Assimilation of passive microwave observations into atmospheric models

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An accurate knowledge of soil moisture is essential for a realistic numerical simulation of the water and energy budget over land surfaces. Due to significant deficiencies in model parameterizations, input data and the absence of a global soil moisture observation network, indirect measures of soil moisture are currently used to adjust soil moisture towards reality in numerical weather prediction models. Since the thermal emission of the land surface in the low-frequency microwave range strongly depends on soil moisture passive microwave observations from satellites have the potential of significantly improving model soil moisture. This study aims to further develop the new European Land Data Assimilation System¿s (ELDAS) soil moisture analysis which is able to assimilate satellite observations of low-frequency passive microwave brightness temperatures into numerical weather prediction models and to investigate its effects on the quality of mid-latitude regional weather forecasts comprising a complete annual cycle. A significant step towards a new operational assimilation system leading to an improved numerical simulation of the water and energy budget over land surfaces is expected.