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- W4289637482 abstract "Operational water-resource forecasters, such as the Colorado Basin River Forecast Center (CBRFC) in the Western United States rely on historical records to calibrate the temperature-index models currently used for snowmelt runoff predictions. This data dependence is increasingly challenged, with global and regional climatological factors changing the seasonal snowpack in mountain watersheds. To evaluate and improve the CBRFC modeling options, this work ran the physically based snow energy balance iSnobal model, forced with outputs from the High-Resolution Rapid Refresh (HRRR) numerical weather model across four years in a subset region. Compared to in-situ, remotely sensed, and the current operational CBRFC model, the iSnobal-HRRR coupling showed well-reconstructed snow depths until peak accumulation (Mean differences between -0.20 and +0.28 m). Once snowmelt set in, iSnobal-HRRR showed that simulated snowmelt was slower relative to observations, depleting snow on average up to 34 days later. The melting period is a critical component for water forecasting. Based on the results, there is a need for revised energy balance calculations in iSnobal, which is a recommended future improvement to the model. Nevertheless, the presented performance and architecture make iSnobal-HRRR a promising combination for the CBRFC production needs, where there is a demonstrated change to the seasonal snow in the mountain ranges around the Colorado River Basin. Long term goal is to introduce the iSnobal-HRRR coupling in day-to-day CBRFC operations, and this work created the foundation to expand and evaluate larger domains." @default.
- W4289637482 created "2022-08-03" @default.
- W4289637482 date "2022-08-03" @default.
- W4289637482 modified "2023-10-01" @default.
- W4289637482 title "Comment on gmd-2022-129" @default.
- W4289637482 doi "https://doi.org/10.5194/gmd-2022-129-rc2" @default.
- W4289637482 hasPublicationYear "2022" @default.
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