Towards Including Dynamic Vegetation Parameters in the EUMETSAT H SAF ASCAT Soil Moisture Products

Abstract

The TUWien Soil Moisture Retrieval (TUW SMR) approach is used to produce several operational soil moisture products from the Advanced Scatterometer (ASCAT) on the MetOP series of satellites as part of the EUMETSAT Satellite Application Facility on Support to Operational Hydrology and Water Management (H SAF). The incidence angle dependence of backscatter is described by a second-order Taylor polynomial, the coefficients of which are used to normalize ASCAT observations to the reference incidence angle of 40∘ and for correcting vegetation effects. Recently, a kernel smoother was developed to estimate the coefficients dynamically, in order to account for interannual variability. In this study, we used the kernel smoother for estimating these coefficients, where we distinguished for the first time between their two uses, meaning that we used a short and fixed window width for the backscatter normalisation while we tested different window widths for optimizing the vegetation correction. In particular, we investigated the impact of using the dynamic vegetation parameters on soil moisture retrieval. We compared soil moisture retrievals based on the dynamic vegetation parameters to those estimated using the current operational approach by examining their agreement, in terms of the Pearson correlation coefficient, unbiased RMSE and bias with respect to in situ soil moisture. Data from the United States Climate Research Network were used to study the influence of climate class and land cover type on performance. The sensitivity to the kernel smoother half-width was also investigated. Results show that estimating the vegetation parameters with the kernel smoother can yield an improvement when there is interannual variability in vegetation due to a trend or a change in the amplitude or timing of the seasonal cycle. However, using the kernel smoother introduces high-frequency variability in the dynamic vegetation parameters, particularly for shorter kernel half-widths.

The effects of satellite soil moisture data on the parametrization of topsoil and root zone soil moisture in a conceptual hydrological model

“…The results in this paper are based on an experimental SWI data product, which mainly benefits from a new vegetation parameterization of the ASCAT topsoil moisture retrieval algorithm (Steele-Dunne et al, 2021). It includes an improved spatial representation due to the application of a new directional resampling method based on Sentinel-1 Synthetic Aperture Radar (SAR) data (Tong et al, 2021).…”

Climatological Drought Monitoring in Switzerland Using EUMETSAT SAF Satellite Data

“…This effect helps to evaluate the impacts of drought on natural vegetation [4,20]. Studies show that information on vegetation, especially when coupled to other drought indicators, provides a powerful tool for monitoring drought events [22][23][24][25][26][27]. Finally, evapotranspiration is also an important variable for drought monitoring [28].…”