Articles | Volume 16, issue 1
Development and technical paper
10 Jan 2023
Development and technical paper |  | 10 Jan 2023

Operational water forecast ability of the HRRR-iSnobal combination: an evaluation to adapt into production environments

Joachim Meyer, John Horel, Patrick Kormos, Andrew Hedrick, Ernesto Trujillo, and S. McKenzie Skiles

Data sets

ASO L4 Lidar Snow Depth 50m UTM Grid, Version 1 T. Painter

Model code and software

Spatial Modeling for Resources Framework (SMRF) (v0.9.1) Scott Havens, Danny Marks, Patrick Kormos, Andrew Hedrick, Ernesto Trujillo, Micah Johnson, Micah Sandusky, and Mark Robertson

Automated Water Supply Model (AWSM) (v0.10.0) Scott Havens, Danny Marks, Micah Sandusky, Micah Johnson, Mark Robertson, Andrew Hedrick, and Patrick Kormos

UofU-Cryosphere/weather_forecast_retrieval: GMD submission (Version 20220512) Scott Havens, Joachim Meyer, Micah Sandusky, Micah Johnson, and Mark Robertson

UofU-Cryosphere/isnoda: GMD-final (Version 20221212) Joachim Meyer and Dillon Ragar

Short summary
Freshwater resupply from seasonal snow in the mountains is changing. Current water prediction methods from snow rely on historical data excluding the change and can lead to errors. This work presented and evaluated an alternative snow-physics-based approach. The results in a test watershed were promising, and future improvements were identified. Adaptation to current forecast environments would improve resilience to the seasonal snow changes and helps ensure the accuracy of resupply forecasts.