Work

Snow-to-Liquid Ratio Prediction over the Contiguous United States Using Machine Learning

Year: 2026

Type: article

Source: Weather and Forecasting

DOI: 10.1175/waf-d-25-0124.1

Authors: Michael D. Pletcher, Peter G. Veals, Randy J. Chase, Steven D. Hilberg, Noah Newman, Andrew A. Rosenow, W. James Steenburgh

Institutions: University of Utah, The Tomorrow Companies Inc. (United States), Colorado State University, NOAA National Severe Storms Laboratory

Topic: Meteorological Phenomena and Simulations

Subfield: Atmospheric Science

Field: Earth and Planetary Sciences

Domain: Physical Sciences

SDG: Climate action

Open Access status: closed

Funders: Climate Program Office, NOAA Weather Program Office

Awards: G3677800767, G4081594127, Analysis of Longitudinal Extreme Weather and Society Data and Development of the Flood Weather Survey and Dashboard, G8699802603

OpenAlex ID: W7119005367

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