Creation of a Sentinel-1 Soil Water Index for data assimilation in a convection-permitting weather model (CRESSIDA)
2015-06-01 – 2017-03-31
Sentinel-1 satellites with their Synthetic Aperture Radar sensors will make it possible to
measure soil moisture in hitherto unreached spatial resolution an requires new approaches
in efficient dealing with Big Data. This new data source will be used to create soil moisture
products like the Soil Water Index (SWI), whereas the innovative combination with already
established satellite sensors (e.g. ASCAT, ERS, SMOS) will result in a product being the
new benchmark with regard to spatio-temporal resolution and accuracy.
Due to the high resolution of the SWI product based on Sentinel-1 data, it will be feasibly for
the first time to meaningful run the weather forecast model AROME with explicit convection
in combination with soil moisture data assimilation. The expected positive impact on
precipitation forecast quality will be verified within several case studies.
At the end of the project, two main outcomes are expected: i) a high-quality soil moisture
data set and an ii) improved severe weather forecast.