Global warming alters surface water availability (precipitation minus evapotranspiration, P-E) and hence freshwater resources. However, the influence of land-atmosphere feedbacks on future P-E changes and the underlying mechanisms remain unclear. Here we demonstrate that soil moisture (SM) strongly impacts future P-E changes, especially in drylands, by regulating evapotranspiration and atmospheric moisture inflow. Using modeling and empirical approaches, we find a consistent negative SM feedback on P-E, which may offset ~60% of the decline in dryland P-E otherwise expected in the absence of SM feedbacks. The negative feedback is not caused by atmospheric thermodynamic responses to declining SM, but rather reduced SM, in addition to limiting evapotranspiration, regulates atmospheric circulation and vertical ascent to enhance moisture transport into drylands. This SM effect is a large source of uncertainty in projected dryland P-E changes, underscoring the need to better constrain future SM changes and improve representation of SM-atmosphere processes in models.

How to cite: Zhou, S., Williams, A. P., Lintner, B., Berg, A., Zhang, Y., Keenan, T., Cook, B., Hagemann, S., Seneviratne, S., and Gentine, P.: Soil moisture-atmosphere feedbacks mitigate declining water availability in drylands, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-9028, https://doi.org/10.5194/egusphere-egu21-9028, 2021.

Interactions between the lower atmosphere and the shallow continental subsurface govern several surface processes important for ecosystems and society, such as extreme temperature and precipitation events. Transient climate simulations performed with climate models have been employed to study the water, mass and energy exchanges between the atmosphere and the shallow subsurface, obtaining large inter-model differences. Understanding the origin of differences between climate models in the simulation of near-surface conditions is crucial for restricting the inter-model variability of future climate projections. Here, we explore the effect of changes in horizontal resolution on the simulation of the surface energy balance and the climatology of near-surface conditions over North America (NA) using the Weather Research and Forecasting (WRF) model. 
We analyzed an ensemble of twelve simulations using three different horizontal resolutions (25 km, 50 km and 100 km) and four different Land Surface Model (LSM) configurations over North America from 1980 to 2013. Our results show that increasing horizontal resolution alters the representation of shortwave radiation, affecting near-surface temperatures and consequently the partition of energy into sensible and latent heat fluxes. Thus, finer resolutions lead to higher net shortwave radiation and temperature at high NA latitudes and to lower net shortwave radiation and temperature at low NA latitudes. The use of finer resolutions also leads to an intensification of the terms associated with the surface water balance over coastal areas at low latitudes, generating higher latent heat flux, accumulated precipitation and soil moisture. The effect of the LSM choice is larger than the effect of horizontal resolution on the representation of the surface energy balance, and consequently on near-surface temperature. By contrast, the effect of the LSM configuration on the simulation of precipitation is weaker than the effect of horizontal resolution, showing larger differences among LSM simulations in summer and over regions with high latent heat flux. This ensemble of simulations is then compared against CRU data. Comparison between the CRU data and the simulated climatology of daily maximum and minimum temperatures and accumulated precipitation indicates that enhancing horizontal resolution marginally improves the simulated climatology of minimum and maximum temperatures in summer, while it leads to larger biases in accumulated precipitation. The larger biases in precipitation with the use of finer horizontal resolutions are likely related to the effect of increasing resolution on the atmospheric model component, since precipitation biases are similar using different LSM configurations.

How to cite: García-García, A., Cuesta-Valero, F. J., Beltrami, H., González-Rouco, F., and García-Bustamante, E.: Surface energy balance and climatology changes from WRF simulations with different horizontal resolutions and soil configurations , EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-1185, https://doi.org/10.5194/egusphere-egu21-1185, 2021.

Rising air temperatures are a leading risk to global crop production and food security under climate change. Recent research has emphasized the critical role of moisture availability in regulating crop responses to heat and the importance of temperature-moisture couplings in the genesis of concurrent hot and dry conditions. Here, we demonstrate that the heat sensitivity of key global crops is dependent on the local strength of couplings between temperature and moisture in the climate system (namely, the interannual correlations of growing season temperature with evapotransipration and precipitation). Over 1970-2013, maize and soy yields declined more during hotter growing seasons where decreased precipitation and evapotranspiration more strongly accompanied higher temperatures. Based on this historical pattern and a suite of CMIP6 climate model projections, we show that changes in temperature-moisture couplings in response to warming could enhance the heat sensitivity of these crops as temperatures rise, worsening the impact of warming by ~5% on global average. However, these changes will benefit crops in some areas where couplings weaken, and are highly uncertain in others. Our results demonstrate that climate change will impact crops not only through warming, but also through changes in temperature-moisture couplings, which may alter the sensitivity of crop yields to heat as warming proceeds. Robust adaptation of cropping systems will need to consider this underappreciated risk to food production from climate change.

How to cite: Lesk, C., Coffel, E., Winter, J., Ray, D., Zscheischler, J., Seneviratne, S., and Horton, R.: The hidden signature of temperature-moisture couplings in the heat sensitivity of global crops, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-1419, https://doi.org/10.5194/egusphere-egu21-1419, 2021.

The planetary boundary layer (PBL) plays an essential role in climate and air quality simulations. Large uncertainties remain in understanding the long-term trend of PBL height (PBLH) and its simulation. Here we use the radiosonde data and reanalysis datasets to analyze PBLH long-term trends over China, and to further evaluate the performance of CMIP6 climate models in simulating these trends. Results show that the observed long-term “positive to negative” trend shift of PBLH is related to the variation in the surface upward sensible heat flux (SHFLX) which is further controlled by the synergistic effect of low cloud cover (LCC) and soil moisture (SM) changes. Variabilities in low cloud cover and soil moisture directly influence the energy balance via surface net downward shortwave flux (SWF) and the latent heat flux (LHFLX), respectively. We have found that the CMIP6 climate models cannot reproduce the observed PBLH long-term trend shift over China. The CMIP6 results show an overwhelming continuous downward PBLH trend during the 1979-2014 period, which is caused by the poorly simulated long-term changes of cloud radiative effect. Our results reveal that the long-term cloud radiative effect simulation is critical for CMIP6 models in reproducing the PBLH long-term trends. This study highlights the importance of low cloud cover and soil moisture processes in modulating PBLH long-term variations and calls attentions to improve these processes in climate models in order to improve the PLBH long-term trend simulations.

How to cite: Yue, M., Wang, M., Guo, J., Zhang, H., Dong, X., and Liu, Y.: Long-term Trend Comparison of Planetary Boundary Layer Height in Observations and CMIP6 models over China, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-1706, https://doi.org/10.5194/egusphere-egu21-1706, 2021.

Tropical islands are commonly seen as hot spots that heat the troposphere, since during the day, they typically become warmer than the ocean. However, at the same time, they also become dryer (in terms of relative humidity), due to the soil's resistance to evaporate. The surface warm and dry anomaly is then propagated upwards into the troposphere by thunderstorms (deep convection) that frequently form over the islands. The vertical propagation of the anomaly happens because the warmer surface over land tends to push the induced diurnal convection towards a warmer moist adiabat. However, the drying of the land surface also pulls the clouds towards a colder moist adiabat, as more initial lifting along the dry adiabat is needed until saturation is reached. In other words, a dryer island leads to a more elevated cloud base, and thus, to convection at a colder moist adiabat. The formation of convective clouds over land results in a local density anomaly that is then communicated to the island's surroundings by gravity waves since the tropical atmosphere cannot sustain strong horizontal density gradients (WTG theory). Together these ideas allow formulating the hypothesis that surface temperature and humidity anomalies emerging over islands project onto the large-scale temperature profile of the troposphere. Who wins in influencing the troposphere, the surface warming or the drying? Or put differently, do islands heat or cool the troposphere?

We assess this hypothesis using a six-member ensemble of double-periodic convection-resolving Radiative-Convective Equilibrium (RCE) simulations (1006x1006x74 grid points), containing an archipelago of flat islands obtained from the Maritime Continent. In contrast to previous RCE simulations, the islands are represented by a land-surface scheme and are thus capable of representing not only the daytime anomaly in temperature but also that in relative humidity. We find that during episodes when precipitation occurs more frequently over land, the domain-mean (virtual) temperature in the mid-troposphere becomes colder. We also find that the drying (i.e, cooling) effect becomes pronounced for larger islands, and thus, removing a large island from the simulation also leads to a systematically colder domain-mean (virtual) temperature profile. The results suggest that islands may rather cool than warm the troposphere and that the inability of evaporation over land to keep up with the daytime surface warming is of key relevance for the temperature profile in the Maritime Continent.

How to cite: Leutwyler, D. and Hohenegger, C.: Do tropical islands warm or cool the troposphere?, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-2523, https://doi.org/10.5194/egusphere-egu21-2523, 2021.

The diurnal variations of surface and air temperature are related but their different responses to evaporative conditions can inform us about land-atmosphere interactions, extreme events, and their response to global change. Here, we evaluate the sensitivity of the diurnal ranges of surface (DT_sR) and air (DT_aR) temperature to evaporative fraction, across short vegetation, savanna, and forests at 106 Fluxnet observational sites and in the ERA5 global reanalysis. We show that the sensitivity of DT_sR to evaporative fraction depends on vegetation type, whereas for DT_aR it does not. Using FLUXNET data we found that on days with low evaporative fraction, DT_sR is enhanced by up to 20 °C (30 °C in ERA5) in short vegetation, whereas only by 8 °C (10 °C in ERA5) in forests. Particularly, in short vegetation, ERA5 shows stronger responses, which is attributable to a negative bias on days with the high evaporative fraction. ERA5 also tends to have lower shortwave and longwave radiation input when compared to FLUXNET data. Contrary to DT_sR, DT_aR responds rather similarly to evaporative fraction irrespective of vegetation type (8 °C in FLUXNET, 10 °C in ERA5). To explain this, we show that the DT_aR response to the evaporative fraction is compensated for differences in atmospheric boundary layer height by up to 2000 m, which is similar across vegetation types. We demonstrate this with a simple boundary layer heat storage calculation, indicating that DT_aR is primarily shaped by changes in boundary layer heat storage whereas DT_sR mainly responds to solar radiation, evaporation, and vegetation.  Our study reveals some systematic biases in ERA5 that need to be considered when using its temperature products for understanding land-atmosphere interactions or extreme events. To conclude, this study demonstrates the importance of vegetation and the dynamics of the atmospheric boundary layer in regulating diurnal variations in surface and air temperature under different evaporative conditions.

How to cite: Panwar, A. and Kleidon, A.: Evaluating the response of the diurnal range of surface and air temperature to evaporative conditions across vegetation types in ERA5 and FLUXNET data, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-2603, https://doi.org/10.5194/egusphere-egu21-2603, 2021.

Land use information is crucial in weather modelling as it determines the energy partitioning of the land surface. Based on the partitioning heating of near surface air and moisture supply of the planetary boundary layer is determined. These processes affect the general calculation of temperature, but it also has substantial effect on precipitation formation, especially on convective precipitation.

In this study the CORINE 44 categories are integrated into the WRF model. Usually the 44 land cover types are recategorized into a standard USGS or MODIS land use types. Here we present a dataset and application with the complete integration of the 44 types.

One-year runs are created with the CORINE land cover compared to the standard USGS dataset. Along with the new land cover types vegetation parameters had be defined as well. Four runs refer to a USGS-reference, CORINE2USGS converted, CORINE-USGS parameter, CORINE-newparameters where the effect of land cover and parameter change is analyzed. The modelled area covers the whole European region with 50 km resolution using the WRF 4.2 model. Regionally, on a monthly average 5-30% difference in precipitation and around 1 °C differences occur.

The research was supported by the Hungarian National Research, Development and Innovation Office, Grant No. FK132014. Hajnalka Breuer's work was additionally financed by the János Bolyai Research Scholarship of the Hungarian Academy of Sciences.

How to cite: Breuer, H., Zempléni, Z., and Varga, Á.: Application of the complete CORINE land covers for modelling in WRF model, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-2940, https://doi.org/10.5194/egusphere-egu21-2940, 2021.

Groundwater (GW) constitutes by far the largest volume of liquid freshwater on Earth. The most active part is soil moisture (SM), which plays a key role on land/atmosphere interactions. But GW is often stored in deep reservoirs below the soil as well, where it presents slow horizontal movements along hillslopes toward the river network. They end up forming baseflow with well-known buffering effects on streamflow variability, but they also contribute to sustain higher SM values, especially in the lowland areas surrounding streams, which are among the most frequent wetlands.  As a result, GW-SM interactions may influence the climate system, in the past but also in the future, with a potential to alleviate anthropogenic warming, at least regionally, owing to enhanced evapotranspiration rate (ET) or higher soil thermal inertia for instance.
To assess where, when, and how much GW-SM interaction affects the climate change trajectories, we use coupled land-atmosphere simulations with the IPSL-CM6 climate model, developed by the Institut Pierre Simon Laplace for CMIP6.  We contrast the results of two long-term simulations (1979-2100), which share the same sea surface temperature and radiative forcing, using the SSP5-8.5 scenario (i.e. the most pessimistic) for 2015-2100. The two simulations differ by their configuration of the land surface scheme ORCHIDEE: in the default version, there is no GW-SM interaction, while this interaction is permitted in the second simulation, within a so-called lowland fraction, fed by surface and GW runoff from the rest of the grid-cell. For simplicity, this lowland fraction is set constant over time, but varies across grid-cells based on a recently designed global scale wetland map. 
Within this framework, we analyse the impact of the GW-SM interaction on climate change trajectories, focusing on the response of evapotranspiration rates and near-surface air temperatures. The GW-SM interaction can modulate the response to climate change by amplifying, attenuating, or even inverting the climate change trend. Based on yearly mean values over land, we find that the GW-SM interaction amplifies the response of evapotranspiration to climate change, as the mean evapotranspiration rate increases 50% faster over 1980 - 2100 in the simulation with GW-SM interaction. In contrast, the mean warming over land is 1% weaker, shifting from 6.4 to 6.3 °C/100 years; thus attenuated, if the GW-SM interaction is accounted for. In both cases, these values hide important differences across climates and seasons, with mitigation or amplification for both variables, indicating the need for regional and seasonal assessment. We will also further explore how GW-SM interaction impacts the future evolution of heatwaves, in terms of duration and frequency. 

How to cite: Arboleda, P., Ducharne, A., and Cheruy, F.: Impact of groundwater – soil moisture interaction on evolution of evapotranspiration and air temperature under climate change, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-5011, https://doi.org/10.5194/egusphere-egu21-5011, 2021.

Vegetation productivity is generally governed by water and energy availability. In arid regions, it is usually water-controlled (i.e. soil moisture), whereas in humid regions it is mainly influenced by energy variables (i.e. incoming radiation). Shifts within or even between these regimes might result from hydro-meteorological extremes. For example, during droughts vegetation might become water-limited even in typically energy-controlled regions. In this context, the aim of our analysis is to detect the difference between the controls of average and extreme vegetation productivity.

For this purpose, we use global satellite-based Sun-Induced Chlorophyll Fluorescence (SIF) data as a proxy for vegetation productivity alongside several hydro-meteorological variables. We select the three largest positive and negative monthly SIF anomalies from 2007 – 2015 and determine the hydro-meteorological variable with the largest corresponding standardized anomaly, which is considered to represent the main driver of the respective vegetation extreme.

We aggregate the results across grid cells of similar climate conditions. By contrasting main controls and their importance on vegetation productivity during extreme and general conditions, we find that water control in arid regions and energy control in humid regions are overall consistent in both conditions, while the importance of deep root-zone soil moisture is significantly increased in arid regions. Then, we identify regions where transitions between water and energy-control occur and further assess to which extent such regime transitions amplify vegetation productivity anomalies and/or impact their recovery.

This study contributes to a better understanding of vegetation productivity extremes, which may change with changing future patterns of temperature and precipitation, with subsequent feedbacks on the climate system and implications on food security.

How to cite: Kroll, J., Denissen, J., Li, W., and Orth, R.: Global hydro-meteorological anomalies associated with vegetation productivity extremes, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-2988, https://doi.org/10.5194/egusphere-egu21-2988, 2021.

Droughts cause serious environmental and societal impacts, often aggravated by simultaneously occurring heat waves. Climate model projections suggest that droughts and high temperatures will further intensify over the next century. Thus, understanding the underlying mechanisms responsible for drought-induced heat is crucial to inform drought management strategies and to improve prediction of dry-hot extremes, especially under a changing climate. Using observation-based, global data over 2001-2015, we show hottest temperature anomalies during droughts in sub-humid and tree-dominated regions. This is mainly driven by a drought-related net radiation surplus and further amplified by forests’ water saving strategies that result in diminished evaporative cooling. By contrast, in semi-arid and short-vegetation regions, drought-related temperature increases are smaller. The reduction of evaporative cooling is weak and net radiation increases only marginally due to higher albedo over drought-stressed vegetation. As a result, our findings show the relative roles of climate and vegetation in shaping drought-heat extremes across space and highlight the importance of considering all interacting factors in understanding concurrent drought-heat extremes.

How to cite: Oh, S., Bastos, A., Reichstein, M., Li, W., Denissen, J., Graefen, H., and Orth, R.: Hottest drought temperature anomalies in sub-humid regions, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-3258, https://doi.org/10.5194/egusphere-egu21-3258, 2021.

Land surface models underpin coupled climate model projections of droughts and heatwaves. However, the lack of simultaneous observations of individual components of evapotranspiration, concurrent with root-zone soil moisture, has limited previous model evaluations. Here, we use a comprehensive set of observations from a water-limited site in southeastern Australia including both evapotranspiration and soil moisture to a depth of 4.5 m to evaluate the Community Atmosphere-Biosphere Land Exchange (CABLE) land surface model. We demonstrate that alternative process representations within CABLE had the capacity to improve simulated evapotranspiration, but not necessarily soil moisture dynamics - highlighting problems of model evaluations against water fluxes alone. Our best simulation was achieved by resolving a soil evaporation bias; a more realistic initialisation of the groundwater aquifer state; higher vertical soil resolution informed by observed soil properties; and further calibrating soil hydraulic conductivity. Despite these improvements, the role of the empirical soil moisture stress function in influencing the simulated water fluxes remained important: using a site calibrated function reduced the soil water stress on plants by 36 % during drought and 23 % at other times. These changes in CABLE not only improve the seasonal cycle of evapotranspiration, but also affect the latent and sensible heat fluxes during droughts and heatwaves. The range of parameterisations tested led to differences of ~150 W m^-2 in the simulated latent heat flux during a heatwave, implying a strong impact of parameterisations on the capacity for evaporative cooling and feedbacks to the boundary layer (when coupled). Overall, our results highlight the opportunity to advance the capability of land surface models to capture water cycle processes, particularly during meteorological extremes, when sufficient observations of both evapotranspiration fluxes and soil moisture profiles are available.

How to cite: Mu, M., De Kauwe, M., Ukkola, A., Pitman, A., Gimeno, T., Medlyn, B., Or, D., Yang, J., and Ellsworth, D.: Evaluating a land surface model at a water-limited site: implications for land surface contributions to droughts and heatwaves, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-4083, https://doi.org/10.5194/egusphere-egu21-4083, 2021.

We study the effect of increased resolution and more elaborate representation of land surface on the soil moisture – air temperature coupling with the WRF climate downscaling model. Previous work indicated reduced winter/spring rainfall and enhanced summer heat. Two different land surface schemes (LSS) Noah and NoahMP with dynamic vegetation option turned on are incorporated in the WRF regional climate model in simulations at 50 and 16 km horizontal resolution over the region of Middle East and North Africa (MENA) for the period of 2000-2004. An analysis is performed for the summer season (June-July-August; JJA) for the four-year period, employing coupling metrics, i.e. associations between climatic variables related to the soil moisture – air temperature coupling. We calculate correlation coefficients between time-series consisting of 10-day averages, non-overlapping, for related surface climate variables from the WRF simulations and observational datasets. This assessment indicates that the NoahMP scheme simulates a stronger coupling than the Noah, irrespective of the resolution. The strength of this coupling varies at different areas around the MENA when considering mean or maximum 2-meter air temperature, with the NoahMP at 16-km producing the strongest effect over the western Asia part of the domain.

How to cite: Constantinidou, K., Hadjinicolaou, P., Zittis, G., and Lelieveld, J.: Varying horizontal resolution and land surface schemes in soil moisture – air temperature coupling, calculated with the WRF model for the MENA-CORDEX domain, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-4099, https://doi.org/10.5194/egusphere-egu21-4099, 2021.

Gross primary productivity (GPP) plays a vital role in the carbon storage potential of ecosystems. Climate change (CC), land use and cover change (LUCC), elevated CO₂ concentrations (eCO₂), and Nitrogen deposition (Ndep) are the main driving forces of GPP. Climate extremes are expected to negatively impact ecosystem carbon uptake (Du et al., 2018, Sci. Total Environ.). The knowledge of impacts of hydroclimatic disturbances (temperature, precipitation, soil moisture, drought, fire emission) on the GPP extremes is still limited for the Indian ecosystems. This study aims to quantify the GPP extremes and assess the drivers of these extremes across Indian ecosystems.

The study considers fourteen terrestrial biosphere models (TBMs). These TBMs are DLEM, ISAM, LPJ-wsl, ORCHIDEE-LSCE, BIOME-BGC, CLM4, CLM4VIC, CLASS-CTEM-N, GTEC, Sib3, SibCASA, TEM6, VISIT, and VEGAS2.1, which took part in the Multi-scale Synthesis and Terrestrial Model Intercomparison Project (MsTMIP). We consider these models' GPP ensemble values from 1981-2010 for four cases: CC, CC+LUCC, CC+LUCC+eCO₂, and CC+LUCC+eCO₂+Ndep. This multi-model ensemble approach predicts better estimates as it captures uncertainty better than a single model (Schwalm et al., 2015, Geophys. Res. Lett.). We also consider an observation-based model by Jung et al. (2011) along with these ensembles. We use a 3-D contiguous (Zscheischler et al., 2013, Ecol. Inform)   statistical approach to assess the spatiotemporal pattern of extreme GPPs in India and in its six meteorologically homogeneous regions. We also diagnose the size distribution and attribution of these negative extreme GPP events to each of these drivers individually and multiple drivers in a compounded way.

How to cite: Chakraborty, A., Muddu, S., and Rao, L.: Assessment of Impact of Hydroclimatic Disturbances on Terrestrial GPP Extremes of India Under Land Use and Climate Change, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-4195, https://doi.org/10.5194/egusphere-egu21-4195, 2021.

Recent accelerating global warming with increasing climate variability exerts a strong impact on terrestrial carbon budgets, but the ecosystem response to the changing climate and the overall climate-vegetation coupling remain largely unclear during different stages of the growing season. The timing of growing seasons can be modulated by different environmental conditions (e.g., thermal and hydrological changes) and affect the overall interpretation of regional climate-vegetation coupling. Here, we analyse the climate-vegetation coupling for Europe during 1982–2014 using a grid-wise definition of the growing season period based on remote sensing data. We quantify sub-seasonal anomalies of vegetation greenness from long-term vegetation indices (Normalized Difference Vegetation Index and two-band Enhanced Vegetation Index), and their relationships with corresponding local growing conditions (2m temperature, downwards surface solar radiation and root-zone soil moisture); and with multiple climate variability indices that reflect the large-scale climatic conditions over Europe. We find that early growing season anomalies in vegetation greenness tend to be large during the first two months of the growing season and that the coupling of these anomalies with large-scale climate largely determines the full-year climate-vegetation coupling. The North Atlantic Oscillation (NAO) and Scandinavian Pattern (SCA) phases evaluated one to two months before the start of growing season are the dominant drivers of the early growing season climate-vegetation coupling over large parts of boreal and temperate Europe. However, the sign of the effect of these indices on vegetation greenness is opposite. The East Atlantic Pattern (EA) evaluated several months in advance of the growing season is instead a main controlling factor on the temperate belt and the Mediterranean region. These findings highlight the importance of accounting for the spatial heterogeneity of growing season periods using location-specific definitions when studying large-scale land-atmosphere interactions.

How to cite: Wu, M., Vico, G., Manzoni, S., Cai, Z., Bassiouni, M., Tian, F., Zhang, J., Ye, K., and Messori, G.: Anomalies in vegetation activity in the early growing season determine the climate-vegetation coupling in Europe, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-4609, https://doi.org/10.5194/egusphere-egu21-4609, 2021.

The rooting zone water storage capacity (S) defines the total amount of water available to plants for transpiration during rain-free periods. Thereby, S determines the sensitivity of carbon and water exchanges between the land surface and the atmosphere, controls the sensitivity of ecosystem functioning to progressive drought conditions, and mediates feedbacks between soil moisture and near-surface air temperatures. While being a central quantity for water-carbon-climate coupling, S is inherently difficult to observe. Notwithstanding scarcity of observations, terrestrial biosphere and Earth system models rely on the specification of S either directly or indirectly through assuming plant rooting depth.

Here, we model S based on the assumption that plants size their rooting depth to maintain function under the expected maximum cumulative water deficit (CWD), occurring with a return period of 40 years (CWD_X40), following Gao et al. (2014). CWD_X40 is “translated” into a rooting depth by accounting for the soil texture. CWD is defined as the cumulative evapotranspiration (ET) minus precipitation, where ET is estimated based on thermal infrared remote sensing (ALEXI-ET), and precipitation is from WATCH-WFDEI, modified by accounting for snow accumulation and melt. In contrast to other satellite remote sensing-based ET products, ALEXI-ET makes no a priori assumption about S and, as our evaluation shows, exhibits no systematic bias with increasing CWD. It thus provides a robust observation of surface water loss and enables estimation of S with global coverage at 0.05° (~5 km) resolution.

Modelled S and its variations across biomes is largely consistent with observed rooting depth, provided as ecosystem-level maximum estimates by Schenk et al. (2002), and a recently compiled comprehensive plant-level dataset. In spite of the general agreement of modelled and observed rooting depth across large climatic gradients, comparisons between local observations and global model predictions are mired by a scale mismatch that is particularly relevant for plant rooting depth, for which the small-scale topographical setting and hydrological conditions, in particular the water table depth, pose strong controls.

To resolve this limitation, we investigate the sensitivity of photosynthesis (estimated by sun-induced fluorescence, SIF), and of the evaporative fraction (EF, defined as ET over net radiation) to CWD. By employing first principles for the constraint of rooting zone water availability on ET and photosynthesis, it can be derived how their sensitivity to the increasing CWD relates to S. We make use of this relationship to provide an alternative and independent estimate of S (S_dSIF and S_dEF), informed by Earth observation data, to which S, modelled using CWD_X40, can be compared. Our comparison reveals a strong correlation (R²=0.54) and tight consistency in magnitude between the two approaches for estimating S. 

Our analysis suggests adaptation of plant structure to prevailing climatic conditions and drought regimes across the globe and at catchment scale and demonstrates its implications for land-atmosphere exchange. Our global high-resolution mapping of S reveals contrasts between plant growth forms (grasslands vs. forests) and a discrepant importance across the landscape of plants’ access to water stored at depth, and enables an observation-informed specification of S in global models.

How to cite: Stocker, B., Tumber-Davila, S., Konings, A., and Jackson, R.: Global carbon and water exchange during drought reflects adaptation of rooting depth to climate and topography, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-6376, https://doi.org/10.5194/egusphere-egu21-6376, 2021.

It has been shown that European heatwaves can be significantly intensified by dry land surface conditions. While local temperature intensification through soil moisture feedbacks are well understood, the role of nonlocal soil moisture conditions has yet to be studied in more detail. Studies suggest that through modification of the atmospheric circulation, soil moisture conditions can enhance local temperatures and even evoke a remote temperature response. 

In this study, we analyze how nonlocal soil moisture – atmosphere feedbacks contribute to the development of high temperature extremes during a seasonally persistent European heatwave. We use a CESM-based global circulation model framework described in Merrifield et al. (2019), in which near-identical heatwave-inducing atmospheric circulation patterns encounter different land surface conditions. In one ensemble the whole atmosphere is constrained, allowing only local temperature intensification by the land surface. In the other ensemble only the upper atmosphere is constrained, enabling the land surface to modify the atmospheric circulation below 300hPa.

To understand what variables and processes contribute to regional heatwave intensification in some members and damping in others on a daily timescale, a refined spatio-temporal analysis of the data set was performed. We find that local daily temperature spread across ensemble members amounts to 5°C in the ensemble with unconstrained lower atmosphere, which is 4°C more than in the ensemble where the whole atmosphere is constrained, highlighting the importance of nonlocal land – atmosphere interactions. We identify atmospheric pathways through which the land surface state in one region affected the intensity of the heatwave in another region during the initiation, peak, and decay phases of the event. These heatwave intensification storylines may help to inform seasonal prediction and improve preparedness for future European heat events.

How to cite: Bohnenblust, R., Merrifield, A. L., Sippel, S., Simpson, I. R., McKinnon, K. A., Fischer, E. M., Deser, C., and Knutti, R.: Nonlocal soil moisture effects during European heatwaves, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-2754, https://doi.org/10.5194/egusphere-egu21-2754, 2021.

Biogenic volatile organic compounds (BVOCs) are emitted globally at about 1,100 Tg per year, with almost half of the share entailed by isoprene. Isoprene is highly reactive in the atmosphere, and its degradation impacts the atmospheric composition through the generation of ozone (in presence of NOx typical of polluted areas) and secondary organic aerosols, which both pose a risk to human health. Extreme weather conditions like heatwaves and droughts can substantially affect the emissions of isoprene in ways that are largely unknown. This limited knowledge is owed to the scarcity of isoprene flux measurements under drought stress conditions. The Missouri Ozarks AmeriFlux (MOFLUX) site is located in a high isoprene-emitting oak-hickory forested region with recurring drought occurrences. Until today, it is the only site with isoprene flux measurements that capture drought behaviour.

In this study, we use the state-of-the-art MEGAN biogenic emission model (Guenther et al., 2006; 2012) coupled with the canopy model MOHYCAN (Müller et al., 2008) to estimate isoprene emissions and evaluate two different parameterizations of the soil moisture stress factor (γ_SM): (a) the one used in MEGANv2.1, which consists of a simple dependence on soil water content and the permanent wilting point with inputs either from ERA-Interim or the GLEAMv3 reanalysis (Martens et al., 2017), and (b) the parameterization available in MEGANv3 (Jiang et al., 2018), which considers the physiological effects of drought stress on plant photosynthesis as defined in the Community Land Model (CLM4.5), which embeds the MEGAN model.  The effect of γ_SM on isoprene estimates is assessed against measurements of isoprene fluxes at the MOFLUX field site collected during the mild summer drought in 2011 (Potosnak et al., 2014) and the severe drought in 2012 (Seco et al., 2015). Based on the comparisons at the MOFLUX site, we perform an optimization of the empirical parameters of the MEGANv2.1 soil moisture stress parameterization. In addition, the parameterization is further evaluated using spaceborne formaldehyde (HCHO) columns observed by the OMI sounder. To this end, we perform multiyear simulations (2005-2016) of atmospheric composition with the IMAGES global chemistry-transport model (Müller et al., 2019) using isoprene emission datasets obtained for several variants of the parameterization. We evaluate the resulting HCHO column distributions and their interannual variability against OMI HCHO columns over drought-prone regions.

This work is conducted in the frame of the ALBERI project, funded by the Belgian Science Policy Office through the STEREO III programme.

How to cite: Opacka, B., Stavrakou, T., Müller, J.-F., Bauwens, M., Miralles, D., Koppa, A., Pagán, B., and Guenther, A. B.: Evaluation of soil moisture stress parameterizations in MEGAN model against MOFLUX field data and satellite observations of formaldehyde from OMI , EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-7021, https://doi.org/10.5194/egusphere-egu21-7021, 2021.

Weather extremes are predicted to be more intense and recurrent in the future because of climate change. Previous studies show that Mediterranean regions around the world are especially vulnerable to extreme events that depend on the hydrological cycle, such as droughts and floods. Land use and land cover changes may enhance these events, as they influence the exchange of moisture and energy between the land surface and atmosphere. To better understand the role of extremes in a future climate, we need to improve our understanding of the impact of climate change on the terrestrial hydrological cycle. Atmospheric transport of moisture is an important element of this cycle as it determines the allocation of evaporated moisture. We are especially interested in the sink-source relations. So, how land contributes to the moisture recycling over land further away, and the origin of the precipitation over, the so-called precipitation-shed. Tuinenburg et al. (2020) recently published a dataset with high-resolution global atmospheric moisture connections from evaporation to precipitation, allowing novel detailed insight. We used this dataset to study temporal variability in atmospheric moisture connections for five different regions with Mediterranean climates. We investigated the dependency of different Mediterranean regions on local and remote moisture sources, and how this dependency varies throughout the year. Large differences in the spatial pattern of moisture recycling over land showed to exist between the Mediterranean regions on the Northern and Southern Hemisphere. Additionally, of all regions, the Mediterranean Basin shows the largest temporal variability. This information is essential to study how local changes in land use and land cover have and will further affect the hydrological cycle in local and remote regions. This helps us to understand how climate extremes could change in the future as a result of land use and land cover changes.  

Tuinenburg, O. A., Theeuwen, J. J. E., and Staal, A. Global evaporation to precipitation flows obtained with Lagrangian atmospheric moisture tracking, PANGAEA, https://doi.org/10.1594/PANGAEA.912710, 2020.

How to cite: Theeuwen, J., Tuinenburg, O., Staal, A., Hamelers, B., and Dekker, S.: Moisture recycling in five different regions with Mediterranean climates around the world, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-7248, https://doi.org/10.5194/egusphere-egu21-7248, 2021.

The state of the land surface can have a crucial influence on the triggering of convection. Investigations of the land-atmosphere coupling strength on the regional scale are still rare, and have been mainly performed using global climate models with coarse resolutions. Increasing the horizontal resolution and the concomitant improved representation of the land surface are expected to refine the representation of feedbacks. A strong limiting factor, especially for process-based studies of the link between surface moisture availability, land cover properties, and convection triggering, is the availability of data with sufficient vertical resolution and temporal coverage. A convenient metric to investigate this link is the ‘Convection Triggering Potential’-‘Low-Level Humidity Index’ framework, which is applied in this study. This process-based coupling metric examines the boundary layer structure based on temperature and humidity profiles to draw conclusions on the potential strength of interactions. However, increasing the resolution of a simulation usually aggravates the amount of storage capacity needed, and in practice the number of vertical levels written out is often decreased to a handful over the total column. Consequently, a comprehensive regional model intercomparison targeting land-convection coupling strength is challenging.

In this study, a perturbation approach was applied as an attempt to overcome this limitation. Differences in the choice and configuration of models cause a spread in mean and variance of atmospheric temperature and humidity between models that in turn may impact the outcome of the framework. Perturbation factors of different magnitudes were added to modify summer atmospheric temperature and humidity from a WRF simulation over the entire column on a daily basis. The simulation covered the period 1986-2015 over the EURO-CORDEX domain. The perturbations were chosen to approximate a potential model spread to some extent. Sensitivity in the coupling strength was assessed in relation to the unperturbed case by applying the framework to a range of perturbation cases with differently strong combinations of temperature and humidity changes.

We will present results 1) of how warmer, cooler, dryer or moister conditions in the atmosphere changed the frequency of summer days with high feedback potential, 2) how the different conditions influenced the occurrence of positive relative to negative feedbacks, and 3) of spatial differences in the sensitivity of the coupling strength to temperature or humidity modifications, respectively, over Europe.

How to cite: Jach, L., Schwitalla, T., Warrach-Sagi, K., and Wulfmeyer, V.: Study of the sensitivity of land-convection coupling in the European summer, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-8406, https://doi.org/10.5194/egusphere-egu21-8406, 2021.

Across West Africa rain-fed agriculture fulfils approximately 80% of the food needs of the population and employs 60% of the workforce. It is therefore critical to understand the effects of intraseasonal rainfall variability across West Africa. Previous work has shown that land-atmosphere interactions across West Africa can influence daily variability in deep convection characteristics and the impact of 10-25 day precipitation variability. Using earth observations and reanalyses, this study investigates the land surface response to 20-200 day precipitation variability and its impact on land-atmosphere interactions and the West African monsoon.

                Surprisingly, even though the sensitivity of the land surface across the Sahel to strong convection is short-lived (days) and daily precipitation patterns are strongly heterogeneous, a coherent regional-scale land surface response to 20-200 day precipitation variability is observed. This sensitivity of the land surface affects land-atmosphere interactions on a regional scale and perturbs the West African monsoon circulation. For example, during sub-seasonal periods of low rainfall, soil moisture significantly decreases across the Sahel and land surface temperatures increase by up to 2°C. Surface drying and warming across the Sahel is associated with an intensified heat low and a northward shift of low-level monsoon westerlies. During periods of high rainfall, the surface moistens and cools, which is associated with a high pressure tendency across the Sahel. This high pressure tendency dampens the heat low circulation across West Africa and reduces regional moisture fluxes. We show that the land surface response to 20-200 day rainfall variability across West Africa can have a significant impact on the monsoon circulation. This suggests that improving the representation of land-surface processes across West Africa has the potential to improve sub-seasonal forecast predictability and enhance early warning systems.

How to cite: Talib, J., Taylor, C., Klein, C., L. Harris, B., R. Anderson, S., and V. Shamsudheen, S.: The response of land-atmosphere interactions and the atmospheric circulation across West Africa to intraseasonal variability, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-8413, https://doi.org/10.5194/egusphere-egu21-8413, 2021.

Terrestrial evapotranspiration (ET) is a key factor in the global energy and water cycles. It is constrained by the transport of moisture from the soil and from vegetation to the atmosphere. The water storage capacity in the root zone (S_r) is an important parameter in land-atmosphere water exchanges, defining how long vegetation is able to transpire during drought. However, S_r is hard to measure directly, being associated with the depth of plant roots actively involved in water uptake and the potential of tap roots accessing deep water and enabling sustained transpiration during drought.

In this study, we present a method to estimate S_r from flux measurements, based on a deep neural network approach trained on eddy covariance (EC) data, multiple soil moisture datasets and a remotely sensed index of vegetation greenness. We derive a soil moisture stress function (fET) that isolates the control of soil moisture on ET. We then use EC data to estimate S_r by investigating how it relates to the climatology of the maximum cumulative water deficit (CWD, defined as the cumulative difference between actual ET and precipitation) experienced by the vegetation across different sites. We hypothesize that plants exposed to high CWD develop higher S_r (acclimation to water stress) and that maximum CWD is thus a good estimator of S_r. To identify root zone water storage from flux measurements, we regress the output of fET against CWD and estimate the maximum CWD for stress by calculating the intersection of the regression line with the x-axis. The apparent sensitivity of fET to CWD and its correlation with the maximum CWD across sites are indicative of adaptation to the prevailing climate and drought regime.

We find that for many sites, particularly in seasonally dry climates, fET does not exhibit a continuous decline with increasing CWD, but follows a step-change and levelling off. That is, at the high end of the CWD spectrum, fET no longer appears sensitive to further increases in CWD. This suggests that plants may have access to deep water reservoirs during the unfolding of a drought event, indicating that plant access to water becomes decoupled from water use.

This study highlights the need to investigate the representation of plant access to deep water reservoirs during drought in terrestrial ecosystem models. These findings could improve our understanding of land-climate interactions, particularly under water-limited conditions.

How to cite: Giardina, F., Gentine, P., Konings, A. G., and Stocker, B. D.: Estimating root zone storage capacity from flux measurements, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-9248, https://doi.org/10.5194/egusphere-egu21-9248, 2021.

With increasingly higher spatial resolution and a broader applications, the importance of soil representation (e.g. soil depth, vertical discretisation, vegetation rooting) within land surface models is enhanced. Those modelling choices actually affects the way land surfaces store and regulate water, energy and also carbon fluxes. Heat and water vapour fluxes towards the atmosphere and deeper soil, exhibit variations spanning a range of time scales from minutes to months in the coupled land-atmosphere system. This is further modulated by the vertical roots' distribution, and soil moisture stress function, which control evapotranspiration under soil moisture stress conditions. Currently in the ECMWF land Surface Scheme the soil column is represented by a fixed 4 layers configuration with a total of approximately 3m depth.

In the present study we explore new configurations with increased soil depth (up to 8m) and higher vertical discretisation (up to 10 layers) including a dissociation between the treatment of water and heat fluxes. Associated with the soil vertical resolution, the vertical distribution of roots is also investigated. A new scheme that assumes a uniform root distribution with an associated maximum rooting depth is explored. The impact of these new configurations is assessed through surface offline simulations driven by the ERA5 meteorological forcing against in-situ and global products of energy, water and carbon fluxes with a particular focus on the diurnal cycle and extreme events in recent years.

How to cite: Boussetta, S., Arduini, G., Balsamo, G., Dutra, E., Agusti-Panareda, A., Zoster, E., and Stevens, D.: What’s the impact of improved soil representations in the ECMWF land surface model and how does it affect the extremes?, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-9740, https://doi.org/10.5194/egusphere-egu21-9740, 2021.

The land-atmosphere interactions via the energy and water exchanges at the ground surface generally translate into a strong connection between the surface air temperature (SAT) and the ground surface temperature (GST). In turn, the surface temperature affects the amount of heat flowing into the soil, thus controlling the subsurface temperature profile. As soil temperature (ST) is a key environmental variable that controls various physical, biological and chemical processes, understanding the relationship between SAT and GST and STs is important.

In situ ST measurements represent the most adequate source of information to evaluate the distribution of temperature in soils and to address its influence on soil biological and chemical processes as well as on climate feedbacks. However, ST observations are scarce both in space and time. Therefore, the development of ST observational datasets is of great interest to promote analyses regarding the soil thermodynamics and the response to atmospheric warming.

We have developed a quality-controlled dataset of Soil Temperature Observations for Spain (SoTOS). The ST data are obtained from the Spanish meteorological agency (AEMET), including ST at different layers down to a depth of 1 m (i.e., 0.05, 0.1, 0.2, 0.5 and 1 m depth) for 39 observatories for the 1985–2018 period. Likewise, 2m air temperature has also been included for the same 39 sites.

SoTOS is employed to evaluate the shallow subsurface thermal regime and the SAT–GST relationship on interannual to multidecadal timescales. The results show that thermal conduction is the main heat transfer mechanism that controls the distribution of soil temperatures in the shallow subsurface. Regarding the SAT-GST relationship, there is a strong connection between SAT and GST. However, the SAT–GST coupling may be disrupted on seasonal to multidecadal timescales due to variations in the surface energy balance in response to decreasing soil moisture conditions over the last decade at some SoTOS sites. This results in larger GST warming relative to SAT. Such a response may have implications for climate studies that assume a strong connection between SAT and GST such as air temperature estimations from remote sensing products or even for palaeoclimatic analyses.

How to cite: Melo Aguilar, C., González Rouco, F., Steinert, N., García Bustamante, E., García Pereira, F., Beltrami, H., Cuesta Valero, F., and García García, A.: Surface air–soil temperature relationship and shallow soil thermal regime: a case study using a soil temperature observational dataset for Spain., EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-10351, https://doi.org/10.5194/egusphere-egu21-10351, 2021.

How to cite: García Pereira, F., González Rouco, J. F., Melo Aguilar, C., Schmid, T., Vegas Cañas, C., and Steinert, N.: An assessment of the subsurface thermal diffusion regime at some sites in the Sierra de Guadarrama , EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-10379, https://doi.org/10.5194/egusphere-egu21-10379, 2021.

Heat waves lead to major impacts on human health, food production and ecosystems, and are projected to increase with climate change. This study evaluates global climate models participating in the Coupled Model Intercomparison Project phase 6 (CMIP6) for their performance in simulating the present climate characteristics of summer heat waves. The analysis exploits the available global datasets (reanalyses, satellite products, gridded in-situ observations) to assess the realism of variables impacting the energy and water balance at the surface during heatwave events.The role of the underlying processes affecting the occurrence and intensity of the heat waves characteristics in present and future climate is also investigated based on the multi-model analysis.  A sensitivity study performed with the coupled atmospheric and land-surface modules of the IPSL climate model helps to support the multi-model analysis. A robust impact of the soil moisture on the dispersion of the heat-wave characteristics is diagnosed.  For 2 models it is possible to analyse the moist heat waves whose intensity and frequency is dramatically increased with respect to the dry heat waves at the end of the 21th century.

How to cite: Zhao, Y. and Cheruy, F.: Summer Heatwaves in Present and Future Climate simulated with global models participating in CMIP6, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-10404, https://doi.org/10.5194/egusphere-egu21-10404, 2021.

Capturing soil moisture-atmosphere feedbacks in a weather or climate model requires realistic simulation of various land surface processes. However, irrigation and other water management methods are still missing in most global climate models today, despite irrigated agriculture being the dominant land use in parts of Asia. In this study, we test the irrigation scheme available in the land model JULES (Joint UK Land Environment Simulator) by running land-only simulations over South and East Asia driven by WFDEI (WATCH Forcing Data ERA-Interim) forcing data. Irrigation in JULES is applied on a daily basis by replenishing soil moisture in the upper soil layers to field capacity, and we use a version of the irrigation scheme that extracts water for irrigation from groundwater and rivers, which physically limits the amount of irrigation that can be applied. We prescribe irrigation for C3 grasses in order to simulate the effects of agriculture, albeit retaining the simpler, widely used 5-PFT (plant functional type) configuration in JULES. Irrigation generally increases soil moisture and evapotranspiration, which results in increasing latent heat fluxes and decreasing sensible heat fluxes. Comparison with combined observational/machine-learning products for turbulent fluxes shows that while irrigation can reduce biases, other biases in JULES, unrelated to irrigation, are larger than improvements due to the inclusion of irrigation. Irrigation also affects water fluxes within the soil, e.g. runoff and drainage into the groundwater level, as well as soil moisture outside of the irrigation season. We find that the irrigation scheme, at least in the uncoupled land-atmosphere setting, can rapidly deplete groundwater to the point that river flow becomes the main source of irrigation (over the North China Plain and the Indus region) and can have the counterintuitive effect of decreasing annual average soil moisture (over the Ganges plain). Subsequently, we will explore the impact of irrigation on regional climate by conducting coupled land-atmosphere simulations.

How to cite: Todt, M., Vidale, P. L., McGuire, P. C., and Müller, O. V.: Irrigation in JULES Land-Only Simulations over South and East Asia, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-12213, https://doi.org/10.5194/egusphere-egu21-12213, 2021.

Climatological parameters like wind speed, temperature, boundary layer height facilitate in dispersion and accumulation of aerosols. Stagnant condition of atmosphere promote accumulation while the pollutants are more likely to get dispersed when non stagnation conditions exist. Sparse studies exist to assess the seasonal and episodic impact of stagnant weather conditions on enhancing aerosol formation in the North-East region of India.PM_2.5 sampling was carried from January to November 2019 at a regional background site in Jorhat,Assam. Meteorological variables like wind speed, surface ambient temperature and relative humidity were obtained at one-minute resolution from a collocated air weather sensor. Ventilation coefficient was calculated from wind speed and Boundary Layer Height (BLH) ( from ERA5 reanalysis dataset)

Episodic days were identified as those exceeding permissible values of PM_2.5 (National Ambient Air Quality Standards) i.e, 60µg/m³. Average wind speed on polluted and non-polluted days was 0.58±0.08 and 0.77 ± 0.17 m/s respectively. The average BLH was lower for the polluted days (243±73) than the non-polluted days (316±79). Pearson corelation coefficient of PM_2.5 and wind speeds on polluted days was low (-0.23) compared to the non-polluted days (-0.54).

Wind rose plots reveal a seasonality trend with winter and summer winds being mostly between North East and South South-West while in monsoon and autumn it lies predominantly between SSW and South South-East (from the Bay of Bengal).  The Pearson correlation coefficients between PM_2.5 and wind speeds are -0.66, -0.54 and -0.52 (all p <0.01) in winter, summer and autumn, respectively.Low average BLH persists in Winter and autumn . The seasonal maxima of BLH during winter, summer, monsoon and autumn was 847±167m, 932 ± 271m, 871 ±275m and 814 ± 256m, respectively.  Low night-time BLH (≈ 50m) in winter and autumn contributes to higher aerosol loading. The ventilation coefficient reaches its maxima during daytime around noon with summer season having the maximum daytime VC. High VC (≈270m²/s) in summer and monsoon  signify the seasonal effect on the pollutant dispersion and consequent high PM_2.5 loading. Statistically significant negative correlations were obtained between PM_2.5 and VC in winter and autumn seasons (-0.75 and -0.43).

Wind speeds have a strong correlation with PM_2.5 except for the monsoon season and play a major role in aerosol dispersion.During monsoon, weak dependence of PM_2.5 with wind speed and ventilation coefficient suggest significance of precipitation  which cause sscavenging of aerosols. Low correlations exist in summer for PM_2.5 and VC due to possible interference due to regional transport of aerosols. 5-day backward trajectory analysis suggest  transport of air masses across the Thar desert and Indo Gangetic Plains to the site during the March(summer) suggesting transport of dust across the region.

How to cite: Qadri, A., Rabha, S., Saikia, B., and Gupta, T.: Seasonal and episodic influence of local meteorology on fine particulate matter at a regional background site in North East India., EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-13059, https://doi.org/10.5194/egusphere-egu21-13059, 2021.

Our results on interannual variability in surface energy fluxes and flux drivers inform long term climate model simulations across the Arctic, which is critical for the improved prediction of the state and development of the surface energy budget and drivers under current and future conditions in this vulnerable, rapidly changing, and understudied region.

How to cite: Grysko, R., Oehri, J., and Schaepman-Strub, G.: Interannual Variability in Arctic Surface Energy Fluxes and their Drivers, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-13286, https://doi.org/10.5194/egusphere-egu21-13286, 2021.

Increasingly, we are using high-resolution convection-permitting models for climate projections but these models are less well understood in terms of the interaction between soil moisture, precipitation and evapotranspiration. The work was motivated by the discovery of warm, dry biases in summer in the 2.2 km convection-permitting model over France and eastern Europe compared to the 12 km convection-parametrised model that were associated with drier soils. We analyse several 12 km and 2.2 km versions of the Met Office Unified Model including sensitivity tests relating to soil hydraulics, land cover type and runoff model. We conduct similar tests using the land surface only to compare results between online and offline versions as the absence of some feedbacks can also produce differences.  

How to cite: Halladay, K., Berthou, S., and Kendon, E.: Understanding differences in land-atmosphere interactions between pan-European convection-permitting and parametrised climate models, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-14859, https://doi.org/10.5194/egusphere-egu21-14859, 2021.

Water and energy availability govern the exchange of carbon, energy and water between the land surface and the atmosphere and therefore exert influence on near-surface weather. Roughly one can distinguish between two evaporative regimes: One limited by available energy (under wet conditions) and one limited by available soil moisture (under dry conditions). The transition between these evaporative regimes has been studied on local to global scales using observational and modelled datasets. This revealed the complexity of defining this transition, as it varies both in space and time and is sensitive to climate, soil and vegetation characteristics.

In this study, we characterized this transition by comparing the correlations of evaporation anomalies with (i) soil moisture anomalies (proxy for strength of water control) and (ii) temperature anomalies (proxy for strength of energy control). In the first step, we use observation-based data to derive global patterns of evaporative regimes and establish that the regime transition is sensitive to not only long-term average soil moisture, but also long-term average temperature. Analyzing historical and future climate model simulations from the Coupled Model Intercomparison Project (CMIP6), we found that the ensemble mean of the CMIP6 models produces similar global patterns and sensitivities to energy and water availability. However, there is ample disagreement between results of individual models, with the largest spread around the transition zones. Further, the disagreement between individual models on the total area of water-limited regions increases gradually in time from historical to future experiments. In the next step, we attribute trends in evaporative regimes to trends in water and energy availability, CO₂ and vapor pressure deficit. This research reveals how global climate change translates into regional-global scale trends in water- vs. energy-controlled evaporative regimes. Our observational results can constrain modelled global evaporative regimes and inform future model development to decrease the substantial spread across the present model ensemble.

How to cite: Denissen, J., Teuling, A., Li, W., Reichstein, M., Pitman, A., and Orth, R.: Future trends in global water vs. energy-controlled evaporative regimes, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-3166, https://doi.org/10.5194/egusphere-egu21-3166, 2021.

Soil moisture (SM) is one of the fields with a relevant role in processes involving land-atmosphere interactions, especially in regions such as the Mediterranean Europe, where coupling between those components of the climate system is very strong. The aim of this study is to address the impact of initial soil conditions on drought and precipitation extremes over the Iberian Peninsula (IP). For this purpose, a dynamical downscalling experiment has been conducted by using the Weather Research and Forecasting model (WRF) along the period 1990-2000. Two one-way nested domains has been considered: a finer domain spanning the IP, with spatial resolution around 10 km, nested within a coarser domain covering the Euro-CORDEX region at 50 km of spatial resolution.

WRF simulations have been driven with ERA-Interim reanalysis data for all fields except for SM. Initial SM conditions can be divided into three different types: wet, dry and very dry. Values corresponding to initial SM states have been calculated by combining the WRF soil texture map along with the Soil Moisture Index (SMI). For wet conditions, SMI = 1 has been assigned; for dry conditions, SMI = -0.5; and for very dry conditions, SMI = -1. For a grid point with a given texture class, field capacity, wilting point and SMI are used to obtain initial SM. Two different initial dates have been taken into account to also consider the effect of initializing at different moments in the year: 1990-01-01 00:00:00 UTC and 1990-07-01 00:00:00 UTC. Therefore, 6 experimental runs have been carried out (2 initial dates x 3 initial SM). Additionally, a control run full-driven with ERA-Interim has been conducted from 1982 to 2000 to be used as reference. In this context, the impact of initial conditions on different extreme precipitation indices (R5xDay, SDII and R10mm) and on the Standardized Precipitation Index (SPI) for drought has been addressed.

Results could help to better understand the relevance of land-atmosphere processes in climate modeling, particularly in assessing WRF sensitivity to variations in SM and its skill to detect drought and precipitation extremes. This information could be notably useful in those applications in which initial conditions are especially relevant, such as the seasonal-to-decadal climate prediction.

Keywords: soil moisture, initial conditions, precipitation extremes, drought, regional climate, Weather Research and Forecasting model

ACKNOWLEDGEMENTS: JJRC acknowledges the Spanish Ministry of Science, Innovation and Universities for the predoctoral fellowship (grant code: PRE2018-083921). This research has been carried out in the framework of the projects CGL2017-89836-R, funded by the Spanish Ministry of Economy and Competitiveness with additional FEDER funds, and B-RNM-336-UGR18, funded by FEDER / Junta de Andalucía - Ministry of Economy and Knowledge.

How to cite: Rosa Cánovas, J. J., García-Valdecasas Ojeda, M., Yeste-Donaire, P., Romero-Jiménez, E., Esteban-Parra, M. J., Gámiz-Fortis, S. R., and Castro-Díez, Y.: An assessment of the impact of initial soil conditions on drought and precipitation extremes by using a high-resolution regional climate model, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-15973, https://doi.org/10.5194/egusphere-egu21-15973, 2021.