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a core project of
2018WCRPspon col July2018 01 1

ARoyer- Improvements in snow monitoring using a coupled snow evolution – microwave emission model

Description

To accurately monitor and predict snowpack properties, including snow water equivalent (SWE), over remote Northern regions remains challenging when using land surface schemes (LSS) of climate models as well as more sophisticated thermodynamic multilayered snow models (TMSM) without any ground-truth data (meteorological or snowpack data). Satellite passive microwave remote sensing has been extensively used to improve SWE estimates, either by direct retrieval approach, or using satellite data assimilation in a radiative transfer model coupled with a snow model (LSS or TMSM). However, both approaches present large uncertainties due to the numerous variables affecting satellite microwave brightness temperature (Tb) (snow depth, vertical profiles of snow density, temperature and grain size, soil properties, vegetation) and their seasonal evolution owing to metamorphism, blowing snow, precipitation. In particular, passive microwave emission is strongly sensitive to snow grain size, and a proper assessment of this variable is required. In this presentation, we investigate the coupling of snow models (the Canadian LSS CLASS and the Swiss TMSM SNOWPACK) driven by reanalysis meteorological data to snow emission model (DMRT-ML and MEMLS). Results first confirm that the standalone snow models provide poor SWE predictions when compared to field measurements acquired during different field campaigns across Canada. The coupling of snow and microwave emission models and a simple assimilation procedure based on successive iterations to correct for the influence of snow grain size and density leads to a significantly improvement the SWE predictions without using any ground-truth data. This method was further validated using an independent dataset which also showed significant improvement . The proposed method is simpler to implement than Tb assimilation schemes such as EnKF, in particular for keeping the variable multilayering discretization in the snowpack evolution.

Author/Presenter: Alain Royer

ESA-CliC-EGU Conference on Earth Observation and Cryospheric Science, Frascati, Italy, November 13-16, 2012

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The atmosphere-ocean boundary layer in which sea ice resides includes many complex processes that require a more realistic treatment in GCMs, particularly as models move toward full earth system descriptions. The primary purpose of the workshop was to define and discuss such coupled processes...
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