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To prepare for the next-generation North American Land Data Assimilation System (NLDAS), three advanced land surface models [LSMs; i.e., Community Land Model, version 4.0 (CLM4.0); Noah LSM with multiphysics options (Noah-MP); and Catchment LSM-Fortuna 2.5 (CLSM-F2.5)] were run for the 1979-2014 period within the NLDAS-based framework. Unlike the LSMs currently executing in the operational NLDAS, these three advanced LSMs each include a groundwater component. In this study, the model simulations of monthly terrestrial water storage anomaly (TWSA) and its individual water storage components are evaluated against satellite-based and in situ observations, as well as against reference reanalysis products, at basinwide and statewide scales. The quality of these TWSA simulations will contribute to determining the suitability of these models for the next phase of the NLDAS. Overall, it is found that all three models are able to reasonably capture the monthly and interannual variability and magnitudes of TWSA. However, the relative contributions of the individual water storage components to TWSA are very dependent on the model and basin. A major contributor to the TWSA is the anomaly of total column soil moisture content for CLM4.0 and Noah-MP, while the groundwater storage anomaly is the major contributor for CLSM-F2.5. Other water storage components such as the anomaly of snow water equivalent also play a role in all three models. For each individual water storage component, the models are able to capture broad features such as monthly and interannual variability. However, there are large intermodel differences and quantitative uncertainties, which are motivating follow-on investigations in the NLDAS Science Testbed developed by the NASA and NCEP NLDAS teams.

The energy components of sixteen Soil-Vegetation Atmospheric Transfer (SVAT) schemes were analyzed and intercompared using 10 years of surface meteorological and radiative forcing data from the Red-Arkansas River basin in the Southern Great Plains of the United States. Comparisons of simulated surface energy fluxes among models showed that the net radiation and surface temperature generally had the best agreement among the schemes. On an average (annual and monthly) basis, the estimated latent heat fluxes agreed (to within approximate estimation errors) with the latent heat fluxes derived from a radiosonde-based atmospheric budget method for slightly more than half of the schemes. The sensible heat fluxes had larger differences among the schemes than did the latent heat fluxes, and the model-simulated ground heat fluxes had large variations among the schemes. The spatial patterns of the model-computed net radiation and surface temperature were generally similar among the schemes, and appear reasonable and consistent with observations of related variables, such as surface air temperature. The spatial mean patterns of latent and sensible heat fluxes were less similar than for net radiation, and the spatial patterns of the ground heat flux vary greatly among the 16 schemes. Generally, there is less similarity among the models in the temporal (interannual) variability of surface fluxes and temperature than there is in the mean fields, even for schemes with similar mean fields.

The water-balance components of 16 Soil-Vegetation Atmospheric Transfer (SVAT) schemes were evaluated by comparing predicted and observed streamflow, predicted evapotranspiration and evapotranspiration inferred from an atmospheric moisture budget analysis, and soil moisture storage changes for a seven-year period (1980-1986) using data from the Red-Arkansas River basins of the Southern Great Plains of the USA. The evaluations support the following suggestions: (a) The mean annual runoff of all models follows, at least generally, the strong climatic East-West gradient of precipitation, although most models predict too much runoff in the dry part of the basin. (b) The mean monthly storage change tends to be underestimated, even though all models capture reasonably well the seasonality of the evapotranspiration. (c) The wide range of conceptualizations used for generation of surface and subsurface runoff strongly affect runoff generation on seasonal, and shorter, time scales. Model responses to summer precipitation ranged from almost no summer runoff (one model) to the (more common) situation of persistent overprediction of summer runoff, especially in the driest part of the basin. (d) All models tended to underpredict evapotranspiration in summer and overpredict in winter. (e) Model-derived mean seasonal cycles of changes in soil moisture storage are qualitatively similar to those inferred from observations, but most models do not predict the decrease in April soil moisture storage and the increase in October that is inferred from observations.