Seasonal Evaluation of SMAP Soil Moisture in the U.S. Corn Belt

Abstract

NASA’s Soil Moisture Active Passive (SMAP) Level 2 soil moisture products are not meeting mission goals in the U.S. Corn Belt according to our seasonal evaluation conducted at a SMAP Core Validation Site in central Iowa. The single-channel algorithm (SCA) soil moisture products are too dry in early spring and late fall before and after crops are present, and too noisy in late spring and early summer when crops begin to grow. We investigated likely contributing factors. The climatology of vegetation’s effect on soil moisture retrieval in the SCA can differ by more than 14 days from what is retrieved by SMAP’s dual-channel algorithm (DCA). Soil and vegetation temperatures, assumed to be equal by all retrieval algorithms, are not: vegetation is about 2 K colder at 6:00 a.m. and about 2 K warmer at 6:00 p.m.. The effective temperature in version 2 products is too warm as compared to in situ soil temperatures. We propose a new effective temperature model that is consistent with observations, decreases the unbiased root-mean-square-error (ubRMSE) overall, and increases the coefficient of determination (R2) of the DCA in every month. However, some monthly dry biases increase to more than 0.10 m3 m−3. The single-scattering albedo, ω , has a significant impact on soil moisture retrieval. While the DCA has its lowest ubRMSE and highest R2 when ω is non-zero, the SCA have their lowest ubRMSE and highest R2 when ω = 0 , and the dry bias of all algorithms increases as ω increases. Errors in soil texture are not significant, but soil surface roughness should not be static and have a higher overall value. Our findings make it clear that a new retrieval algorithm that can account for changing soil roughness and vegetation conditions is needed.

Keywords

• smap
• u.s. corn belt
• soil moisture
• effective surface temperature