[1] This article presents first results of deriving relative surface soil moisture from the METOP-A Advanced Scatterometer. Retrieval is based on a change detection approach which has originally been developed for the Active Microwave Instrument flown onboard the European satellites ERS-1 and ERS-2. Using model parameters derived from eight years of ERS scatterometer data, first global soil moisture maps have been produced from ASCAT data. The ASCAT data were distributed by EUMETSAT for validation purposes during the ASCAT product commissioning activities. Several recent cases of drought and excessive rainfall are clearly visible in the soil moisture data. The results confirm that seamless soil moisture time series can be expected from the series of two ERS and three METOP scatterometers, providing global coverage on decadal time scales (from 1991 to about 2021). Thereby, operational, nearreal-time ASCAT soil moisture products will become available for weather prediction and hydrometeorological applications.
The Advanced Scatterometer (ASCAT) onboard the Metop-A satellite became operational shortly after launch in 2006, and an absolute calibration using three transponders was achieved in November 2008. In this paper, we describe how the CMOD5.n ocean backscatter geophysical model function (GMF), which was derived using data from previous scatterometers onboard the European Remote Sensing 1 and 2 satellites (ERS-1 and ERS-2), was used to derive backscatter bias correction factors. The purpose is to remove the bias between ASCAT backscatter data and the CMOD5.n GMF output which allows these data to be used in place of ERS data in existing wind processing algorithms. The ASCAT Wind Data Processor, developed at the Royal Netherlands Meteorological Institute (KNMI), applies the bias correction factors to ASCAT data and uses CMOD5.n to retrieve wind vectors in order to produce an operational wind product. This resulted in a stable and high-quality ASCAT wind product since February 2007. We validate this product by comparing it to the European Centre for Medium-range Weather Forecasts (ECMWF) winds and buoy measurements. The bias correction factors indicate that ASCAT data and the GMF differ by roughly 0.3 dB below 55 • and up to 0.8 dB above 55 •. A possible explanation lies in CMOD5.n which has been poorly validated in this incidence angle regime. Validation of ASCAT data using the ocean calibration method confirms this result and also indicates that bias-corrected data are everywhere within 0.3 dB of CMOD5.n. The wind product validation shows an rms error of 1.3 m • s −1 in wind speed and 16 • in wind direction when compared to ECMWF winds. This is better than the results achieved using ERS scatterometer data. Against buoy winds, we find an rms error wind component error of approximately 1.8 m • s −1. These results show that the ASCAT wind product is of high quality and satisfies its wind component accuracy requirement of 2 m • s −1 .
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