Abstract
The TU Wien 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.
Highlights
Over the past decade, global-scale soil moisture data products derived from active and passive microwave measurements acquired by polar orbiting Earth observation satellites have become widely available [1]
Results presented here indicate that accounting for interannual variability in the effect of vegetation on sensitivity of Advanced Scatterometer (ASCAT) normalized backscatter to soil moisture could benefit soil moisture retrievals
The proposed approach using a kernel smoother with a kernel half-width of λ = 21 days to estimate dynamic vegetation parameters was undermined by its sensitivity to short-term variations in the relationship between slope and incidence angle
Summary
Global-scale soil moisture data products derived from active and passive microwave measurements acquired by polar orbiting Earth observation satellites have become widely available [1]. These include data products derived from the Soil. The spatial resolution of these microwave soil moisture data products is typically rather coarse, limiting their use in applications such as precision agriculture, landslide prediction or erosion monitoring. The longest standing operational soil moisture data service rests on ASCAT, an active microwave sensor flown on board a series of three Metop satellites operated by the European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT).
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