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Despite the importance of precipitation phase to global hydroclimate simulations, many land surface models use spatially uniform air temperature thresholds to partition rain and snow. Here we show, through the analysis of a 29-year observational dataset (n = 17.8 million), that the air temperature at which rain and snow fall in equal frequency varies significantly across the Northern Hemisphere, averaging 1.0 °C and ranging from -0.4 to 2.4 °C for 95% of the stations. Continental climates generally exhibit the warmest rain-snow thresholds and maritime the coolest. Simulations show precipitation phase methods incorporating humidity perform better than air temperature-only methods, particularly at relative humidity values below saturation and air temperatures between 0.6 and 3.4 °C. We also present the first continuous Northern Hemisphere map of rain-snow thresholds, underlining the spatial variability of precipitation phase partitioning. These results suggest precipitation phase could be better predicted using humidity and air temperature in large-scale land surface model runs.
This manuscript describes an observationally-based dataset of soil evaporation for the conterminous U.S. (CONUS), gridded to a 9 km resolution for the time-period of April 2015-March 2019. This product is termed E-SMAP (Evaporation-Soil Moisture Active Passive) in which soil evaporation is estimated from the surface layer, defined by the SMAP sensing depth of 50 mm, between SMAP overpass intervals that are screened on the basis of precipitation and SMAP quality control flags. Soil evaporation is estimated using a water balance of the surface soil that we show is largely dominated by SMAP-observed soil drying. E-SMAP soil evaporation is on average 0.72 mm day-1, which falls within the range of soil evaporation estimates (0.17-0.89 mm day-1) derived from operational land surface models and an alternative remote sensing product. E-SMAP is independent from existing soil evaporation estimates and therefore has the potential to improve understanding of evapotranspiration partitioning and model development.
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