Land–atmosphere interactions often play a decisive role in shaping climate extremes. As climate change continues to exacerbate the occurrence of extreme events, a key challenge is to unravel how land states regulate the occurrence of droughts, heatwaves, intense precipitation and other extreme events. This session focuses on how natural and managed land surface conditions (e.g., soil moisture, soil temperature, vegetation state, surface albedo, snow or frozen soil) interact with other components of the climate system – via water, heat and carbon exchanges – and how these interactions affect the state and evolution of the atmospheric boundary layer. Moreover, emphasis is placed on the role of these interactions in alleviating or aggravating the occurrence and impacts of extreme events. We welcome studies using field measurements, remote sensing observations, theory and modelling to analyse this interplay under past, present and/or future climates and at scales ranging from local to global but with emphasis on larger scales.
Temperature-based events such as heatwaves and compound dry hot extremes impact the socio-economic sectors of a nation. In this study, the differential rates of temperature intensification across different seasons and regions in India coupled with dry/ wet climatologies are studied. The analysis is done for both historical observations and future CMIP6 simulations. Further, the temperature intensification rates were linked to established atmospheric feedback mechanisms. Results show that observed temperature intensification rates are positive/negative during dry/wet climatology relative to average climatology. Analysis of feedback mechanisms showed that cooling temperature trends are associated with a decrease in atmospheric aridity (vapor pressure deficit) and an increase in relative humidity. While in southern India, temperature trends are similar for all three climatologies (average, dry, and wet), albeit with different rates of intensification, in northern India, the temperature intensification shows notable contrasting trends during dry and wet climatologies. The highly irrigated Indo-Gangetic Plain region in northern India is found to experience significant cooling temperature trends during dry climatology and these trends are much more prominent during the agricultural Rabi season. Climate change analysis using CMIP6 simulations indicates further exacerbation of temperatures across all regions in the Indian subcontinent and foresees an increased probability of compound extremes in the future.
How to cite:
Prabhakar, A. and Mitra, S.: Modulation of Dry and Wet Period Temperatures in India, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-234, https://doi.org/10.5194/egusphere-egu22-234, 2022.
Measurements of global solar and net radiation fluxes were made above a grass-covered surface at DACCIWA site in a tropical location, Ile-Ife, southwest Nigeria for a period of three years (2017 - 2019). The radiation data sets were obtained from a four-component net radiometer (model NR01). Observations were made for cases of clear sky and cloudy conditions during the measurement period. The results showed considerable fluctuations of both radiation fluxes occurring during the period of measurements at the location. For clear sky conditions, the magnitudes of global and net radiation fluxes were higher than those observed for cloudy conditions due to attenuation by clouds and aerosols. For the period of observation, the highest radiation flux values occurred in 2018 while the lowest were observed in 2017. The daily surface albedo (α) values ranged from 0.16 to 0.22 at the site. Empirical relationships obtained for global solar and net radiation are RN = 0.754 RG – 17.4 Wm-2 and RN = 0.657 RG – 32.7 Wm-2 for wet and dry seasons respectively. Based on the empirical relationships, daily net and global solar radiation can be obtained when measurements like these are not available. Linear relationships between RN and RG indicate that for all days (cloudy and clear sky conditions), average RN is about 65 % of RG , and about 50 % of RG for clear sky conditions at the location
How to cite:
Ajao, A., Abiye, O., and Agboola, A.: Analysis of global and net radiation fluxes in relation to surface albedo at DACCIWA site in Ile-Ife, southwest Nigeria, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-1283, https://doi.org/10.5194/egusphere-egu22-1283, 2022.
Land-surface shortwave albedo is an important quantity in the energy budget of the Earth. Remotely sensed snow cover, maximum tree height and maximum fractional absorbed photosynthetically active radiation (fAPAR) explain 87% of the variation in present-day annual mean land surface albedo (weighted by the seasonal cycle of shortwave radiation) in a generalized linear model. We can therefore apply this model during Dansgaard-Oeschger (D-O) warming events during the last glacial period. We have already used these repeated, rapid (50–200 year), near-global climate-change events to provide new quantifications of Earth system feedbacks involving atmospheric CO2, CH4 and N2O. We now reconstruct maximum tree height and maximum fAPAR based on a new global compilation of pollen data covering the relevant time interval, combined with snow cover changes during simulated D-O events, in order to reconstruct global changes in radiative forcing due to changes in vegetation and snow cover – and thereby quantify the global land-surface albedo feedback.
How to cite:
Liu, M., Prentice, I. C., and Harrison, S. P.: Quantifying land-surface albedo feedback using Dansgaard-Oeschger events, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-1292, https://doi.org/10.5194/egusphere-egu22-1292, 2022.
The change of land cover affects regional and global climate through the surface energy budget and the water cycle, which determine the interactions between the terrestrial biosphere and the atmosphere. Land cover change not only affects the climate but is also influenced by it. The projected climate change and the occurrence of extreme climate events will profoundly affect the land cover, crop production, as well as water and food security. Yet, the complex interactions between land cover changes and climate variability are not fully understood. Previous studies have shown that land cover change influences the mean and extreme values of climate variables such as temperature. However, most research focused on specific types of land cover change such as deforestation or urbanisation and looked at only one climate variable (e.g., temperature). A comprehensive multivariate analysis relating multiple land cover changes and climate variables at the global scale is still missing. Here, we take an observation-based approach that analyses the complex interactions between different types of land cover change and the joint effect of temperature and humidity variability at the global scale. We analyse almost three decades of remotely sensed land cover and climate data to investigate the complex coupling between the patterns of different types of land cover change and the variability of temperature and relative humidity across the globe. Our analysis identifies hotspots of change on a global scale and correlations which will help to devise necessary action plans for sustainable land management and climate change mitigation measures crucial to the achievement of the United Nations Sustainable Development Goals.
How to cite:
Hemshorn de Sánchez, A. L., Stevens, B., D’Odorico, P., and Shokri, N.: Interactions between land cover change and temperature-humidity variability on a global scale, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-1526, https://doi.org/10.5194/egusphere-egu22-1526, 2022.
Managed alterations to ecosystems designed to increase carbon sequestration or reduce greenhouse gas emissions – so-called “natural” or “nature-based” climate solutions like reforestation and cover cropping - have growing public and private support. Despite this enthusiasm, the realizable benefits of these strategies, and unintended consequences to be avoided, are not well understood. In particular, land cover and management changes designed to affect carbon cycles will also impact water and energy cycles in ways that may or may not be climatically beneficial, but we lack systematic frameworks for assessing and valuing these “biophysical impacts.” Moreover, most of the existing observation-driven work on the topic has been limited to impacts on surface temperature; we still know relatively little about when and where modifications to surface temperature extend to the near-surface air temperature, which is arguably the more relevant target for climate adaptation. In this talk, I will describe a new approach for leveraging flux tower observations to understand the duality of surface and air temperature responses to land cover change. Then, using Eastern US reforestation as a case study, I will apply the approach together with analysis of remote sensing and meteorological data to demonstrate that over annual time scales, reforestation substantially lowers both surface and air temperature, due to canopy structural effects that enhance both sensible heat flux and latent heat flux. However, during heat waves when cooling benefits are most needed, divergent responses of sensible and latent heat fluxes between forested and non-forested ecosystems may reduce the local climate adaptation potential of reforestation.
How to cite:
Novick, K.: The local climate adaptation potential of reforestation, and how it changes during heat waves, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-2056, https://doi.org/10.5194/egusphere-egu22-2056, 2022.
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In tropical convective climates, where numerical weather prediction of rainfall has high uncertainty, nowcasting provides essential alerts of extreme events several hours ahead. In principle, short-term prediction of intense convective storms could benefit from knowledge of the slowly-evolving land surface state in regions where soil moisture controls surface fluxes. Here we explore how near-real time (NRT) satellite observations of the land surface and convective clouds can be combined to aid early warning of severe weather in the Sahel on time scales of up to 12 hours. Using Land Surface Temperature (LST) as a proxy for soil moisture deficit, we characterise the state of the surface energy balance in NRT. We identify the most convectively-active parts of Mesoscale Convective Systems (MCSs) from spatial filtering of cloud-top temperature imagery.
We find that predictive skill provided by LST data is maximised early in the rainy season, when soils are drier and vegetation less developed. Land-based skill in predicting intense convection extends well beyond the afternoon, with strong positive correlations between daytime LST and MCS activity persisting as far as the following morning in more arid conditions. For the Science for Weather Information and Forecasting Techniques (SWIFT) Forecasting Testbed event during September 2021, we developed a simple technique to translate LST data into NRT maps quantifying the likelihood of convection based solely on land state. We used these maps in combination with convective features to nowcast the tracks of existing MCSs, and predict likely new initiation locations. This is the first time to our knowledge that nowcasting tools based principally on land observations have been developed. The strong sensitivity of Sahelian MCSs to soil moisture, in combination with MCS life times of typically 6-18 hours, opens up the opportunity for nowcasting of hazardous weather well beyond what is possible from atmospheric observations alone, and could be applied elsewhere in the semi-arid tropics.
How to cite:
Taylor, C. M., Klein, C., Dione, C., Parker, D. J., Marsham, J., Abdoulahat Diop, C., Fletcher, J., Saidou Chaibou, A. A., Nafissa, D. B., Semeena, V. S., Cole, S., and Anderson, S.: Nowcasting Tracks of Severe Convective Storms in West Africa from Observations of Land Surface State, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-2915, https://doi.org/10.5194/egusphere-egu22-2915, 2022.
Results: Soil temperature is a crucial variable in Land Surface Models (LSMs) because it affects the fractions of frozen and unfrozen water content in the soil. For example, getting the coupling between below-ground heat- and water transfer correct in LSMs is very important in permafrost regions because these are particularly sensitive to climate change. Poor predictions of the energy- and water balance in these regions will lead to large uncertainties in predicted carbon fluxes, and related land-atmosphere feedbacks. Also, simulated near-surface soil temperatures can be used to diagnose and explain model differences in skin temperatures and soil heat fluxes, both of which are pivotal in the prediction of the surface energy balance.
Soil temperature is generally under-researched as part of LSM intercomparisons. Here we present an analysis of the spatial distribution (including the vertical distribution along the soil profile) and seasonal evolution of soil temperature simulated by eight LSMs as part of the Soil Parameter Model Intercomparison Project (SP-MIP). We found large inter-model differences in key metrics of the annual soil temperature wave, including the amplitude, phase shift and damping depth, which were partly attributed to diversity in hydraulic as well as thermal soil properties. Soil layer discretisation also played a role.
Methods: Via manipulation of model soil hydraulic properties, and the soil texture inputs required to calculate these properties, controlled multi-model experiments have been conducted as part of SP-MIP, this MIP wasoriginally proposed at the GEWEX-SoilWat workshop held in Leipzig (June 2016).
The model experiments closely followed the LS3MIP protocol (van den Hurk et al. 2016). Eight land models (CLM5, ISBA, JSBACH, JULES, MATSIRO, MATSIRO-GW, NOAH-MP and ORCHIDEE) were run globally on 0.5° with GSWP3 forcing, from 1980-2010, for vertically homogeneous soil columns. There were 4 model experiments, leading to 7 model runs: Experiment 1. Global soil hydraulic parameter maps provided by SP-MIP; Experiment 2. Soil-hydraulic parameters derived from common soil textural properties, provided by SP-MIP, using model-specific pedotransfer functions (PTFs); Experiment 3. Reference run with all models applying their default soil hydraulic settings (including their own soil maps to derive the parameters); Experiment 4: four runs using spatially uniform soil hydraulic parameters for the whole globe (loamy sand, loam, clay and silt) provided by SP-MIP.
Differences between the model experiments will allow the assessment of the inter-model variability that is introduced by the different stages of preparing model parameters. Soil parameters for Experiments 1 and soil textures for Experiment 2 at 0.5° resolution were prepared from dominant soil classes of the 0-5 cm layer of SoilGrids (Hengl et al. 2014) at 5 km resolution. Brooks and Corey hydraulic parameters come from Table 2 of Clapp and Hornberger (1978), Mualem-Van Genuchten hydraulic parameters are ROSETTA class average hydraulic parameters (Schaap et al. 2001), and soil textures are from Table 2 of Cosby et al. (1984). Experiments 4 a-d use the USDA soil classes, using the same PTFs for Brooks and Corey and Mualem-van Genuchten parameters as in Experiment 1.
How to cite:
Verhoef, A., Zeng, Y., Cuntz, M., Gudmundsson, L., Thober, S., McGuire, P. C., Bergner, H., Boone, A., Ducharne, A., Ellis, R., Kim, H., Koirala, S., Lawrence, D., Oleson, K., Swenson, S., Tafasca, S., de Vrese, P., Seneviratne, S., Or, D., and Vereecken, H.: Assessing the variability of soil temperatures in Land Surface Models using outputs from the Soil Parameter Model Intercomparison Project (SP-MIP), EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-4349, https://doi.org/10.5194/egusphere-egu22-4349, 2022.
Natural processes within the Earth system have been shown to organise themselves to achieve a state of thermodynamic optimality. Here we test these physical principles for convective flux exchange within the surface – atmosphere system. We propose an idealised modelling framework where the convective exchange is conceptualised as the outcome of a heat engine operated between the hotter Earth’s surface and the cooler atmosphere. We use the first and second law of thermodynamics in conjunction with the surface energy balance which give rise to thermodynamic constraints on turbulent flux exchange. This new constraint is associated with the maximum power that can be generated within the heat engine to sustain convective motion. We use daily radiative forcing from NASA-CERES dataset as the input to our approach and estimated the surface energy partitioning on land into turbulent fluxes and emitted longwave radiation. The former is closely related to convective exchange within the atmosphere driving the hydrologic cycling while the latter directly relates to the surface temperature of the Earth. We compare our estimates of surface temperatures, latent and sensible heat fluxes with observation based datasets and found a very good agreement over land at a global scale. Our findings show that physical principles of thermodynamics alone can explain the surface energy partitioning to a large extent. We further show an application of this approach in removing the cloud radiative effects (CRE) from surface temperatures. We used clear-sky fluxes from the NASA-CERES dataset as a forcing to our thermodynamically constrained energy balance model and estimated "clear-sky" temperatures. These temperatures removes the effect of radiative cooling by clouds on surface temperatures and can be used as useful variable to infer the hydrological sensitivity from observations. Our work implies that thermodynamically constrained idealised models can be used to identify the dominant physical controls on climate system to better understand land-atmosphere interactions and climate sensitivities.
How to cite:
Ghausi, S. and Kleidon, A.: How much of the surface energy partitioning can be explained by controls imposed by thermodynamics?, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-4528, https://doi.org/10.5194/egusphere-egu22-4528, 2022.
Different land covers present contrasting changes in energy budgets as a response to heatwaves and droughts and thus the land feedback is expected to vary over the landscape. To date, the study of the biotic determinants of land-atmosphere feedbacks during heatwaves has been restricted to the consideration of different plant functional types. We used improved vegetation structural measurements at organizational levels lower than plant functional types (inter– and intra–specific) to estimate the impact of forests on the surface thermal balance.
We combined space-borne measurements of the temperature of plants (ECOSTRESS) and the land surface (MODIS) with ground-based meteorological data to estimate the thermal balance of the surface (∆T) at a resolution of 70x70m in 615 forest plots, dominated by 28 different species. In each plot, forest structural variables were determined through LiDAR. We then analysed the spatiotemporal drivers of ∆T by quantifying the contribution of topographical, landscape, meteorological and forest structural variables on ∆T both during normal conditions and heatwave episodes.
Canopy temperatures fluctuated according to changes in air temperature and were on average 1˚C warmer than the air. During heatwaves, canopies were relatively cooler than the air, compared to normal conditions in all but Mediterranean coniferous forests. The thermal response of canopies to heatwaves strongly varied as a function of environmental variables. Forests in rainy areas and in steep slopes presented the lowest ∆T, whereas forests in arid areas and flat terrain had the highest ∆T. Interestingly, there was a strong effect of forest structure, since forests with larger biomass kept a cooler thermal balance (lower ∆T). Indeed, the total effect of forest structural variables on ∆T was of equal magnitude as that of topography or meteorological conditions.
The thermal balance of the surface (∆T) was not only different among the main forest types, but also, it strongly varied within forests dominated by the same species. Because ∆T is an important component of the surface energy budget, our results on its dependence on forest structure imply that forest management could be employed to modify the surface energy budget to promote negative (mitigating) feedbacks of forests during heatwave episodes. Further efforts concentrate on estimating changes in aerodynamic conductance between forests and their surroundings, and their potential influence on the land–atmosphere coupling and the feedback of forests on local temperatures.
How to cite:
Barbeta, A., Miralles, D. G., Mendiola, L., Gimeno, T. E., Sabaté, S., Pou, A., and Carnicer, J.: Drivers of the spatiotemporal variability in the thermal balance of forests during heatwaves and normal conditions., EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-5646, https://doi.org/10.5194/egusphere-egu22-5646, 2022.
Hot temperature extremes have severe implications for human health, crop yields and tree mortality. Whereas they are mostly introduced by atmospheric circulation patterns, the intensity of hot temperature extremes is modulated by ecosystem functioning; when soil moisture is abundant, evaporation of water through transpiration and evaporation from surfaces is high, which causes relevant evaporative cooling. This cooling is greatly reduced under drought stress, because ecosystems adapt to water-limited conditions by saving water e.g. through stomatal regulation which leads to decreased terrestrial evaporation. This in turn leaves more energy to potentially exacerbate hot temperature extremes.
While it has been shown that ecosystem water limitation is projected to increase in the future, the respective implications on hot temperature extremes are unclear. In this study, we capture the ecosystem's water limitation through the so-called Ecosystem Limitation Index (ELI, Denissen et al. 2020). To mitigate the confounding influence of changes in mean temperatures, which possibly originate from heat advection and circulation, we focus on the differences between mean and hot temperature extremes. Based on global climate projections from the sixth Coupled Model Intercomparison Project (CMIP6) from 1980 - 2100, we find regions with significant correlations between future evolution of temperature differences and ELI, with hot spots in North and South America. We furthermore test the role of the initial ELI for these correlations and find weak effects in Earth System Models included in the CMIP6 ensemble, but higher relevance in reanalysis data from the ECMWF Reanalysis 5th generation (ERA5) from 1980 - 2020, where the highest correlations are found in initially water-limited regions. These findings show that in large areas across the globe, temperature extremes increase much faster than mean temperatures alongside ecosystem drying. Therefore, considering ecosystem drying is relevant for assessing the intensity of projected temperature extremes and their corresponding impacts. This way, improving the representation of vegetation dynamics in state-of-the-art models is necessary to more accurately estimate evaporative cooling and consequently hot temperature extremes.
Denissen, J. M., Teuling, A. J., Reichstein, M., & Orth, R. (2020). Critical soil moisture derived from satellite observations over Europe. Journal of Geophysical Research: Atmospheres, 125(6), e2019JD031672.
How to cite:
Denissen, J., Teuling, A. J., Balsamo, G., and Orth, R.: Shift towards ecosystem water limitation exacerbates hot temperature extremes, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-5787, https://doi.org/10.5194/egusphere-egu22-5787, 2022.
The major concern of land-atmosphere interactions (L-A) is the evolutionary process between the land surface and the planet boundary layer during the daytime, however many relevant studies had to use entire-day-mean daily time series to perform investigation due to lack of sub-daily data. Yet it is unclear whether the inclusion of nighttime data would alter the results or obscure the L-A interactive processes. To address this question, we generated daytime-only-mean (D) and entire-day-mean (E) daily data based on the ERA5 (5th ECMWF reanalysis) hourly product, and evaluated the strength of L-A coupling through a two-legged metrics, which assessed the coupling strength by the causality as well as the impact magnitude through two segments (land-fluxes and fluxes-atmosphere). The results demonstrated significant differences between the D- and E-based diagnoses as large as 67% (median 20.7%), which strongly depended on the season and the region. More importantly, for the first time, two special L-A coupling mechanisms were revealed. One was the advection-dominant L-A mechanism in tropical hyper-arid regions. The other was the soil moisture and sensible heat flux coupling mechanism during the cooling process over the nighttime. Both processes may play important roles during the night, andweaken the signal of L-A coupling if E was applied. To improve our knowledge of L-A interactions, we call attention to the urgent need for more high frequency data for relevant diagnoses. Meanwhile, we propose two approaches to resolve the dilemma of huge storage for high frequency data: (1) integration of L-A metrics in Earth System Model outputs, and (2) production of daily datasets based on different averaging algorithms.
How to cite:
Yin, Z., Findell, K., Dirmeyer, P., Shevliakova, E., Malyshev, S., Ghannam, K., Raoult, N., and Tan, Z.: Daytime-only-mean data can enhance our understanding of land-atmosphere coupling, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-6467, https://doi.org/10.5194/egusphere-egu22-6467, 2022.
Heat wave is one of the most severe natural disasters in the mid-latitude regions. Due to climate change and urbanization, heat waves have been intensified in the past, and are projected to be more severe in the future. Droughts and heat waves usually occur simultaneously, which are referred to as compound extreme events. Antecedent or simultaneous droughts enhance heat waves through local land-atmosphere interaction, but a few case studies show that upwind droughts can have a significant impact on heat waves through sensible heat advection. In order to systematically study the impact of upwind droughts on heat waves, this study uses a Lagrangian integrated trajectory model driven by reanalysis data to analyze the heat wave events in northern part of Eastern China from 1979 to 2019. We find that half of the heat waves are enhanced by upwind droughts. For the related heat waves, the upwind droughts contributed to 67.9% of the heat anomalies. The impact of flash drought on heat waves in Eastern China is also being explored, with particular interest to extract heat wave signals from antecedent flash drought to provide early warning for extreme heat waves over downwind areas.
How to cite:
Zhou, S. and Yuan, X.: Upwind droughts enhance heat waves in Eastern China, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-6753, https://doi.org/10.5194/egusphere-egu22-6753, 2022.
During droughts, low water availabilities limit soil evaporation and induce stomatal closure to prevent transpiration, leading to reductions in evapotranspiration (ET). At the same time, drought-associated meteorological conditions such as high temperature elevate atmospheric evaporative demand, acting to increase ET. However, the overall effect of drought on the sign of ET anomalies remains unknown, as are the determinants of this response. Positive anomalies during drought (ET+), in particular, are of concern because they quickly deplete water resources, may cause flash droughts, and exacerbate ecosystem stress. Because remotely sensed ET datasets implicitly assume a stomatal response to drought, they cannot provide direct observational constraints of the prevalence of ET+. Eddy covariance tower records are often too short and sparse to adequately sample drought conditions. To avoid these shortcomings, we used a water balance approach to derive a new estimate of ET+ occurrence during droughts by combining total terrestrial water storage (TWS) observations from the Gravity Recovery and Climate Experiment (GRACE) and GRACE Follow-On (GRACE-FO) with Global Precipitation Climatology Project precipitation data. The robustness of this approach is demonstrated across 104 hydrological basins. With this new water balance-based estimate, we showed that ET+ during droughts are globally widespread. On average, ET+ occurs in ~45% of drought periods, and it is more likely to occur during milder droughts (with relatively lower P reductions and ample available TWS). CMIP6 Earth system models (ESMs) underestimate the observed ET+ probability by nearly half. This underestimation is particularly large in relatively dry locations with an aridity index (P/PET) below ~1.5 and can be attributed in part to an overly strong ET response to decreases in soil moisture in these regions. Furthermore, ESM’s lack of accounting for variability in plant water stress response traits within plant functional types exacerbates their underestimation of ET+. This demonstrates for the first time that local adaptation of plant water stress response traits reduces the impact of droughts on ET. These process representations should be improved to reduce model uncertainties in predicting drought impacts on the energy-water-carbon nexus.
How to cite:
Zhao, M., Aa, G., Liu, Y., and Konings, A.: Evapotranspiration frequently increases during droughts, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-6904, https://doi.org/10.5194/egusphere-egu22-6904, 2022.
Extratropical windstorms are amongst the highest rated perils for the European continent. Extreme wind speeds of these synoptic scale systems occur primarily in the winter season and often cause damage to buildings, forests and infrastructure, and thus can have large socio-economic impacts.
In our studies of extratropical windstorms in the CMIP6 model ensemble, we found remarkable trends of opposite sign in the wind speed during the historical period. More specifically, we found a continuous increase in the surface wind speed in the early historical period between 1850 and 1920, and an even stronger decrease thereafter until the present.
In a case study with one of the models (MPI-ESM) we found that the trends in the wind speed relate to a trend of opposite sign in the roughness length, thus the wind speed increases in eras with a decrease in the surface roughness (and tree fraction) and vice versa. While this relationship is expected and physically reasonable, it appears that the interaction of surface parameters with the atmosphere was different in CMIP5 climate models, as there is no comparable reaction of surface wind speeds to the trends in surface parameters (e.g. tree fraction).
Since the historical era serves as the reference for any derived climate change signal, these trends might affect the amplitude of the changes in a future climate and the derived conclusions. Also, state of the art climate change signals regarding storminess might need to be reconsidered with this newly represented land-atmosphere interaction in the models.
We further explore this phenomenon by eliminating the influence of the roughness on the wind speed and investigate the effect that this correction has on the appearance of climate change signals of extratropical windstorms.
How to cite:
Schuster, M., Raddatz, T., and Ulbrich, U.: Impact of trends in historical surface roughness over Europe on extra-tropical windstorms in CMIP6 , EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-7812, https://doi.org/10.5194/egusphere-egu22-7812, 2022.
Morocco as many semi-arid Mediterranean and north African countries is facing strong pressure on water resources exacerbated by climate change. Assessing the representation and variability of the Moroccan climate by using the climate models is of major importance to strengthen the reliability of future scenarios and anticipate the water cycle evolutions.
The aim of this study is to evaluate and improve the representation of the surface-atmosphere coupling, and the boundary-layer dynamics over the Haouz plain by the IPSL-CM Earth System Model. The Haouz plain is one of the most important agricultural and touristic regions of Morocco. It is located in the Tensift watershed and limited with the Atlas mountains, and it has been equipped with a network of meteorological stations. We set a simulation configuration up with a model grid refined over the Haouz plain and with a nudging towards atmospheric reanalysis outside the plain, making it possible to concomitantly compare the model outputs with in-situ data.
A first evaluation of the control simulation reveals an overall good agreement between the observed daily mean temperature and the simulated one despite some cold biases. Simulated near-surface relative humidity is generally low-biased (up to 20%) while precipitation is overestimated (up to 50% of observed daily precipitation). Those biases are further deciphered through a careful evaluation of the different terms of the surface energy and water budgets. Complementary analyses conditioned to the direction of the large scale flow also investigate how model’s performances over the plain depend on the representation of the orographic flow over the Atlas. This evaluation work is a preliminary and an important step to identify which and how LMDZ parameterizations have to be improved for semi-arid African regions.
How to cite:
Arjdal, K., Driouech, F., Vignon, É., Chéruy, F., Sima, A., Drobinski, P., Chehbouni, A., and Er-Raki, S.: Modeling the surface-atmosphere coupling in the Moroccan semi-arid plains in the context of climate change, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-8163, https://doi.org/10.5194/egusphere-egu22-8163, 2022.
The Arabian Peninsula exhibits extreme hot summers and has one of the world's largest population growth. We use satellite observations and reanalysis as well as climate model projections to analyze morning and evening land surface temperatures (LST), to refer to processes at the surface, and wet bulb temperatures (WBT) to measure human heat stress. We focus on three regions: The Persian Gulf and Gulf of Oman, the inland capital of Saudi Arabia, Riyadh and the irrigated agricultural region in Al-Jouf, Saudi Arabia. This study shows that the time of the day is important when studying LST and WBT, with current and future WBT higher in the early summer evenings. It also shows that the effect of humidity brought from waterbodies or through irrigation can significantly increase heat stress.
Over the coasts of the Peninsula, humidity decreases LST but increases heat stress via WBT values higher than 25°C in the evening. Riyadh, located in the heart of the Peninsula has lower WBT of 15°C to 17.5°C and LST reaching 42.5°C. Irrigation in the Al-Jouf province decreases LST by up to 10° with respect to its surroundings, while it increases WBT by up to 2.5°. Climate projections over the Arabian Peninsula suggest that global efforts will determine the survivability in this region. Even under the sustainability scenario, the projected increase in LST and WBT reaches +10° and +5°C respectively in the Persian Gulf and Riyadh by 2100 posing significant risk on human survivability in the Peninsula.
How to cite:
Safieddine, S., Whitburn, S., Clarisse, L., and Clerbaux, C.: Present and future land surface and wet bulb temperatures in the Arabian Peninsula, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-8601, https://doi.org/10.5194/egusphere-egu22-8601, 2022.
Droughts are impactful climate extremes with proven dramatic consequences on economy, ecosystems and society. Numerous research has been devoted to exploring land surface controls on meteorological drought onset and evolution. However, the importance of land conditions may be equally important for drought termination, yet the latter remains much less understood. Drought demise is often abrupt, can lead to extreme rainfall and floods, and is generally hard to capture using traditional monthly drought metrics. A better predictability of the end of a drought can not only help better anticipate the duration of droughts, but also significantly improve risk assessment and water resource management during dry extremes.
In this study, we explore the existence of a positive or negative feedback between the decreasing soil moisture and the probability of drought termination. As test cases, multiple droughts in Belgium during the period of 1981–2015 are selected. As a first step, we compose a data set of past droughts based on precipitation and soil moisture from ECMWF reanalysis data and identify the drought termination days. Next, multiple simulations of the drought termination days are executed with the CLASS4GL mixed-layer model framework, in which the influence of changing soil moisture conditions is evaluated. Finally, the sensitivity of drought demise to soil moisture is assessed based on multiple soil moisture–atmosphere coupling metrics and revealed sensitivity relationships. The obtained results highlight the importance of realistic representation of land–atmosphere feedbacks and soil moisture for drought evolution and termination, and could be used to inform drought prediction efforts or pave the way for effective geoengineering solutions designed to mitigate the increasing risk of dry climate extremes in the future.
How to cite:
De Vestele, D., Yu. Petrova, I., and G. Miralles, D.: Land surface controls on drought termination in Belgium, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-9810, https://doi.org/10.5194/egusphere-egu22-9810, 2022.
Understanding the roles of land surface conditions and atmospheric circulation on continental daily temperature variance is key to improving predictions of temperature extremes. Evaporative resistance (rs, hereafter), a function of the land cover type, reflects the ease with which water can be evaporated or transpired and is a strong control on land-atmosphere interactions. This study explores the effects of rs perturbations on summer daily temperature variance using the Simple Land Interface Model (SLIM) by mimicking a global land cover conversion from forest (high rs) to crop/grassland (low rs). Decreasing rs causes a global cooling. The cooling is larger in wetter areas and weaker in drier areas, and primarily result from perturbations in shortwave radiation (SW) and latent heat flux (LH). Decreasing rs enhances cloud cover due to greater land surface evaporation, thus reduces SW over most land areas. Wetter areas experience strong evaporative cooling, while drier areas become more moisture-limited when rs decreases, thus experience relatively less cooling. Thermal advection further shapes the temperature response by dampening the combined impacts of SW and LH. Temperature variance increases in drier areas and decreases in wetter areas as rs decreases. The temperature variance changes can be largely explained from changes in the combined variance of SW and LH, including an important contribution of changes in the covariance of SW and LH. In contrast to changes in the mean, changes in thermal advection variance amplify the changes in temperature variance predicted from the surface energy balance alone, particularly in the Northern Hemisphere mid-latitudes.
How to cite:
Kong, W., A. McKinnon, K., R. Simpson, I., and M. Laguë, M.: Understanding responses of summer continental daily temperature variance to perturbations in the land surface evaporative resistance , EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-10991, https://doi.org/10.5194/egusphere-egu22-10991, 2022.
To simulate the extreme precipitation events through GCMs has become a challenge due to discrepancies in spatio-temporal resolution, physics, and parameterization schemes of the models along with deficiencies in the observed datasets. In this study, the performance of 27 CMIP6 models and their Multi model mean (MMM) in simulating extreme precipitation indices has been compared to the observed precipitation datasets (APHRODITE and IMD) over India during JJAS for 1975-2014. Meanwhile, the MMM shows a close agreement in simulating the indices derived from APHRODITE with PCC >0.6 for all indices with higher skill score (0.54), lower NRMSE than IMD. However, the MMM over- (under)-estimate the number of consecutive wet days (total precipitation) with a median relative error of 64% and 160% (5% and 20%) respectively, as compared to APHRODITE and IMD. Which inferred that similar biases still persist in the newly released CMIP6 GCMs with inter-observation dissimilarity in reproducing the indices. In general, the MMM is unable to replicate the very heavy precipitation (R20mm), with negative median relative errors. However, for all three aforementioned precipitation indices the extent of over- and under-estimation is less while comparing against the APHRODITE than IMD. For consecutive dry days (CDD), the MMM over- (under)-estimate over the North west (northern tip and peninsular as well as lee side of Western Ghat) parts of India, where the biases relative to APHRODITE (IMD) is large (less). The MMM simulates precipitation indices well, instead of using individual model. Whereas, the variation of NRMSE values of individual models are less with the exception of CDD and CWD, where the disagreement between the models with observation is large with larger interquartile model range. Comparing the relative errors between the different homogenous regions of India, all the regions are marginally performing good in simulating the different indices except the NW region, which is appended with larger relative error. It was worth noting that the models having higher spatial resolutions simulate the indices realistically with high (low) PCC (NRMSE), whereas the reversal is not valid for the worst performing models.
How to cite:
Bhuyan, D. P., Salunke, P., and Mishra, S. K.: Assessment of Extreme Precipitation Indices over India by CMIP6 Models, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-11121, https://doi.org/10.5194/egusphere-egu22-11121, 2022.
This study examined boreal summer soil moisture using long-term satellite observations to study the bimodal probability distribution function (bimodality) of the surface soil moisture for the land-atmosphere coupling hotspot region, i.e., United States, Sahel and India. Although boreal summer soil moisture bimodality has been detected globally, it has not yet been established how surface soil moisture bimodality is caused. In this comparative multiregional study of surface soil moisture, the object was to classify India, Sahel, and Unites States regions into inter-annual or intra-seasonal soil moisture variation-based soil moisture bimodality. It was found that soil moisture bimodality detection is sensitive to the number of observations and the selected time period window. For northern India, intra-seasonal soil moisture variation dominates for soil moisture bimodality, while in the case of the United States, intra-annual soil moisture variation is dominant.
How to cite:
Dengri, A. and Yamada, T.: Soil moisture bimodality over Land–Atmosphere hotspot regions at intraseasonal and interannual timescale., EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-12122, https://doi.org/10.5194/egusphere-egu22-12122, 2022.
Gando Bawal (Mad Tree) as it is called by the people of Kutch, Gujarat is the non-native species originally known as Prosopis juliflora which was introduced in this semi-arid region in the year 1960 for rehabilitation of sodic lands and to prevent the encroachment of Rann desert onto the Banni grassland. Studies by Pasha et al. 2014 have suggested that there was an increase of 42.9% of area under Prosopis cover in Kutch during 1977 to 2011. Due to its invasive nature it has spread over large areas and invaded the pastoral grasslands of Banni region of Kutch, Gujarat. There is an increase in frequency of droughts and the people of Banni are blaming Prosopis juliflora as the culprit. Prosopis juliflora has depleted the ground water sources by accessing it through its long roots. To evaluate this and to assess the rate of groundwater depletion in this region here we used terrestrial water storage-change observations from NASA's Gravity Recovery and Climate Experiment satellites (GRACE) and simulated soil-water variations from a data-integrating hydrological model to show that groundwater is being depleted. The data set was prepared by collecting the measured precipitation, remote sensing evaporation and ground water table from the period of 2002 to 2017. During this period, the other terrestrial water storage components i.e. soil moisture, surface waters and biomass did not contribute significantly to the observed decline in total water levels. The study provided valuable information in understanding the net groundwater depletion rate by the tree species. Although our observational record is brief, the available evidence suggests that the consumption of groundwater by the tree species Prosopis juliflora is the cause why the region is going through shortages of potable water, leading to extensive socio economic stresses.
How to cite:
Tundia, K., Rao, A., and Shastri, Y.: Satellite based Assessment of Groundwater Depletion by the Invasive Tree Species- Prosopis juliflora in a Semi-Arid Region of Gujarat, India , EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-12254, https://doi.org/10.5194/egusphere-egu22-12254, 2022.