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Sonja S. Folwell, Phil P. Harris, and Christopher M. Taylor

Abstract

Soil moisture plays a fundamental role in regulating the summertime surface energy balance across Europe. Understanding the spatial and temporal behavior in soil moisture and its control on evapotranspiration (ET) is critically important and influences heat wave events. Global climate models (GCMs) exhibit a broad range of land responses to soil moisture in regions that lie between wet and dry soil regimes. In situ observations of soil moisture and evaporation are limited in space, and given the spatial heterogeneity of the landscape, are unrepresentative of the GCM gridbox scale. On the other hand, satelliteborne observations of land surface temperature (LST) can provide important information at the larger scale. As a key component of the surface energy balance, LST is used to provide an indirect measure of surface drying across the landscape. To isolate soil moisture constraints on evaporation, time series of clear-sky LST are analyzed during dry spells lasting at least 10 days from March to October. Averaged over thousands of dry spell events across Europe, and accounting for atmospheric temperature variations, regional surface warming of between 0.5 and 0.8 K is observed over the first 10 days of a dry spell. Land surface temperatures are found to be sensitive to antecedent rainfall; stronger dry spell warming rates are observed following relatively wet months, indicative of soil moisture memory effects on the monthly time scale. Furthermore, clear differences in surface warming rate are found between cropland and forest, consistent with contrasting hydrological and aerodynamic properties.

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Phil P. Harris, Sonja S. Folwell, Belen Gallego-Elvira, José Rodríguez, Sean Milton, and Christopher M. Taylor

Abstract

Soil moisture availability exerts control over the land surface energy partition in parts of Europe. However, determining the strength and variability of this control is impeded by the lack of reliable evaporation observations at the continental scale. This makes it difficult to refine the broad range of soil moisture–evaporation behaviors across global climate models (GCMs). Previous studies show that satellite observations of land surface temperature (LST) during rain-free dry spells can be used to diagnose evaporation regimes at the GCM gridbox scale. This relative warming rate (RWR) diagnostic quantifies the increase in dry spell LST relative to air temperature and is used here to evaluate a land surface model (JULES) both offline and coupled to a GCM (HadGEM3-A). It is shown that RWR can be calculated using outputs from an atmospheric GCM provided the satellite clear-sky sampling bias is incorporated. Both offline JULES and HadGEM3-A reproduce the observed seasonal and regional RWR variations, but with weak springtime RWRs in central Europe. This coincides with sustained bare soil evaporation (Ebs) during dry spells, reflecting previous site-level JULES studies in Europe. To assess whether RWR can discriminate between surface descriptions, the bare soil surface conductance and the vegetation root profile are revised to limit Ebs. This increases RWR by increasing the occurrence of soil moisture–limited dry spells, yielding more realistic springtime RWRs as a function of antecedent precipitation but poorer relationships in summer. This study demonstrates the potential for using satellite LST to assess evaporation regimes in climate models.

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Aaron Boone, Patricia de Rosnay, Gianpaolo Balsamo, Anton Beljaars, Franck Chopin, Bertrand Decharme, Christine Delire, Agnes Ducharne, Simon Gascoin, Manuela Grippa, Françoise Guichard, Yeugeniy Gusev, Phil Harris, Lionel Jarlan, Laurent Kergoat, Eric Mougin, Olga Nasonova, Anette Norgaard, Tristan Orgeval, Catherine Ottlé, Isabelle Poccard-Leclercq, Jan Polcher, Inge Sandholt, Stephane Saux-Picart, Christopher Taylor, and Yongkang Xue

The rainfall over West Africa has been characterized by extreme variability in the last half-century, with prolonged droughts resulting in humanitarian crises. There is, therefore, an urgent need to better understand and predict the West African monsoon (WAM), because social stability in this region depends to a large degree on water resources. The economies are primarily agrarian, and there are issues related to food security and health. In particular, there is a need to better understand land-atmosphere and hydrological processes over West Africa because of their potential feedbacks with the WAM. This is being addressed through a multiscale modeling approach using an ensemble of land surface models that rely on dedicated satellite-based forcing and land surface parameter products, and data from the African Multidisciplinary Monsoon Analysis (AMMA) observational field campaigns. The AMMA land surface model (LSM) Intercomparison Project (ALMIP) offline, multimodel simulations comprise the equivalent of a multimodel reanalysis product. They currently represent the best estimate of the land surface processes over West Africa from 2004 to 2007. An overview of model intercomparison and evaluation is presented. The far-reaching goal of this effort is to obtain better understanding and prediction of the WAM and the feedbacks with the surface. This can be used to improve water management and agricultural practices over this region.

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