Many studies have developed snow process understanding by exploring the impact of snow model complexity on simulation performance. This paper revisits this topic using several recently developed land surface models, including the Simplified Simple Biosphere Model (SSiB); Noah; Variable Infiltration Capacity (VIC); Community Land Model, version 3 (CLM3); Snow Thermal Model (SNTHERM); and new field measurements from the Cold Land Processes Field Experiment (CLPX). Offline snow cover simulations using these five snow models with different physical complexity are performed for the Rabbit Ears Buffalo Pass (RB), Fraser Experimental Forest headquarters (FHQ), and Fraser Alpine ( FA) sites between 20 September 2002 and 1 October 2003. These models simulate the snow accumulation and snowpack ablation with varying skill when forced with the same meteorological observations, initial conditions, and similar soil and vegetation parameters.All five models capture the basic features of snow cover dynamics but show remarkable discrepancy in depicting snow accumulation and ablation, which could result from uncertain model physics and/or biased forcing. The simulated snow depth in SSiB during the snow accumulation period is consistent with the more complicated CLM3 and SNTHERM; however, early runoff is noted, owing to neglected water retention within the snowpack. Noah is consistent with SSiB in simulating snow accumulation and ablation at RB and FA, but at FHQ, Noah underestimates snow depth and snow water equivalent (SWE) as a result of a higher net shortwave radiation at the surface, resulting from the use of a small predefined maximum snow albedo. VIC and SNTHERM are in good agreement with each other, and they realistically reproduce snow density and net radiation. CLM3 is consistent with VIC and SNTHERM during snow accumulation, but it shows early snow disappearance at FHQ and FA. It is also noted that VIC, CLM3, and SNTHERM are unable to capture the observed runoff timing, even though the water storage and refreezing effects are included in their physics.A set of sensitivity experiments suggest that Noah's snow simulation is improved with a higher maximum albedo and that VIC exhibits little improvement with a larger fresh snow albedo. There are remarkable differences in the vegetation impact on snow simulation for each snow model. In the presence of forest cover, SSiB shows a substantial increase in snow depth and SWE, Noah and VIC show a slight change though VIC experiences a later onset of snowmelt, and CLM3 has a reduction in its snow depth. Finally, we observe that a refined precipitation dataset significantly improves snow simulation, emphasizing the importance of accurate meteorological forcing for land surface modeling.

This study examines the recently released National Centers for Environmental Prediction (NCEP) North American Regional Reanalysis (NARR)products over diverse climate regimes to determine the regional relationships between soil moisture and near-surface atmospheric variables. NARR assimilates observed precipitation, as well as near-surface observations of humidity and wind, while seeking a balance of the surface water and energy budgets with a modern land surface model. The results of this study indicate that for most basins (of approximate size of 0.5-1.0 x 106 km(2)) the NARR surface water budgets have relatively small residuals (about 0.2 mm day(-1)), and slightly larger residuals (about 0.4 mm day(-1)) for basins with complex terrain like those in the western United States.Given that the NARR is an assimilation system (especially one that assimilates observed precipitation), the NARR does not include feedbacks between soil moisture and precipitation. Nonetheless, as a diagnostic tool anchored to observations, the NARR does show that the extent of positive correlation between anomalies of soil moisture and anomalies of precipitation in a given region depends on that region's dryness. The existence of correlations among all variables is a necessary-but not sufficient-condition for land atmosphere feedbacks to exist, as a region with no correlations would not be expected to have feedbacks. Likewise, a high degree of persistence of soil moisture anomalies in a given basin does not by itself guarantee a positive correlation between anomalies of soil moisture and precipitation.Land surface-atmosphere relationships at monthly time scales are identified by examining the associations between soil moisture and surface and boundary layer variables. Low soil moisture is consistently associated with increased net shortwave radiation and increased outgoing longwave radiation through the effects of less cloud cover and lower atmospheric humidity. No systematic association is revealed between soil moisture and total net surface radiation, as this relation varies substantially between different basins. Low soil moisture is positively correlated with increased sensible heat and lower latent heat (reflected in a smaller evaporative fraction), decreased low-cloud cover, and higher lifting condensation level. The relation between soil moisture anomalies and precipitation anomalies is found to be quite variable between the basins, depending on whether availability of surface water exceeds the available energy for evaporation, or vice versa. Wetter basins, like the Columbia and Ohio, display weak or no correlations between soil moisture anomalies and precipitation anomalies. On the other hand, transitional regions between wet and dry regions, like the central Great Plains, manifest a positive correlation between soil moisture anomalies and precipitation anomalies. These results further the understanding of previous predictability studies (in coupled land-atmosphere prediction models), which indicates that in order for precipitation anomalies to emerge in response to soil moisture anomalies in a given region, it is necessary that the region's seasonal climate be neither too dry nor too wet.

The surface hydrology of the United States' western basins is investigated using the National Centers for Environmental Prediction operational Eta Model forecasts. During recent years the model has been subject to changes and upgrades that positively affected its performance. These effects on the surface hydrologic cycle are discussed by analyzing the period June 1995-May 2003. Prior to the model assessment, three gauge-based precipitation analyses that are potential sources of model validation are appraised. A fairly large disparity between the gridded precipitation analyses is found in the long-term area averages over the Columbia basin (similar to 23% difference) and over the Colorado basin (similar to 12% difference). These discrepancies are due to the type of analysis scheme employed and whether an orographic correction was applied.The basin-averaged Eta Model precipitation forecasts correlate well with the observations at monthly time scales and, after 1999, show a small bias. Over the Columbia basin, the model precipitation bias is typically positive. This bias is significantly smaller with respect to orographically corrected precipitation analyses, indicating that the model's large-scale precipitation processes respond reasonably well to orographic effects, though manifesting a higher bias during the cool season. Over the Colorado basin. the model precipitation bias is typically negative, and notably more so with respect to 1) the orographically corrected precipitation analyses and 2) the warm season, indicating shortfalls in the convection scheme over arid high mountains.The mean fields of the hydrological variables in the Eta Model are in qualitative agreement with those from the Variable Infiltration Capacity (VIC) macroscale hydrologic model at regional-to-large scales. As expected, the largest differences are found near mountains and the western coastline. While the mean fields of precipitation, evaporation, runoff, and normalized soil moisture are in general agreement, important differences arise in their mean annual cycle over the two basins: snowmelt in the Eta Model precedes that of VIC by 2 months, and this phase shift is also reflected in the other variables. In the last 3-4 yr of the study period, notable improvements are evident in the quality of the model's precipitation forecast and in the reduction of the residual term of the surface water balance, suggesting that at least similar (or better) quality will be found in studies based on NCEP's recently completed Eta Model-based North American regional reanalysis.

This article discusses the water and surface energy budgets over the Mississippi River basin and subbasins using NCEP's Eta model forecasts. It also discusses the relation between surface states (soil moisture) and other variables that affect the surface energy balance, potentially interacting with precipitation processes. The Eta model is NCEP's operational mesoscale model and therefore has been subject to changes and upgrades over the period of this evaluation. While the atmospheric water cycle is analyzed here using a 7‐year long (June 1995 to May 2002) data set, the research focusing on surface processes is based on a 4‐year period (June 1998 to May 2002) after substantial upgrades to the land surface component were performed. On the 7‐year average the Eta model 12–36 h forecast precipitation averaged over the Mississippi basin differs from the observed precipitation by 2%, while the estimate of evaporation computed as a residual of the water balance equation differs by 5% from the evaporation estimate resulting from a data set of land surface fluxes prepared with the macroscale hydrologic variable infiltration model (VIC). However, the difference between the model parameterized evaporation and VIC's is about 17% due to excessive bare soil evaporation in the Eta model. Notably, the long‐term average of moisture flux convergence also estimated from the 12–36 h forecasts is 0.54 mm day−1 over the Mississippi basin, while streamflow observations at Vicksburg average 0.50 mm day−1. This agreement within 10% is a strict test of the quality of the hydrologic cycle estimates; therefore these are promising results for estimates of the water cycle from regional analysis or future regional reanalysis. Subbasins of the Mississippi have diverse land surface‐atmosphere interactions at monthly timescales. In the western half of the Mississippi basin, feedbacks can be described as follows: increased soil moisture is associated with a slight increase of net radiation at the surface; latent heat also increases with soil moisture while sensible heat decreases, resulting in an almost linear increase of the evaporative fraction. Increased soil moisture is also associated with a lower lifting condensation level and an increase of observed precipitation (though not statistically significant). The overall results support the concept of a positive feedback in which increased soil moisture affects surface fluxes in such a manner that increased precipitation results. However, toward the east (e.g., the Ohio basin), there are no well‐defined land surface‐atmosphere interactions, suggesting that other effects, like the advection of moisture, may be more relevant for precipitation processes.

[1] This article discusses the water and surface energy budgets over the Mississippi River basin and subbasins using NCEP's Eta model forecasts. It also discusses the relation between surface states (soil moisture) and other variables that affect the surface energy balance, potentially interacting with precipitation processes. The Eta model is NCEP's operational mesoscale model and therefore has been subject to changes and upgrades over the period of this evaluation. While the atmospheric water cycle is analyzed here using a 7-year long (June 1995 to May 2002) data set, the research focusing on surface processes is based on a 4-year period (June 1998 to May 2002) after substantial upgrades to the land surface component were performed. On the 7-year average the Eta model 12-36 h forecast precipitation averaged over the Mississippi basin differs from the observed precipitation by 2%, while the estimate of evaporation computed as a residual of the water balance equation differs by 5% from the evaporation estimate resulting from a data set of land surface fluxes prepared with the macroscale hydrologic variable infiltration model (VIC). However, the difference between the model parameterized evaporation and VIC's is about 17% due to excessive bare soil evaporation in the Eta model. Notably, the long-term average of moisture flux convergence also estimated from the 12-36 h forecasts is 0.54 mm day -1 over the Mississippi basin, while streamflow observations at Vicksburg average 0.50 mm day -1 . This agreement within 10% is a strict test of the quality of the hydrologic cycle estimates; therefore these are promising results for estimates of the water cycle from regional analysis or future regional reanalysis. Subbasins of the Mississippi have diverse land surface-atmosphere interactions at monthly timescales. In the western half of the Mississippi basin, feedbacks can be described as follows: increased soil moisture is associated with a slight increase of net radiation at the surface; latent heat also increases with soil moisture while sensible heat decreases, resulting in an almost linear increase of the evaporative fraction. Increased soil moisture is also associated with a lower lifting condensation level and an increase of observed precipitation (though not statistically significant). The overall results support the concept of a positive feedback in which increased soil moisture affects surface fluxes in such a manner that increased precipitation results. However, toward the east (e.g., the Ohio basin), there are no well-defined land surface-atmosphere interactions, suggesting that other effects, like the advection of moisture, may be more relevant for precipitation processes.