Operational water forecast ability of the HRRR-iSnobal combination: an evaluation to adapt into production environments
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Published:2023-01-10
Issue:1
Volume:16
Page:233-250
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ISSN:1991-9603
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Container-title:Geoscientific Model Development
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language:en
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Short-container-title:Geosci. Model Dev.
Author:
Meyer JoachimORCID, Horel John, Kormos PatrickORCID, Hedrick AndrewORCID, Trujillo ErnestoORCID, Skiles S. McKenzieORCID
Abstract
Abstract. Operational water-resource forecasters, such as the Colorado Basin River
Forecast Center (CBRFC) in the Western United States, currently rely on historical records to calibrate the temperature-index models used for
snowmelt runoff predictions. This data dependence is increasingly
challenged, with global and regional climatological factors changing the
seasonal snowpack dynamics 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 prediction model across 4 years in a Colorado River Basin forecast region. Compared to in situ, remotely sensed, and the current operational CBRFC model data, the HRRR-iSnobal combination
showed well-reconstructed snow depth patterns and magnitudes until peak
accumulation. Once snowmelt set in, HRRR-iSnobal showed slower simulated
snowmelt relative to observations, depleting snow on average up to 34 d
later. The melting period is a critical component for water forecasting.
Based on the results, there is a need for revised forcing data input
preparation (shortwave radiation) required by iSnobal, which is a
recommended future improvement to the model. Nevertheless, the presented
performance and architecture make HRRR-iSnobal 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. The
long-term goal is to introduce the HRRR-iSnobal combination in day-to-day
CBRFC operations, and this work created the foundation to expand and
evaluate larger CBRFC domains.
Funder
Earth Sciences Division
Publisher
Copernicus GmbH
Reference81 articles.
1. Anderson, E. A.: A point energy and mass balance model of a snow cover, United States, National Weather Service, https://repository.library.noaa.gov/view/noaa/6392 (last access: 28 February 2022), 1976. 2. Ayers, J., Ficklin, D. L., Stewart, I. T., and Strunk, M.: Comparison of
CMIP3 and CMIP5 projected hydrologic conditions over the Upper Colorado
River Basin, Int. J. Climatol., 36, 3807–3818,
https://doi.org/10.1002/joc.4594, 2016. 3. Bellaire, S., Jamieson, J. B., and Fierz, C.: Forcing the snow-cover model SNOWPACK with forecasted weather data, The Cryosphere, 5, 1115–1125, https://doi.org/10.5194/tc-5-1115-2011, 2011. 4. Bellaire, S., Jamieson, J. B., and Fierz, C.: Corrigendum to “Forcing the snow-cover model SNOWPACK with forecasted weather data” published in The Cryosphere, 5, 1115–1125, 2011, The Cryosphere, 7, 511–513, https://doi.org/10.5194/tc-7-511-2013, 2013. 5. Benjamin, S. G., Weygandt, S. S., Brown, J. M., Hu, M., Alexander, C. R.,
Smirnova, T. G., Olson, J. B., James, E. P., Dowell, D. C., Grell, G. A.,
Lin, H., Peckham, S. E., Smith, T. L., Moninger, W. R., Kenyon, J. S., and
Manikin, G. S.: A North American Hourly Assimilation and Model Forecast
Cycle: The Rapid Refresh, Mon. Weather Rev., 144, 1669–1694,
https://doi.org/10.1175/MWR-D-15-0242.1, 2016.
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