cda8bc36-7184-4956-99e7-7e7d2e0f1eb8 Scenarios Network for Alaska and Arctic Planning uaf-snap-data-tools@alaska.edu 2022-08-18T09:57:57 ISO 19115:2003/19139 1.0 3 365 1 262 20 262 20 Historical and Projected Rain On Snow (ROS) events across the State of Alaska and Surrounding Regions from 1979 to 2100 2019-01-10 Rain on snow (ROS) events were derived from 20km dynamically downscaled ERA-Interim reanalysis and global climate model (GCM) climate projections data. The GCM data were from RCP 8.5 of GFDL-CM3 and NCAR-CCSM4. The amount of liquid precipitation for each day is provided in the database for each grid cell and was determined to be a ROS event by the temperature being at or near freezing and/or the presence of snow on the ground. The rain-on-snow data were derived from the 20km downscaled data as stakeholders have identified such events as being impactful. The can be applied to local studies evaluating historical and projected change in winter rainfall events. Peter Bieniek Alaska Climate Adaptation and Science Center Scenarios Network for Alaska and Arctic Planning uaf-snap-data-tools@alaska.edu https://catalog.snap.uaf.edu/geonetwork/srv/api/records/cda8bc36-7184-4956-99e7-7e7d2e0f1eb8/attachments/ros_preview.png precipitation historical modeled projected https://creativecommons.org/licenses/by/4.0/ 20 eng climatologyMeteorologyAtmosphere 1979-01-01 2100-12-31 -237.9823 -66.0191 37.233 88.261 Rain on snow (ROS) events were derived from 20km dynamically downscaled ERA-Interim reanalysis and global climate model (GCM) climate projections data. The GCM data were from RCP 8.5 of GFDL-CM3 and NCAR-CCSM4. The amount of liquid precipitation for each day is provided in the database for each grid cell and was determined to be a ROS event by the temperature being at or near freezing and/or the presence of snow on the ground. Data are provided as NetCDF files closely following Climate and Forecasting (CF) metadata conventions, but may not be fully compliant. It is output on a 20x20km grid in a WRF-derived polar stereographic projection system aggregated at daily timesteps by year. Background The ice formed by cold-season rainfall or rain on snow (ROS) has striking impacts on the economy and ecology of Alaska. An understanding of the atmospheric drivers of ROS events is required to better predict them and plan for environmental change. The spatially/temporally sparse network of stations in Alaska makes studying such events challenging, and gridded reanalysis or remote sensing products are necessary to fill the gaps. Recently developed dynamically downscaled climate data provide a new suite of high-resolution variables for investigating historical and projected ROS events across all of Alaska. Variables include: Variable | Description ROS | Rain on snow (mm) References: Bieniek, P. A., U. S. Bhatt, J. E. Walsh, R. Lader, B. Griffith, J. K. Roach, and R. L. Thoman, 2018: Assessment of Alaska Rain-on-Snow Events Using Dynamical Downscaling. J. Appl. Meteor. Climatol., 57, 1847–1863, https://doi.org/10.1175/JAMC-D-17-0276.1 NetCDF 4.0 http://data.snap.uaf.edu/data/Base/AK_WRF/Rain_on_Snow WWW:LINK-1.0-http--link These data represent the highest quality climate projections for Alaska and Western Canada. They are updated to improve quality as issues are discovered.