Data from: Spatial variation of the rain-snow temperature threshold across the Northern Hemisphere

We present the first continuous map of rain-snow air temperature thresholds over the Northern Hemisphere land surface, underlining the spatial variability of precipitation phase partitioning. Land surface models typically discriminate between rain and snow using a simple, spatially uniform air temperature threshold, but observations indicate the threshold is not static. Our analysis of a 29-year observational dataset (n = 17.8 million) shows the threshold varies significantly, averaging 1.0°C and ranging from -0.4°C to 2.4°C for 95% of Northern Hemisphere stations, with continental climates exhibiting the warmest thresholds and maritime the coolest. Relative humidity exerts the strongest control on phase partitioning, while surface pressure plays a secondary role. Simulations indicate the selection of a rain-snow threshold introduces significant uncertainty to snowfall frequency and that including relative humidity as a predictor variable provides the greatest improvement to precipitation phase prediction between 0.6°C and 3.4°C, the interval where phase partitioning is most uncertain.Station locations and elevationsLatitude, longitude, and elevation for all meteorological and precipitation phase observation stations used in the Jennings et al. (2018) manuscript.jennings_et_al_2018_file1_station_locs_elev.csvPrecipitation phase and meteorological observationsObservations of precipitation phase and meteorological data used in the Jennings et al. (2018) manuscript. Please note, this is a cleaned, formatted version of the http://rda.ucar.edu/datasets/ds464.0/ dataset. Be sure to cite the original dataset as well if you choose to use these data in your work.jennings_et_al_2018_file2_ppt_phase_met_observations.csvObserved 50% rain-snow air temperature thresholds50% rain-snow air temperature thresholds for 6,883 Northern Hemisphere stations. Snow frequency was calculated per 1°C temperature bin using observations of precipitation phase. A hyperbolic tangent was then fit to the frequency data and used to calculate the 50% rain-snow air temperature threshold. All NA values indicate there were not enough data to fit the hyperbolic tangent.jennings_et_al_2018_file3_temp50_observed_by_station.csvSimulated 50% rain-snow air temperature thresholds (hyperbolic tangent)Map of simulated 50% rain-snow air temperature thresholds based on a bivariate binary logistic regression phase prediction model applied to 27 years of MERRA-2 reanalysis data. The probability of snowfall was predicted for each precipitation event in the record as a function of air temperature and relative humidity. For each MERRA-2 grid cell, the probabilities were binned by 1°C air temperature bins to produce a snow frequency curve. A hyperbolic tangent was then fit to the data and used to calculate the 50% rain-snow air temperature threshold.jennings_et_al_2018_file4_temp50_raster.tifSimulated 50% rain-snow air temperature thresholds (linear regression)Map of simulated 50% rain-snow air temperature thresholds based on a bivariate binary logistic regression phase prediction model applied to 27 years of MERRA-2 reanalysis data. The probability of snowfall was predicted for each precipitation event in the record as a function of air temperature and relative humidity. For each MERRA-2 grid cell, the probabilities were binned by 1°C air temperature bins to produce a snow frequency curve. The 50% rain-snow air temperature threshold was then calculated using a linear regression on snow frequency between 0.5°C and 6.5°C. This approach was used for grid cells without enough snow and rain events to compute the threshold using a hyperbolic tangent.jennings_et_al_2018_file5_temp50_linregr_raster.tifR code for calculating observed 50% rain-snow air temperature thresholdsR code for computing the 50% rain-snow air temperature threshold using the station data in jennings_et_al_2018_file2_ppt_phase_met_observations.csvjennings_et_al_2018_file6_precipphase_station_observations_code.RR code for evaluating precipitation phase methodsR code for evaluating the performance of different precipitation phase methods using the station data in jennings_et_al_2018_file2_ppt_phase_met_observations.csvjennings_et_al_2018_file7_precipphase_phasemethods_code.RR code for mapping simulated rain-snow thresholdsR code for creating the simulated 50% rain-snow air temperature threshold maps (jennings_et_al_2018_file4_temp50_raster.tif and jennings_et_al_2018_file5_temp50_linregr_raster.tif).jennings_et_al_2018_file8_precipphase_merra_threshold_simulation_code.RR code for snowfall frequency uncertaintyR code for analyzing the sensitivity of simulated snowfall frequency to 18 different precipitation phase methods.jennings_et_al_2018_file9_precipphase_merra_snowfall_frequency_sensitivity_code.RFunding provided by: National Science FoundationCrossref Funder Registry ID: http://dx.doi.org/10.13039/100000001Award Number: DGE-114408