Evaluation and diagnosis of the National Water Model snow simulations

Snow accumulation and its melt dominate water resources in mountainous areas, with regions such as the western United States deriving more than 75% of the total freshwater available annually from snowmelt. Rain-on-snow floods, in some cases amplified by frozen soils, have been responsible for some of the largest recorded floods in the West, as well as the North Central States and the Northeast. Despite their importance snowpacks remain poorly quantified (especially, but not only, in topographically complex regions), leaving hydrological models such as the National Water Model (NWM) poorly constrained with significant uncertainty in both their physical and statistical parameterizations. Remote sensing can alleviate some of these limitations and recently-produced datasets from optical satellite sensors have provided long-term and high-resolution maps of snow water equivalent (SWE). In this project, we will extend a satellite-derived SWE reanalysis (from Landsat, MODIS, and VIIRS) over the Continental United States (CONUS) and assess the representation of SWE in the NWM. Apart from directly evaluating the output of the NWM in terms of SWE, we will diagnose model errors and characterize them both statistically as well as in terms of the model parameterizations. The results from the diagnostic and sensitivity analyses will be used to derive error models and improved parameterizations for NWM that will be tested and compared with the baseline NWM version.