Comparing Operational NLDAS-2 and Experimental NLDAS-3 Soil Moisture with Observational Soil Moisture Data from In-Situ Networks and SMAP Remote Sensing

Soil moisture is a key state variable of the terrestrial water cycle, important for water resources management, agricultural productivity, drought monitoring, and numerical weather and seasonal climate prediction. This study will present a unique evaluation of the new North American Land Data Assimilation System version 3 (NLDAS-3) and NLDAS-2 soil moisture against both in situ (ISMN and NASMD) and remotely sensed observations. Modeled soil moisture has not been comprehensively evaluated yet due to the scarcity and representativeness of existing observations (e.g., spatial scale mismatch). The proposed methodology follows from research by Dirmeyer et al. (2016) and Nicolai-Shaw et al. (2015) (among others) where in situ stations are screened for spatial representativeness before comparison and vertically interpolated to the model’s soil profile. Spatial representativeness is analyzed using a simple parameter-free approach to quantify the area surrounding a station for which its temporal dynamics is representative. In situ stations capture deeper soil moisture variability while surface soil moisture evaluation will use retrievals from the NASA SMAP satellite (~5 cm). Comparison metrics used are monthly soil moisture variances and short-term anomalies (35-days) to allow fair comparison between models and observations that do not follow the same climatology. The objectives of this study are to: (i) highlight discrepancies and agreements between LSM outputs and observations, (ii) determine if models used in experimental NLDAS-3 development perform more skillfully than models used in operational NLDAS-2, and (iii) highlight in situ stations and networks most suitable for grid-scale validation.