatwave frequency over the past 21 years across the world. For each model, a radius of 1.5 degrees (approximately 149 neighboring pixels) is considered in the computation to identify key parameters contributing to heatwaves in that region. We analyzed surface fluxes, as well as atmospheric, hydrological, and local environmental variables, to understand their correlation to heatwaves. Our findings suggest that geopotential height representing atmospheric drivers, is the key predictor of heatwave events in regions with deep groundwater tables (>100 m). In contrast, in areas with shallow groundwater (<10 m), surface fluxes emerge as important contributor to the onset of heatwaves. These findings highlight the less-discussed impact of groundwater depth on atmospheric processes and the important role of soil in linking groundwater and the atmosphere. Our results have important implications for water and land management, emphasizing the need for integrated approaches to understand and address the increasing risks posed by heatwaves.
References:
Sadeghi, M., Shokri, N., Jones, S.B. (2012). A novel analytical solution to steady-state evaporation from porous media. Water Resour. Res., 48, W09516, https://doi.org/10.1029/2012WR012060
Vogelbacher, A., Aminzadeh, M., Madani,K., Shokri, N. (2024). An analytical framework to investigate groundwater‐ atmosphere interactions influenced by soil properties. Water Resour. Res., 60, e2023WR036643. https://doi.org/10.1029/2023WR036643
How to cite: Vogelbacher, A., Afshar, M. H., Aminzadeh, M., Madani, K., AghaKouchak, A., and Shokri, N.: How shallow and deep groundwater impact environmental parameters correlated with global heatwaves, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-8944, https://doi.org/10.5194/egusphere-egu25-8944, 2025.
Irrigation is a significant anthropogenic forcing to the Earth system, altering water and heat budgets at the land surface and inducing changes in regional hydro-climate conditions across various spatiotemporal scales. These impacts of irrigation are expected to intensify in the future due to growing food demand and the pervasive effects of climate change. Therefore, it is imperative to better understand its nature, extent, and mechanisms through which irrigation affects the Earth system. However, despite its increasing importance, irrigation remains an emerging component in Earth system modeling community, necessitating further advancements in modeling approaches and a deeper understanding.
Our research aims to improve the quantitative understanding of how irrigation and groundwater use, as anthropogenic drivers, affect regional climate and environmental changes. To achieve this, we developed an enhanced Earth system modeling framework based on MIROC-ES2L (Hajima et al., 2020, GMD), integrated with hydrological human-activity modules (Yokohata et al., 2020, GMD). This framework enables simulations of coupled natural-human interactions, including hydrological dynamics associated with irrigation processes. Using this Earth system model, we carried out numerical experiments at T85 spatial resolution with an AMIP-style setup. Our large ensemble simulations allow statistical quantification of irrigation impacts, statistically distinguishing them from uncertainties arising due to natural variability.
Our investigation identified specific regions and seasons where irrigation exerts notable influences on regional hydro-climate. In particular, our results reveal substantial disparities—comparable to or exceeding inter-annual variability—between simulations with and without irrigation processes, especially in heavily irrigated regions such as Pakistan and India. Our model demonstrates that artificially wet soils due to irrigation alter the land surface hydrological balance, which consequently impacts the overlying atmosphere. However, significant uncertainties remain in the impact estimates for several variables in some regions, even those heavily irrigated, including the central United States and eastern China. This highlights the necessity of employing appropriate statistical approaches to evaluate irrigation impacts, accounting for inherent natural variability.
Additionally, our study estimates regional variations in the contributions of groundwater and surface water use to irrigation impacts. Our estimate indicates that approximately two-fifths of global irrigation water depend on groundwater resource, while this groundwater dependency ratio may still be underestimated. By emphasizing the importance of understanding regional and seasonal characteristics, our study underscores the importance of comprehending the complex interactions between irrigation-related human activities and the Earth's climate system. Nevertheless, we may still underestimate the full impacts of irrigation because irrigation water demand estimated by our coupled simulations is lower than that derived from preceding offline simulations or reported statistics. In this presentation, we will discuss this challenge as well.
How to cite: Satoh, Y., Pokhrel, Y., Kim, H., Hajima, T., and Yokohata, T.: Estimating the impact of irrigation and groundwater pumping on regional hydroclimate using an Earth System Model, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-14418, https://doi.org/10.5194/egusphere-egu25-14418, 2025.
Heatwaves constitute one of the most lethal weather phenomena, presenting substantial risks to millions of individuals. Characterized by extended periods of extreme temperatures, these events significantly impact ecosystems, economies, and human mortality rates. When coupled with high humidity, these events pose high heat stress over the heatwave domain. India, being one of the significant hotspots, experiences heatwaves during the pre-monsoon season. These heatwaves are associated with both moist and dry mechanisms. Moist heatwaves have high wet bulb temperatures and cause high fatalities among humans and mammals. With high population loading and the context of climate change, the origin or source of these moist heat waves has not been examined thoroughly till now.
In the study, we investigate the precursors of the moist and dry heat waves in the Indo-Gangetic Plains using the Eulerian temperature decomposition equation to find out the dominant processes responsible for the formation of these events. The past literature says that advection is the major component in triggering these events, but our analysis proves that the effect of advection is minimal and supports the weak temperature gradient (WTG) theory in the tropics. To study the precursors, we extend our analysis from the pre-heatwave time to the onset of the heatwaves. Our analysis shows that pre-monsoon showers are responsible for forming moist heat waves. These showers are associated with nighttime low-level clouds that trap the outgoing long-wave radiation, further accumulating the heat content and causing the temperatures to rise. Further, these rainfall activities must be supported by the mid-tropospheric dryness (MTD) for it to be sustained throughout the period. The MTD helps the low-level clouds resulting from shallow convection remain as they are and does not promote deep convection. We emphasize the importance of local atmospheric conditions along with large-scale activities (that trigger anticyclones in the upper troposphere) in sustaining the heatwave intensity. The findings of this study will help in developing heatwave early warning systems at localized scales.
Keywords: Moist heatwaves, Pre-Monsoon showers, Mid Tropospheric Dryness, Weak Temperature Gradient, Advection
How to cite: Saha, M., Dixit, V., and Lanka, K.: Role of Pre-Monsoon Showers in the Evolution of Indian Heatwaves, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-15325, https://doi.org/10.5194/egusphere-egu25-15325, 2025.
The terrestrial biosphere absorbs about one third of anthropogenic carbon dioxide emissions and thereby dampens human-induced climate change. However, its capacity to act as a carbon sink depends on climate conditions, including temperature and water availability. Uncertainties in both future climate conditions and the response of the terrestrial biosphere lead to greatly diverging projections of the land carbon sink among state-of-the-art Earth System Models (ESMs).
Previous research identified soil moisture (SM) as a critical factor that can restrict land carbon uptake through water limitation and the intensification and prolongation of heat extremes. Green et al. (2019) demonstrated the severe negative impact of reduced SM on long-term land carbon sink projections of the 5th Coupled Model Intercomparison Project (CMIP5) using dedicated experiments isolating the effects of SM.
Here, we use equivalent experiments performed with four ESMs participating in CMIP6 to investigate the impact and uncertainty of SM-induced changes in land carbon sink projections by the end of the century (2070-2099). Our results demonstrate a substantial reduction in the negative impact of SM on the global land carbon sink compared to the previous model generation. Models agree on a SM-induced reduction in land carbon uptake in summer, consistent with an overall SM decline across models, while intermodel uncertainty remains high in spring, particularly regarding the effects of SM variability at mid-to-high latitudes. Additionally, high uncertainty in SM-induced impact on annual carbon uptake persists in the tropics and northern mid-latitudes, driven by differences in the sensitivity of carbon uptake to SM but also disagreement in SM projections across models.
We extend our analysis to a larger ensemble of CMIP6 models that have not performed the SM experiments. To this end, we employ the methods of Schwingshackl et al. (2018), which utilize the distinct link between SM and the evaporative fraction in the different SM regimes. Using this relationship we emulate the impact of SM on the land carbon sink in regions where land carbon uptake is controlled by SM.
The study aims to gain insights into SM-induced impacts and related uncertainties in land carbon sink projections of CMIP6 models, highlighting the ongoing challenge of accurately projecting SM-induced changes in the land carbon sink.
References:
Green, J. K., Seneviratne, S. I., Berg, A. M., Findell, K. L., Hagemann, S., Lawrence, D. M., & Gentine, P. (2019). Large influence of soil moisture on long-term terrestrial carbon uptake. Nature, 565(7740), 476-479. https://doi.org/10.1038/s41586-018-0848-x
Schwingshackl, C., Hirschi, M., & Seneviratne, S. I. (2018). A theoretical approach to assess soil moisture–climate coupling across CMIP5 and GLACE-CMIP5 experiments. Earth System Dynamics, 9(4), 1217-1234. https://doi.org/10.5194/esd-9-1217-2018
How to cite: Gabele, L., Sieber, P., Hauser, M., Hirschi, M., and Seneviratne, S.: Assessing soil moisture-induced changes in land carbon sink projections of CMIP6 models, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-18334, https://doi.org/10.5194/egusphere-egu25-18334, 2025.
In recent years, an increase in the frequency of occurrence of heatwaves and in the number of hot days in Europe is undeniable. Hence, there is an increased need to understand the feedback mechanisms relevant to their development. Due to their localised impact and although they modify local land surface properties that control the land-atmosphere mass, energy, and momentum exchanges, the influence of land use/land cover changes (LUC) at regional scales still needs to be better represented in coordinated downscaling experiments. The Flagship Pilot Study LUCAS (Land Use & Climate Across Scales) provides a coordinated effort to study LUC using an ensemble of 11 regional climate models (RCMs). In the first phase of the project, three experiments were performed for continental Europe: eval (current climate), grass (trees replaced by grassland), and forest (grasses and shrubs replaced by trees). Heat events can be defined using percentiles, and heat waves are periods of consecutive hot days where temperatures exceed a certain percentile. Here, we use P85, P90 and P95 for maximum temperature thresholds and consider durations of 5, 7, and 10 days. To facilitate the comparison of the intensity of these extreme events and their evolution over time, we normalise the daily maximum temperature, latent heat and soil moisture using a seasonal interquartile range. An analysis of frequency, magnitude, duration and extension is performed for the three percentiles and for the different land covers.
The results suggest that model responses to afforestation and deforestation exhibit some variability, particularly during summer months. While a substantial proportion of the models indicate a potential enhancement in the intensity and magnitude of heat extremes under forest scenarios, others demonstrate more muted or contrasting effects. The objective of the present analysis is to understand these discrepancies among models and their implications for land-atmosphere interactions under various land use scenarios. The findings will be discussed in terms of their relevance to climate extremes, providing insights into the role of LUC in modulating heat events across Europe.
How to cite: Santos, L., Cardoso, R., García Bustamante, E., Lima, D. C. A., Soares, P. M., Camara, C. D., Rechid, D., and Russo, A. and the Lucas Team: How do land-use changes shape the occurrence of extreme temperatures across Europe? , EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-13907, https://doi.org/10.5194/egusphere-egu25-13907, 2025.
Tibetan Plateau has been experiencing profound warming and slight wetting over recent decades, which have contradictive effects on soil organic carbon by enhancing plant growth and thereafter carbon input into the soil and increasing the soil organic carbon (SOC) decomposition rate. In this study, we developed a SOC model (WetlandC model) for wetlands, considering also the process of litterfall decomposition and parameterizing the effect of grazing on SOC accumulation. We also established a modelling framework to combine WetlandC model with TEM (Terrestrial Ecosystem Model) model to simulate the changes in SOC of the alpine wetlands on the Tibetan Plateau from 2000 to 2018. Results showed that spatially, the soil organic carbon density (SOCD) of alpine wetlands was higher in the southeast and lower in the northwest, ranging from 1358.22 to 22571.81 g C m-2. The SOCD spatial pattern coincided with the northernmost and southernmost northern boundary of Asian summer monsoon. The SOCD was higher in region with precipitation ranging from 450 to 900 mm, suggesting that the precipitation played an important role in regulating the spatial heterogeneity of SOCD. The temporal trends of SOCD varied from -55.84 to 407.59 g C m-2 yr-1 over the plateau, and 97.98% of the wetland area was accumulating SOC. Temperature, precipitation and actual livestock carrying capacity, as the top influencing factors of the temporal trend of SOCD, accounted for 35.06%, 34.52% and 30.41% of the area in the alpine wetlands, respectively. The 0–30 cm SOC stock of the alpine wetlands on the Tibetan Plateau increased from 518.06 Tg C in 2000 to 607.67 Tg C in 2018. Surface soil in the alpine wetlands acts as a carbon sink of 4.98 Tg C yr-1. Our results indicated that in the context of climate change, additional soil carbon sequestration in the alpine wetlands was facilitated by enhanced plant growth, in spite that grazing consumed the above-ground biomass. Future climate warming and wetting is likely to benefit the SOC accumulation in the alpine wetlands on the Tibetan Plateau if not overgrazed.
How to cite: Zhang, Q.: Effects of climate change and grazing on soil organic carbon stock of alpine wetlands on the Tibetan Plateau, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-4887, https://doi.org/10.5194/egusphere-egu25-4887, 2025.
Shrinking and swelling of clays (SSC), occur as a result of water content fluctuations in expansive clayey soils, governed by seasonal cycles of precipitation and drought. This hazard causes ground movement, which can affect foundations and infrastructures. In France, where 54% of constructions are exposed to this hazard, SSC is the second largest category for natural disaster compensation.
With climate change, modification in the intensity and frequency of droughts, heat waves and precipitation are likely to exacerbate this phenomenon. In this context, further research is needed to anticipate the influence of climatic changes on the evolution of the SSC hazard and its impact on constructions in the next decades.
In particular, it is crucial to understand soil-atmosphere interactions on some appropriate spatial and temporal scales, but also through scales. Climate impact studies use hydrological or agricultural models, fed by global climate data adapted locally by statistical adjustments or downscaling. These methods improve local accuracy but increase bias and uncertainty, as they are often based on stationarity assumptions, which are not always valid in the context of climate change. The modeling of extreme values, essential for risk management, thus becomes more complex.
In response to the difficulties of climate models in representing extreme events at high spatio-temporal resolutions, and in understanding hydro-climatic interactions with clay soil, several geostatistical approaches are proposed.
An in-depth study of the existing literature has enabled us to compare the various downscaling methods. This state of the art is complemented by the study of data (extreme meteorological phenomena, humidity, soil displacements, etc.) acquired by various organizations concerned by the SSC problem (sources: BRGM, INRAE, SNCF, Météo-France, etc.).
This presentation will include the results of geostatistical analyses based on (multi)fractals conducted on this data (spatiotemporal variability, scale breaks, estimation of extreme values, spectral analysis, etc.). The data analyzed will cover the main parameters influencing soil moisture, i.e., precipitation and temperature.
These analyses may reveal the statistical signatures of climatic extremes. By identifying them, it will then be possible to research the different climate scenarios, and thus represent the extremes with precision. This step is essential to understanding SSC phenomena.
The final objective of this research work is to propose a soil-atmosphere interaction model, capable of generating the input data required for a numerical SSC behavior model. This model will take into account the various hydro-climatic parameters mentioned above, focusing mainly on evaporation and infiltration processes, as well as soil heterogeneity.
How to cite: Tixier, C., Versini, P.-A., and Dardé, B.: Identification of climatic extremes by multi-fractal analysis of long climate data series, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-4419, https://doi.org/10.5194/egusphere-egu25-4419, 2025.
Urban areas significantly influence planetary processes by altering heat, moisture and chemical budgets and it plays a pivotal role in modifying planetary processes through their unique interactions with the environment. The reduction in natural vegetation and permeable surfaces limits evapotranspiration and alters the hydrological balance, often leading to increased surface runoff, reduced groundwater recharge and changes in local humidity levels. The current study evaluates the spatial and temporal variation of temperature extremes for the historical period (1951–2014) and the future scenarios of two Shared Socioeconomic Pathways; SSP245 and SSP 585 for the future periods of 2015-2100, divided into two periods; near future (2015-2050) and far future (2051-2100) for the major tributary of The River Godavari; The Wainganga Basin, India. The temperature data for the basin is sourced from five General Circulation Models (GCMs) and an ensemble model derived from them. The ensemble model incorporates climate forecasts and accounts for anticipated space-weather-related atmospheric perturbations, resulting in a more complete knowledge of fluctuations in temperature in the Wainganga River Basin. The temperature variation due to climate change is evaluated using the extreme climate indices influenced by minimum and maximum temperature, recommended by the Expert Team on Climate Change Detection and Indices (ETCCDI) and Expert Team on Sector-Specific Climate Indices (ET-SCI). These indices provide a standardized framework for assessing the impacts of driving forces of dynamic temperature and atmospheric processes. The findings will showcase the impact of changes in temperature and their effects temporally, and spatially on the sub-basin level also address the change in atmosphere strongly with the type of driver, time, and location. As global urbanization continues, insights from studies like this are crucial for developing and evaluating adaptive strategies. Conclusively, findings can inform policies aimed at climate resilience, drawing parallels with urban climate adaptation efforts.
How to cite: Rajkumar, G. A., Nema, M. K., and Khare, D.: Exploring Dynamics of Climate and Atmosphere Employing the Temperature Indices Using Bias-Corrected GCMS and Ensemble Model Approach, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-957, https://doi.org/10.5194/egusphere-egu25-957, 2025.
