Intercomparison of snow water equivalent products in the Sierra Nevada California using airborne snow observatory data and ground observations

Whereas many independent methods are used to estimate snow water equivalent (SWE) and its spatial distribution seasonal variability, a need exists for systematic characterization of inter-model differences at annual, seasonal, regional scales necessary quantify the associated uncertainty in these datasets. This study conducts multi-scale validation comparison, based on Airborne Snow Observatory data, five state-of-the-art SWE datasets Sierra Nevada, California, including three from retrospective models: an INiTial REConstruction model (REC-INT), improved ParBal energy balance (REC-ParBal), Nevada with Data Assimilation (REC-DA), two operational U.S. National Weather Service, System (SNODAS) Water Model (NWM-SWE). The results show that REC-DA REC-ParBal provide most accurate estimates snowmelt season, both small positive biases. provides ( R 2 = 0.87, MAE 66 mm, PBIAS 8.3%) pixel scale, while has least basin-wide 0.79, 73 4.1%) season. Moreover, underestimates peak by −5.8%, overestimates it 7.5%, when compared measured pillow stations across Nevada. products—SNODAS NWM-SWE—are less accurate. Furthermore, comparison reveals certain amount disagreement storage time space between advances our understanding uncertainties critical insights support future applications data products therefore broad implications resources management hydrological process studies.