LAUSR

The validation of the soil moisture retrievals from the recently launched National Aeronautics and Space Administration (NASA) Soil Moisture Active/Passive (SMAP) satellite is important prior to their full public release. Uncertainty in attempts to characterize footprint-scale surface-layer soil moisture using point-scale ground observations has generally limited past validation of remotely sensed soil moisture products to densely instrumented sites covering an area approximating the satellite ground footprint. However, by leveraging independent soil moisture information obtained from land surface modeling and/or alternative remote sensing products, triple collocation (TC) techniques offer a strategy for characterizing upscaling errors in sparser ground measurements and removing the impact of such error on the evaluation of remotely sensed soil moisture products. Here, we propose and validate a TC-based strategy designed to utilize existing sparse soil moisture networks (typically with a single sampling point per satellite footprint) to obtain an unbiased correlation validation metric for satellite surface soil moisture retrieval products. Application of this TC strategy at five SMAP core validation sites suggests that unbiased estimates of correlation between the satellite product and the true footprint average can be obtained—even in cases where ground observations provide only one single reference point within the footprint. An example of preliminary validation results from the application of this TC strategy to the SMAP Level 2 Soil Moisture Passive (beta release version) product is presented.