Deep Learned Process Parameterizations Provide Better Representations of Turbulent Heat Fluxes in Hydrologic Models
Author:
Affiliation:
1. Department of Civil and Environmental Engineering University of Washington Seattle WA USA
Funder
National Science Foundation
Publisher
American Geophysical Union (AGU)
Subject
Water Science and Technology
Link
https://onlinelibrary.wiley.com/doi/pdf/10.1029/2020WR029328
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