A Wet‐Bulb Temperature‐Based Rain‐Snow Partitioning Scheme Improves Snowpack Prediction Over the Drier Western United States

Wang, Yuan‐Heng; Broxton, Patrick; Fang, Yuanhao; Behrangi, Ali; Barlage, Michael; Zeng, Xubin; Niu, Guo‐Yue

doi:10.1029/2019gl085722

i

A Wet‐Bulb Temperature‐Based Rain‐Snow Partitioning Scheme Improves Snowpack Prediction Over the Drier Western United States

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2019
By Wang, Yuan‐Heng ; Broxton, Patrick ; Fang, Yuanhao ; ...

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Journal Title:

Geophysical Research Letters
Personal Author:

Wang, Yuan‐Heng ; Broxton, Patrick ; Fang, Yuanhao ; Behrangi, Ali ; Barlage, Michael ; Zeng, Xubin ; Niu, Guo‐Yue
NOAA Program & Office:

OAR (Oceanic and Atmospheric Research)
Description:

Accumulation of snowfall during winter and snowmelt in the subsequent spring or earlier summer provides a dominant water source in alpine regions. Most land surface and hydrological models use near ‐surface air temperature ( Ta) thresholds to partition precipitation into snow and rain, underestimating snowfall over drier regions. We developed a snow ‐rain partitioning scheme using the wet ‐bulb temperature ( Tw), which is closer to the surface temperature of a falling hydrometeor than Ta.Twbecomes more depressed in drier environments as derived from Twdepression equation using Taand surface air humidity, resulting in a greater fraction of snowfall. We implemented this new Twscheme
Keywords:

General Earth And Planetary Sciences Geophysics General Earth And Planetary Sciences General Earth And Planetary Sciences
Source:

Geophysical Research Letters, 46(23), 13825-13835
DOI:

https://doi.org/10.1029/2019gl085722
ISSN:

0094-8276 ; 1944-8007
Format:

PDF
Publisher:

American Geophysical Union (AGU)
Document Type:

Journal Article
Funding:

Grant no. NA18OAR4590397
Rights Information:

Other
Compliance:

Library
Main Document Checksum:

urn:sha256:ae4bc7943f9606618cc3812cd638d7a735d020181351734ba4b0dda5f1a160c0
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https://repository.library.noaa.gov/view/noaa/54993/noaa_54993_DS1.pdf
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[PDF - 21.92 MB ]

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