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

Abstract

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 (T a ) 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 (T w ), which is closer to the surface temperature of a falling hydrometeor than T a . T w becomes more depressed in drier environments as derived from T w depression equation using T a and surface air humidity, resulting in a greater fraction of snowfall. We implemented this new T w scheme in the Noah-MP land surface model and evaluated the model against a high-quality ground-based snow product over the contiguous United States. The results suggest that the new T w scheme substantially improves the model skill in simulating snow depth and snow water equivalent over most snow-covered grids, especially the higher and drier continental mountain ranges in the Western United States, while it retains the modeling accuracy over the more humid Eastern United States.Plain Language Summary The partitioning between rainfall and snowfall is important for understanding the impacts of climate change and water resource availability. Most land surface and hydrological models use surface air temperature to partition precipitation into rain and snow and thus underestimate snowfall and snow mass accumulated on the ground in the drier Western United States. A falling hydrometeor evaporates or sublimates at its surface depending on the humidity of the surrounding air and cools off, resulting in a surface temperature that is cooler than the air temperature. The depressed surface temperature is close to the wet-bulb temperature. We developed a scheme using the wet-bulb temperature and tested it with a physically based snow model over the contiguous United States. The testing results strongly support the use of wet-bulb temperature, which enhances snowfall and the snow mass on the ground more significantly over the higher and drier mountains in the Western United States, while it retains the modeling accuracy in the more humid Eastern United States.

Technical note: Precipitation-phase partitioning at landscape scales to regional scales

“…The height of the freezing level is an important parameter for evaluating climate variability and change in mountain environments (Diaz et al, 2003). Freezing level height influences the phase of precipitation at a given elevation, the state of the land surface (frozen or unfrozen), the thermodynamic processes occurring in an existing snowpack leading to snowpack ripening and melt, and the duration of the snow-free season (Diaz et al, 2003;White et al, 2010;Sospedra-Alfonso et al, 2015;Contosta et al, 2019). The NAFLT calculates the freezing level as the highest elevation in the troposphere (200-1000 hPa) above mean sea level where free air temperatures are 0 • C for each 2.5 • NCEP/NCAR grid point (Step 1 in the conceptual diagram shown in Fig.…”

Why Is the Terrestrial Water Storage in Dryland Regions Declining? A Perspective Based on Gravity Recovery and Climate Experiment Satellite Observations and Noah Land Surface Model With Multiparameterization Schemes Model Simulations

“…We adopted the modified scheme of two‐stream radiation transfer through the plant canopy (Niu & Yang, 2004) and the CLASS‐type for snow surface albedo (Verseghy, 1991). Partitioning of precipitation into rainfall and snowfall uses a sigmoidal relationship of the wet bulb temperature (Wang et al, 2019). The lower boundary condition of soil temperature at 8 m deep is assumed the hourly climatology of the near‐surface air temperature.…”

Interactions between snow cover and evaporation lead to higher sensitivity of streamflow to temperature

“…To estimate PET over unstressed surfaces of free water and partially snow covered, we employed a widely used LSM, Noah with multi-physics (Noah-MP) 26 . Noah-MP is a widely used LSM with demonstrated ability in simulating land surface fluxes 26,34,35 . Noah-MP considers detailed snowpack physics (e.g., liquid water retention and refreezing, densification, heat released or absorbed due to phase changes, and surface albedo changes due to snow aging), and surface energy and mass exchanges with the atmosphere (e.g., sublimation/deposition, patchy snow effects on surface albedo, and surface turbulent heat and moisture exchanges, etc.).…”

“…In addition, to ensure a conceptual agreement between Noah-MP evaporation and that of conventionally employed analytical solutions 11,13,28 , we excluded the stability correction to the surface drag coefficient, though the atmospheric warming may substantially increase the surface layer stability over snow and lake surfaces 27 suppressing the surface turbulent exchanges of water and energy with the atmosphere. We estimated f s based on a new snow-rain partitioning scheme using a sigmoidal function of wet-bulb temperature, which was demonstrated to improve snow simulations in the CONUS 35 .…”