An intercomparison of soil moisture fields in the North American land data assimilation system (NLDAS)

The multiple-agency/university North American Land Data Assimilation System (NLDAS) project is designed to provide enhanced soil and temperature initial conditions for numerical weather/climate prediction models. Currently, four land surface models (LSMs) are running in NLDAS both in retrospective mode and in real-time mode. All LSMs are driven by the same meteorologic forcing data and are initiated at the same time with the same relative soil wetness. This study intercompares these NLDAS soil moisture fields with each other and with available observations. The total water storage and the storage variability range are the foci of the study. The mean statistical properties and the spatial variation of these soil moisture fields along with their temporal change are investigated. Model soil moisture fields are compared to soil moisture observations in Illinois. The storage variability range in Arkansas-Red River basin is validated against a water balance diagnostic analysis using historical precipitation and streamflow data. There is better agreement between observed and simulated ranges of water storage variability than between observed and simulated amounts of total water storage. Significant differences are found between NLDAS-simulated soil moisture fields from the different models. Total water storage is found to be highly model dependent. There is better agreement between models in the water total water storage range than in the model values of total water storage. Total water storage ranges agree best in humid areas where variation in water storage is strongly driven by variation in precipitation. In very dry areas, agreement between simulated water storage ranges is weak because model differences have as much influence on water storage range as climate variability in these areas. Finally, the spin-up properties of the models and relationships between water storage properties and climate are investigated. The results of this study should provide important insights into the similarities and differences of the four LSMs in NLDAS. Differences in NLDAS soil moisture fields pose challenges to land surface modelers who intend to use soil moisture field from one model to initialize another model.