Explore the vast range of titles available.

Land surface temperature (LST) is a preeminent state variable that controls the energy and water exchange between the Earth’s surface and the atmosphere. At the landscape-scale, LST is derived from thermal infrared radiance measured using space-borne radiometers. In contrast, plot-scale LST estimation at flux tower sites is commonly based on the inversion of upwelling longwave radiation captured by tower-mounted radiometers, whereas the role of the downwelling longwave radiation component is often ignored. We found that neglecting the reflected downwelling longwave radiation leads not only to substantial bias in plot-scale LST estimation, but also have important implications for the estimation of surface emissivity on which LST is co-dependent. The present study proposes a novel method for simultaneous estimation of LST and emissivity at the plot-scale and addresses in detail the consequences of omitting down-welling longwave radiation as frequently done in the literature. Our analysis uses ten eddy covariance sites with different land cover types and found that the LST values obtained using both upwelling and downwelling longwave radiation components are 0.5–1.5 K lower than estimates using only upwelling longwave radiation. Furthermore, the proposed method helps identify inconsistencies between plot-scale radiometric and aerodynamic measurements, likely due to footprint mismatch between measurement approaches. We also found that such inconsistencies can be removed by slight corrections to the upwelling longwave component and subsequent energy balance closure, resulting in realistic estimates of surface emissivity and consistent relationships between energy fluxes and surface-air temperature differences. The correspondence between plot-scale LST and landscape-scale LST depends on site-specific characteristics, such as canopy density, sensor locations and viewing angles. Here we also quantify the uncertainty in plot-scale LST estimates due to uncertainty in tower-based measurements using the different methods. The results of this work have significant implications for the combined use of aerodynamic and radiometric measurements to understand the interactions and feedbacks between LST and surface-atmosphere exchange processes.

The impact of elevated air temperature and heat stress on human health is a global concern. It not only affects our well-being directly, but also reduces our physical work capacity, leading to negative effects on society and economic productivity. Climate change has already affected the climate in Luxembourg and, based on the results of regional climate models, extreme heat events will become more frequent and intense in the future. To assess historical conditions, the micro-scaleRayManPro 3.1 model was used to simulate the thermal stress levels for different genders and age classes based on hourly input data spanning the last two decades. For the assessment of future conditions, with a special emphasis on heat waves, a multi-model ensemble of regional climate models for different emission scenarios taken from the Coordinated Regional Climate Downscaling Experiment (CORDEX) was used. For both, the past and future conditions in Luxemburg, an increase in the heat stress levels was observed. Small differences for different age groups and genders became obvious. In addition to the increase in the absolute number of heat waves, an intensification of higher temperatures and longer durations were also detected. Although some indications of the adaptation to rising air temperatures can be observed for high-income countries, our results underscore the likelihood of escalating heat-related adverse effects on human health and economic productivity unless more investments are made in research and risk management strategies.

[...]the large volume of information usually produced by numerical simulations that integrate many physical processes across the terrestrial compartments and over long periods hinges to the challenge of the 4 V’s of big data and research reproducibility [8]. By providing a holistic view of the integrated water, energy and matter cycles, such models strive to define a unified and physically consistent framework for testing and validating advanced scientific hypotheses [9]. [...]as suitable models for long-term climate simulations, they represent promising decision support tools for the definition of new water management strategies and natural hazard mitigation policies [10]. In summary, this Special Issue effectively highlights some of the various challenges posed by the integration of hydrological models, such as the coupling of different processes (e.g., water flow and solute transport, both at the catchment [14] and at the hillslope scale [12]), spatio-temporal scaling issues [16], pros and cons related to use of fully physics-based integrated approaches as compared to more simplified and/or conceptual models [17], and the coupling of different eco-hydrological modules in a component-based integrated framework [20].

Operational weather and flood forecasting has been performed successfully for decades and is of great socioeconomic importance. Up to now, forecast products focus on atmospheric variables, such as precipitation, air temperature and, in hydrology, on river discharge. Considering the full terrestrial system from groundwater across the land surface into the atmosphere, a number of important hydrologic variables are missing especially with regard to the shallow and deeper subsurface (e.g., groundwater), which are gaining considerable attention in the context of global change. In this study, we propose a terrestrial monitoring/forecasting system using the Terrestrial Systems Modeling Platform (TSMP) that predicts all essential states and fluxes of the terrestrial hydrologic and energy cycles from groundwater into the atmosphere. Closure of the terrestrial cycles provides a physically consistent picture of the terrestrial system in TSMP. TSMP has been implemented over a regional domain over North Rhine-Westphalia and a continental domain over Europe in a real-time forecast/monitoring workflow. Applying a real-time forecasting/monitoring workflow over both domains, experimental forecasts are being produced with different lead times since the beginning of 2016. Real-time forecast/monitoring products encompass all compartments of the terrestrial system including additional hydrologic variables, such as plant available soil water, groundwater table depth, and groundwater recharge and storage.

Forest transpiration is controlled by the atmospheric water demand, potentially constrained by soil moisture availability, and regulated by plant physiological properties. During summer periods, soil moisture availability at sites with thin soils can be limited, forcing the plants to access moisture stored in the weathered bedrock. Land surface models (LSMs) have considerably evolved in the description of the physical processes related to vegetation water use, but the effects of bedrock position and water uptake from fractured bedrock have not received much attention. In this study, the Community Land Model version 5.0 (CLM 5) is implemented at four forested sites with relatively shallow bedrock and located across an environmental gradient in Europe. Three different bedrock configurations (i.e., default, deeper, and fractured) are applied to evaluate if the omission of water uptake from weathered bedrock could explain some model deficiencies with respect to the simulation of seasonal transpiration patterns. Sap flow measurements are used to benchmark the response of these three bedrock configurations. It was found that the simulated transpiration response of the default model configuration is strongly limited by soil moisture availability at sites with extended dry seasons. Under these climate conditions, the implementation of an alternative (i.e., deeper and fractured) bedrock configuration resulted in a better agreement between modeled and measured transpiration. At the site with a continental climate, the default model configuration accurately reproduced the magnitude and temporal patterns of the measured transpiration. The implementation of the alternative bedrock configurations at this site provided more realistic water potentials in plant tissues but negatively affected the modeled transpiration during the summer period. Finally, all three bedrock configurations did not show differences in terms of water potentials, fluxes, and performances on the more northern and colder site exhibiting a transition between oceanic and continental climate. Model performances at this site are low, with a clear overestimation of transpiration compared to sap flow data. The results of this study call for increased efforts into better representing lithological controls on plant water uptake in LSMs.

Estimation of groundwater recharge is of critical importance for effective management of freshwater resources. Three common and distinct approaches for calculating recharge rely on techniques of baseflow separation, well hydrograph analysis, and numerical modeling. In this study, these three methods are assessed for a watershed in southwestern Quebec, Canada. A physically based surface–subsurface model provides estimates of spatially distributed recharge; two baseflow separation filters estimate recharge from measured streamflow; and a well hydrograph master recession curve technique calculates recharge from water-table elevation records. The recharge results obtained are in good agreement over the entire catchment, producing an annual aquifer recharge of 10–30 % of rainfall. The annual average estimated across all methods is 200 mm/year. High variability is obtained for the monthly and seasonal recharge patterns (e.g. respectively, 0–30 mm for September and 0–95 mm for the summer), in particular between the baseflow filters and the well hydrograph technique and between the hydrograph technique and the simulated estimates at the observation wells. Recharge occurs predominantly in the spring months for the different approaches, except for the master recession curve method for which the highest recharge estimates are obtained during the summer. The recharge distribution obtained with the model shows that the main recharge area of the aquifer is the Covey Hill region. The use of a fully integrated physically based model enables the construction of an arbitrary number of well hydrographs to enhance the representativity of the master recession curve technique.

This study compares two modeling platforms, ParFlow.WRF (PF.WRF) and the Terrestrial Systems Modeling Platform (TerrSysMP), with a common 3D integrated surface–groundwater model to examine the variability in simulated soil–vegetation–atmosphere interactions. Idealized and hindcast simulations over the North Rhine–Westphalia region in western Germany for clear-sky conditions and strong convective precipitation using both modeling platforms are presented. Idealized simulations highlight the strong variability introduced by the difference in land surface parameterizations (e.g., ground evaporation and canopy transpiration) and atmospheric boundary layer (ABL) schemes on the simulated land–atmosphere interactions. Results of the idealized simulations also suggest a different range of sensitivity in the two models of land surface and atmospheric parameterizations to water-table depth fluctuations. For hindcast simulations, both modeling platforms simulate net radiation and cumulative precipitation close to observed station data, while larger differences emerge between spatial patterns of soil moisture and convective rainfall due to the difference in the physical parameterization of the land surface and atmospheric component. This produces a different feedback by the hydrological model in the two platforms in terms of discharge over different catchments in the study area. Finally, an analysis of land surface and ABL heat and moisture budgets using the mixing diagram approach reveals different sensitivities of diurnal atmospheric processes to the groundwater parameterizations in both modeling platforms.

Most activities of humankind take place in the transition zone between four compartments of the terrestrial system: the unconfined aquifer, including the unsaturated zone; surface water; vegetation; and atmosphere. The mass, momentum, and heat energy fluxes between these compartments drive their mutual state evolution. Improved understanding of the processes that drive these fluxes is important for climate projections, weather prediction, flood forecasting, water and soil resources management, agriculture, and water quality control. The different transport mechanisms and flow rates within the compartments result in complex patterns on different temporal and spatial scales that make predictions of the terrestrial system challenging for scientists and policy makers. The Transregional Collaborative Research Centre 32 (TR32) was formed in 2007 to integrate monitoring with modeling and data assimilation in order to develop a holistic view of the terrestrial system. TR32 is a long-term research program funded by the German national science foundation Deutsche Forschungsgemeinschaft (DFG), in order to focus and integrate research activities of several universities on an emerging scientific topic of high societal relevance. Aiming to bridge the gap between microscale soil pores and catchment-scale atmospheric variables, TR32 unites research groups from the German universities of Aachen, Bonn, and Cologne, and from the environmental and geoscience departments of Forschungszentrum Jülich GmbH. Here, we report about recent achievements in monitoring and modeling of the terrestrial system, including the development of new observation techniques for the subsurface, the establishment of cross-scale, multicompartment modeling platforms from the pore to the catchment scale, and their use to investigate the propagation of patterns in the state and structure of the subsurface to the atmospheric boundary layer.

Plant physiological properties have a significant influence on the partitioning of radiative forcing, the spatial and temporal variability of soil water and soil temperature dynamics, and the rate of carbon fixation. Because of the direct impact on latent heat fluxes, these properties may also influence weather-generating processes, such as the evolution of the atmospheric boundary layer (ABL). In this work, crop-specific physiological characteristics, retrieved from detailed field measurements, are included in the biophysical parameterization of the Terrestrial Systems Modeling Platform (TerrSysMP). The physiological parameters for two typical European midlatitudinal crops (sugar beet and winter wheat) are validated using eddy covariance fluxes over multiple years from three measurement sites located in the North Rhine–Westphalia region of Germany. Comparison with observations and a simulation utilizing the generic crop type shows clear improvements when using the crop-specific physiological characteristics of the plant. In particular, the increase of latent heat fluxes in conjunction with decreased sensible heat fluxes as simulated by the two crops leads to an improved quantification of the diurnal energy partitioning. An independent analysis carried out using estimates of gross primary production reveals that the better agreement between observed and simulated latent heat adopting the plant-specific physiological properties largely stems from an improved simulation of the photosynthesis process. Finally, to evaluate the effects of the crop-specific parameterizations on the ABL dynamics, a series of semi-idealized land–atmosphere coupled simulations is performed by hypothesizing three cropland configurations. These numerical experiments reveal different heat and moisture budgets of the ABL using the crop-specific physiological properties, which clearly impacts the evolution of the boundary layer.