christophreimer / ESA_LPS2016

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An enhanced soil moisture product from the ERS scatterometers

Christoph Reimer, Isabella Pfeil and Wolfgang Wagner

ESA Living Planet Symposium 2016 Prague

Abstract

Active microwave remote sensing has a long heritage in the European earth observation programme, initiated with the launch of the European Remote Sensing satellite ERS-1 in 1991. ERS-1 was equipped with a sophisticated C-band scatterometer (ESCAT) providing insights into ocean and land surface dynamics of the Earth. Because of the great success of the ERS-1 mission, the follow-up mission ERS-2 was launched in 1995 carrying an identical constructed C-band scatterometer. After 9 years of excellent performance, ERS-1 was decommissioned in the year 2000, followed by ERS-2 in 2011 after almost 16 years in space. Global C-band scatterometer observations from ESCAT on-board of ERS-1 and ERS-2 comprise a unique data archive covering a period of about 20 years. In the framework of the ESA funded project SCIRoCCo (Scatterometer Instrument Competence Centre), this data archive was reconsidered with the objective to generate the most complete and consistent ESCAT dataset. TU Wien is one of the project consortium members regarded as the reference laboratory for soil moisture (SM) retrieval from scatterometers. Accordingly, TU Wien undertake the generation of an up-to-date ESCAT SM dataset based on re-processed Level 1 backscatter data. In this study the major project achievements with respect to the production of the most complete ESCAT SM data archive are presented. First, the high radiometric quality of the re-processed Level 1 backscatter data is demonstrated with reference to well defined calibration targets. Furthermore, enhancements of the TU Wien soil moisture algorithm are discussed covering an improved SM error characterisation and improvements in the model parameter estimation. Finally, results of a comprehensive validation of the obtained SM product in comparison to in-situ measurements and soil moisture estimates from land surface models are presented.

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