Abstract
Surface soil moisture (SSM) controls the the energy and water transfers between soil, vegetation and atmosphere. A better representation of this variable in Land Surface Models (LSMs) could reduce significantly the uncertainties associated to future climate predictions. Thanks to its large spatio-temporal coverage, the new ESA CCI multi-instruments dataset offers a good opportunity to benchmark LSMs and improve their parametrization with data assimilation techniques. In this study, the ESA CCI surface soil moisture (SSM) combined product is confronted with the different simulated soil layers of the ORCHIDEE LSM (the continental part of the IPSL earth system model), in order to assess whether it can be used to improve the model using data assimilation.
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