Description: Das Projekt "Creation of a Sentinel-1 Soil Water Index for data assimilation in a convection-permitting weather model (CRESSIDA)" wird vom Umweltbundesamt gefördert und von Technische Universität Wien, Department für Geodäsie und Geoinformation (E120) durchgeführt. 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.
Types:
SupportProgram
Origin: /Bund/UBA/UFORDAT
Tags: Wien ? Radar ? Satellitendaten ? Sensor ? Main ? Big Data ? Bodenwasser ? Fernerkundungsdaten ? Regenwasser ? Satellit ? Prognose ? Geoinformation ? Geodäsie ? Fallstudie ? Prognosemodell ? Assimilation ? Wettervorhersage ? Bodenfeuchte ? Verwitterung ? Datenmodell ? Bodenuntersuchung ? Daten ? Satellitenfernerkundung ? Extremwetter ? Benchmarking ? Informationsgewinnung ? Niederschlag ? Produkt ? Wetter ? Datenerhebung ? Datenassimilation ? SAR [Radar] ? Data Assimilation ? Sentinel-1 ? Soil Water Index ? Synthetic Aperture Radar (SAR) ? Wettervorhersagemodell ? weather forecast model ? Konvektion ?
License: cc-by-nc-nd/4.0
Language: Deutsch
Time ranges: 2015-06-01 - 2016-11-30
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