2017
DOI: 10.1002/2017gl075046
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Relative Humidity Has Uneven Effects on Shifts From Snow to Rain Over the Western U.S.

Abstract: Predicting the phase of precipitation is fundamental to water supply and hazard forecasting. Phase prediction methods (PPMs) are used to predict snow fraction, or the ratio of snowfall to total precipitation. Common temperature‐based regression (Dai method) and threshold at freezing (0°C) PPMs had comparable accuracy to a humidity‐based PPM (TRH method) using 6 and 24 h observations. Using a daily climate data set from 1980 to 2015, the TRH method estimates 14% and 6% greater precipitation‐weighted snow fracti… Show more

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Cited by 49 publications
(39 citation statements)
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“…Figure shows that the declining trends in annual maximum M _ only (not including ROS) were higher and more widespread than the other three W conditions with the inclusion of ROS, indicating that annual maximum M _ ros was less likely to be affected by a warming climate. These results were expected because a warming climate can cause more precipitation to fall as rain and partially offset the loss of snowpack (Musselman et al, ), especially in the regions that experience higher humidity and warmer wet bulb temperatures (Harpold et al, ; Rupp & Li, ). In Figures S6–S7, higher humidity is associated with larger annual maximum M _ ros across all SNOTEL stations, highlighting the importance of humidity in controlling the precipitation phase and, consequently, affecting the ROS intensity.…”
Section: Discussionmentioning
confidence: 94%
“…Figure shows that the declining trends in annual maximum M _ only (not including ROS) were higher and more widespread than the other three W conditions with the inclusion of ROS, indicating that annual maximum M _ ros was less likely to be affected by a warming climate. These results were expected because a warming climate can cause more precipitation to fall as rain and partially offset the loss of snowpack (Musselman et al, ), especially in the regions that experience higher humidity and warmer wet bulb temperatures (Harpold et al, ; Rupp & Li, ). In Figures S6–S7, higher humidity is associated with larger annual maximum M _ ros across all SNOTEL stations, highlighting the importance of humidity in controlling the precipitation phase and, consequently, affecting the ROS intensity.…”
Section: Discussionmentioning
confidence: 94%
“… Greater sensitivity to errors associated with the temperature‐only precipitation partitioning method (Harpold, Kaplan, et al, ; Jennings et al, ; Wayand et al, ). Improvement can be made by incorporating wet bulb temperature, dew point temperature, or relative humidity into the partitioning method (Ding et al, ; Harpold, Rajagopal, et al, ; Jennings et al, ; Marks et al, ). Greater sensitivity to errors in model simulated energy balances (Essery et al, ; Lapo et al, ). For instance, although mountain microclimate simulation model algorithms perform reasonably well under most climate conditions, they produce significantly higher (negative) bias in shortwave fluxes and (positive) longwave fluxes in coastal maritime environments (Bohn et al, ; Currier et al, ).…”
Section: Resultsmentioning
confidence: 99%
“…The snow‐covered season is the continuous period between initial snow cover and end of season snow disappearance that spans the date of maximum annual SWE. We make no effort to distinguish precipitation phase because of the challenges of doing so without local measurements (Harpold et al, ) of temperature and its relationship to phase (Rajagopal & Harpold, ). Moreover, we were not able to distinguish between melt and rain on days where both may have occurred and thus assumed that all rainwater was stored long enough on the pillow to be recorded (i.e., rain did not drain directly to the soil surface).…”
Section: Data Sets and Methodsmentioning
confidence: 99%