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.
Highlights
The Soil Moisture Active Passive (SMAP) mission, an L-band satellite launched by the National Aeronautics and Space Administration (NASA) in 2015, is intended to produce global observations of soil moisture and soil freeze-thaw state in order to improve modeling of surface water, energy, and carbon fluxes and improve weather, climate, and agricultural monitoring [1]
We found that the SMAP Level 2 Soil Moisture (L2SM) bias and unbiased root-mean-square-error (ubRMSE) vary seasonally in the South Fork core validation sites (CVS)
We hypothesized that a seasonal analysis of SMAP L2SM retrievals, rather than the annual analysis performed by prior investigations, is more appropriate for the South Fork Core Validation Site in the U.S Corn Belt as there are two distinct land cover periods: annual crops in the summer and bare soil in the spring and fall
Summary
The Soil Moisture Active Passive (SMAP) mission, an L-band satellite launched by the National Aeronautics and Space Administration (NASA) in 2015, is intended to produce global observations of soil moisture and soil freeze-thaw state in order to improve modeling of surface water, energy, and carbon fluxes and improve weather, climate, and agricultural monitoring [1]. We perform a monthly evaluation of SMAP L2SM in the South Fork over a four-year period and examine croplands parameterizations that could potentially cause observed errors This includes an investigation into the changes introduced by the most recent data version that significantly reduced dry biases in soil moisture retrievals [10]
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