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Improvement of the soil-atmosphere interactions and subsequent heavy precipitation modelling by enhanced initialization using remotely sensed 1 km soil moisture information

Helgert, Sebastian 1; Khodayar, Samiro 1
1 Institut für Meteorologie und Klimaforschung Troposphärenforschung (IMKTRO), Karlsruher Institut für Technologie (KIT)

Abstract (englisch):

This study assesses the impact of an improved soil moisture (SM) initialization using direct insertion methodology for convection-resolving modelling of heavy precipitation events (HPEs). State-of-the-art 1 km SM data from the Soil Moisture and Ocean Salinity (SMOS) mission, SMOS-BEC L4 version 3 are used for this purpose. A strategy is developed to prepare the SMOS-L4 surface soil moisture (SSM) product for the COnsortium for Small-scale MOdelling (COSMO) model initialization by applying a cumulative density function (CDF)-matching bias-correction and the exponential filter method to calculate corresponding SM profiles (L4-Expo). The processed satellite-derived product is validated with 38 observing sites from three in-situ SM networks REMEDHUS (19), SMOSMANIA (11) and VAS (8). All networks measure at a soil depth of 5 cm, only at the SMOSMANIA network additional measurements at 10, 20 and 30 cm are available. Four HPEs are selected to evaluate the impact of the high-resolution realistic initialization. The results show a high agreement index (AI = 0.91) and a low root-mean-square deviation (0.03 m3/m3) of the high-resolution, bias-corrected SMOS-L4 SSM product compared to in-situ observations. ... mehr

DOI: 10.1016/j.rse.2020.111812
Zitationen: 8
Web of Science
Zitationen: 8
Zitationen: 9
Zugehörige Institution(en) am KIT Institut für Meteorologie und Klimaforschung Troposphärenforschung (IMKTRO)
KIT-Zentrum Klima und Umwelt (ZKU)
Publikationstyp Zeitschriftenaufsatz
Publikationsmonat/-jahr 09.2020
Sprache Englisch
Identifikator ISSN: 0034-4257
KITopen-ID: 1000119698
HGF-Programm 12.01.02 (POF III, LK 01) Proc.res.f.multisc.predictab.of weather
Erschienen in Remote sensing of environment
Verlag Elsevier
Band 246
Seiten Article no: 111812
Nachgewiesen in Scopus
Web of Science
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