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<p>Soil moisture (SM) datasets retrieved from the advanced&#160;scatterometer&#160;(ASCAT) sensor are well established and widely used for various hydro-meteorological, agricultural,&#160;and&#160;climate monitoring applications. Besides SM, ASCAT is sensitive to vegetation structure and vegetation water content, enabling the retrieval of vegetation optical depth (VOD;&#160;1). The challenge in the retrieval of SM and vegetation products&#160;from ASCAT observations&#160;is to separate the two effects. As described by Wagner et al. (2), SM and vegetation affect the&#160;relation between&#160;backscatter&#160;and incidence angle differently.&#160;&#160;At high incidence angles, the response from bare soil and thus the sensitivity to SM conditions is significantly weaker than at low incidence angles,&#160;leading to decreasing backscatter with increasing incidence angle.&#160;The presence of vegetation on the other hand&#160;decreases the backscatter dependence on&#160;the incidence angle. The dependence of backscatter on the incidence angle&#160;can be&#160;described by a second-order Taylor polynomial based on a slope and a curvature coefficient.&#160;It was found empirically that SM conditions have no significant effect on the steepness of the slope, and that therefore,&#160;SM and&#160;vegetation effects can be&#160;separated&#160;using&#160;the&#160;slope&#160;(2).&#160;&#160;This is a major assumption in the&#160;TU&#160;Wien&#160;soil moisture retrieval algorithm used in several operational soil moisture products. However,&#160;recent&#160;findings by&#160;Quast et al. (3)&#160;using&#160;a first-order radiative transfer model for the inversion of soil and vegetation parameters from&#160;scatterometer&#160;observations&#160;indicate that SM may influence the slope, as the SM-induced backscatter increase is more pronounced at low incidence angles.&#160;</p>
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<p>The aim of this analysis is to&#160;revisit&#160;the assumption that&#160;SM&#160;does not affect the&#160;slope of the backscatter incidence angle relations by&#160;investigating&#160;if&#160;short-term variability,&#160;observed&#160;in ASCAT slope&#160;timeseries&#160;on top of the seasonal vegetation cycle,&#160;is caused by SM.&#160;We therefore compare timeseries and anomalies of&#160;the&#160;ASCAT slope&#160;to&#160;air temperature,&#160;rainfall&#160;and SM&#160;from the ERA5-Land dataset. We carry out the analysis in a&#160;humid continental&#160;climate (Austria) and a&#160;Mediterranean&#160;climate&#160;study region (Portugal).&#160;First results show&#160;significant negative&#160;correlations between slope and SM anomalies. However,&#160;correlations between temperature and slope anomalies are&#160;of a similar magnitude,&#160;albeit&#160;positive,&#160;which may reflect temperature-induced vegetation dynamics. The fact that temperature and SM are&#160;strongly correlated&#160;with each&#160;other&#160;complicates the&#160;interpretation of the results.&#160;Thus, our second approach is to&#160;investigate&#160;daily slope values and their change between dry and wet days.&#160;The results of this study shall&#160;help to quantify&#160;the&#160;uncertainties&#160;in ASCAT SM products caused by&#160;the potentially&#160;inadequate&#160;assumption&#160;of a SM-independent&#160;slope.&#160;</p>
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<p>(1) Vreugdenhil, Mariette, et al. "Analyzing the vegetation parameterization in the TU-Wien ASCAT soil moisture retrieval." IEEE Transactions on Geoscience and Remote Sensing 54.6 (2016): 3513-3531.</p>
<p><span>(2) Wagner, Wolfgang, et al. "Monitoring soil moisture over the Canadian Prairies with the ERS scatterometer." IEEE Transactions on Geoscience and Remote Sensing 37.1 (1999): 206-216.&#160;</span></p>
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<p>(3) Quast, Raphael, et al. "A Generic First-Order Radiative Transfer Modelling Approach for the Inversion of Soil and Vegetation Parameters from Scatterometer Observations." Remote Sensing 11.3 (2019): 285.</p>
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Technical Note: A new discrete ordinate first-order rotational Raman scattering radiative transfer model – implementation and first results
