Preprints
https://doi.org/10.5194/gmd-2022-129
https://doi.org/10.5194/gmd-2022-129
Submitted as: development and technical paper
07 Jul 2022
Submitted as: development and technical paper | 07 Jul 2022
Status: this preprint is currently under review for the journal GMD.

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

Joachim Meyer1, S. McKenzie Skiles1, John Horel2, Patrick Kormos3, Andrew Hedrick4, and Ernesto Trujillo5,4 Joachim Meyer et al.
  • 1Department of Geography, University of Utah, Salt Lake City, UT, USA
  • 2Department of Atmospheric Sciences, University of Utah, Salt Lake City, UT, USA
  • 3Colorado Basin River Forecast Center NOAA National Weather Service, Salt Lake City, UT, USA
  • 4Northwest Watershed Research Center, USDA Agricultural Research Service, Boise, ID, USA
  • 5Department of Geosciences, Boise State University, Boise, ID, USA

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.

Joachim Meyer et al.

Status: open (until 01 Sep 2022)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on gmd-2022-129', Bertrand Cluzet, 30 Jul 2022 reply
  • RC2: 'Comment on gmd-2022-129', Anonymous Referee #2, 03 Aug 2022 reply

Joachim Meyer et al.

Joachim Meyer et al.

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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.