Assessment and Validation of Snow Liquid Water Retrievals in the Antarctic Ice Sheet Using Categorical Triple Collocation

Abstract

Snow liquid water produced by melting can affect the surface mass and energy balance in the Antarctic Ice Sheet (AIS). It is essential for monitoring the occurrence of snow liquid water (OLW) within the snowpack. Spaceborne microwave sensors (i.e., scatterometer and radiometer) and climate models are primary tools for examining the OLW in the AIS. However, implementing the complementary nature of measurements and comparing their observations quantitatively are challenging owing to sparse snow wetness validation data. In this article, we use categorical triple collocation to rank the relative performance of OLW products. According to the first rankings, we construct an ensemble OLW product that is more consistent with the results detected by in situ station air temperature data than single data source products. Furthermore, we quantitatively estimate the proportion correct of wet snow (sensitivity) and the proportion correct of dry snow (specificity) of the measurements on the Antarctic Peninsula (AP). The scatterometer demonstrates high balanced accuracy (a binary-variable performance metric) on the AP (up to 0.899); however, this result does not signify that the scatterometer is the optimal observation in any period. The radiometer and climate model show high sensitivities in different melt stages but underestimate wet snow extent during certain periods. The quantitative estimation provides a new perspective for comparing various observations and detection methods.

Keywords

• Active and passive microwave
• categorical triple collocation
• regional atmospheric circulation model (RACMO2)
• snow liquid water