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Academic PhD or PostDoc in Satellite Data Assimilation

20.02.2019 - University of Hohenheim, Stuttgart, Germany

A full-time PhD / Postdoctoral position in satellite data assimilation into coupled land-atmosphere models is available at the Data Assimilation in the Earth System group, Institute of Physics and Meteorology (IPM), University of Hohenheim, Stuttgart (Germany). We are open for applicants that have already received a doctoral degree or candidates that wish to gain a doctoral degree with this position. A teaching task of 4 h/week (for PhD student) or 6 h/week (for Postdoc) is assigned to this position. The three year fixed-term contract (with possibility of extension) is paid according to TV-L E13 (100%). The earliest start date of the position is 01.05.2019. (Application deadline 15 March 2019)

Numerical models have contributed significantly to improve our understanding of the dynamics of the global water cycle. However, these models indicate limitations due to the uncertainty of input data, boundary conditions, parameterisation, and imperfect model structure. Earth Observation (EO) satellite missions provide invaluable estimates of atmospheric and hydrologic variables, which often cover the entire globe. From these EO missions, the Gravity Recovery And Climate Experiment (GRACE) and its follow-on mission (GRACE-FO) measurements can be used to estimate Terrestrial Water Storage Changes (TWSC), i.e. a vertical summation of surface and sub-surface water storage changes. In addition, various satellite missions provide multi-decadal Surface Soil Moisture (SSM) estimates, as well as Land Surface Temperature (LST). These missions include SMOS, SMAP, MODIS, and Sentinel, which typically measure electromagnetic radiance emitted by the Earth surface or sample waveforms returned from radar pulses. However, the relationship between the measured radiance or waveforms and the quantities of interest might be incredibly complex. Therefore, a strategic step for the Earth sciences involves merging data and models via data assimilation and model parameter calibration techniques that is the research focus of the Data Assimilation in the Earth System group.