Tag: journal of hydrometeorology

Figure: Three-year JJA-averaged quantities are shown for the WRFS simulation and (b), (d) the differences (WRFG - WRFS) in those quantities, where S and G stand for the different soil datasets. (top) Precipitable water (kg m-2) and (bottom) vertically integrated moisture flux vectors every 20 grid spaces (kg m s-1). Stippled areas in (b) and red vectors in (d) show 90% confidence intervals (p = 0.1).

Soil Properties and the Atmospheric Moisture Budget

May 23, 2022

ESSIC/CISESS Scientists Eli Dennis (a former CISESS grad student), and Hugo Berbery have a new article published in the May 2022 issue of the Journal of Hydrometeology critiquing how models represent soil attributes.

Using Machine Learning to Improve Snow Cover Fraction Observations

January 25, 2022

ESSIC/CISESS scientists Soni Yatheendradas and Sujay Kumar are co-authors on a paper in Journal of Hydrometeorology titled, “A novel Machine Learning-based gap-filling of fine-resolution remotely sensed snow cover fraction data by combining downscaling and regression”.

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Last Updated: 24 April 2024

Tag: journal of hydrometeorology

Soil Properties and the Atmospheric Moisture Budget

Using Machine Learning to Improve Snow Cover Fraction Observations

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