CESM Large Ensemble RCP 8.5-driven, post-processed Weather Research and Forecasting (WRF) model output for Greenland melt season, 2071-2080

• Main Author: B. Reusch, David
• Format: Dataset
• Language: English
• Published: NSF Arctic Data Center 2020
• Subjects: EARTH SCIENCE > ATMOSPHERE; EARTH SCIENCE SERVICES > MODELS; EARTH SCIENCE SERVICES > MODELS > WEATHER RESEARCH/FORECAST MODELS; Greenland; Kay; Dee; Duda; Hines; Sanderson; Ice Sheet; National Snow and Ice Data Center; Sea ice
• Online Access: https://dx.doi.org/10.18739/a2gq6r33x; https://arcticdata.io/catalog/view/doi:10.18739/A2GQ6R33X

Summary This dataset contains postprocessed, high resolution (15 kilometers (km), 3 hours (h)) output from Polar Weather Research and Forecast (WRF) driven by Community Earth System Model (CESM) Large Ensemble Representative Concentration Pathway (RCP) 8.5 dataset, Jun-Jul-Aug, 2071-2080. These simulations used WRF-distributed ice sheet topography and General Circulation Model (GCM)-derived sea ice. Details These datasets are output from the regional forecast model Polar WRF (i.e., WRF-Advanced Research WRF (ARW) with polar modifications developed by the Polar Meteorology Group at The Ohio State University; Hines and Bromwich 2008; Skamarock et al 2008). Datasets are available as both original model output and as post-processed output, i.e, model output that has been processed into more user-friendly format with an National Center for Atmospheric Research (NCAR) Command Language (NCL) script. Post-processed files are also smaller after removing variables of lesser interest. All datasets are on a 15-km spatial grid with 39 vertical levels. Output is archived every 3 hours for the core melt-season months of June, July and August. WRF initial and boundary conditions were provided by three global datasets: the European Centre for Medium-Range Weather Forecasts (ECMWF) Re-Analysis (ERA) Interim reanalysis (ECMWF, erai, Dee et al, 2011), the CESM Large Ensemble (NCAR, cesmle, Kay et al, 2015) and the CESM Low Warming Ensemble (NCAR, cesmlw, Sanderson et al 2016). Simulations cover two broad time periods: historical (or hindcast) and future (based on standard emissions scenarios). Future, GCM-based simulations cover a “high warming” scenario based on RCP 8.5 and a “low warming” scenario based on limiting future temperature increases to 1.5 degrees Celsius above pre-industrial levels. These simulations are limited to time periods where the driving variables required by WRF were archived for the GCM at sub-daily resolution. ERA Interim-based WRF simulations were done as overlapping 3-day runs with the first day discarded for spinup and the remaining days concatenated to produce the time series. These simulations used the Bootstrap Sea Ice dataset (Comiso 2000) from National Snow and Ice Data Center (NSIDC) for sea ice data. GCM-based WRF simulations were done as overlapping month-plus-one day runs with the first day discarded for spinup and the remaining days concatenated to produce the time series. These runs used upper level four dimensional data assimilation (grid nudging) to maintain the large- scale wave patterns from CESM during these long simulations. To be self-consistent, these runs used sea ice data from that component (Community Ice CodE (CICE)) of the GCM instead of the Bootstrap dataset. Model domain corner coordinates are: 55.2 North, 62.2 West (Southwest), 76.2 North, 117.2 West (Northwest), 76.2 North, 37.2 East (Northeast), 55.2 North, 17.8 West (Southeast). References Comiso, J. C. 2000, updated 2015. Bootstrap Sea Ice Concentrations from Nimbus-7 Scanning Multichannel Microwave Radiometer (SMMR) and Defense Meteorological Satellite Program (DMSP) Special Sensor Microwave/Imager (SSM/I)-SSMIS, Version 2. Boulder, Colorado USA. National Aeronautics and Space Administration (NASA) National Snow and Ice Data Center Distributed Active Archive Center. doi: https://doi.org/10.5067/J6JQLS9EJ5HU. Dee, D.P., with 35 co-authors, 2011: The ERA-Interim reanalysis: configuration and performance of the data assimilation system. Quart. J. R. Meteorol. Soc., 137, 553-597, doi: 10.1002/qj.828. Hines, K. M., and D. H. Bromwich, 2008: Development and testing of Polar WRF. Part I. Greenland ice sheet meteorology. Mon. Wea. Rev., 136, 1971-1989. Howat, I.M., A. Negrete, B.E. Smith, 2014: The Greenland Ice Mapping Project (GIMP) land classification and surface elevation datasets, The Cryosphere, 8, 1509-1518, doi:10.5194/tc-8-1509-2014. Kay, J. E., with 20 co-authors, 2015: CESM Large Ensemble Project: A Community Resource for Studying Climate Change in the Presence of Internal Climate Variability, Bulletin of the American Meteorological Society, 96, 1333-1349, doi: 10.1175/BAMS-D-13-00255.1. Sanderson, B., B. O'Neill, and C. Tebaldi, 2016: What would it take to achieve the Paris temperature targets? Geophys. Res. Lett., doi: 10.1002/2016GL069563. Skamarock, W. C., Klemp, J. B., Dudhia, J., Gill, D. O., Barker, D., Duda, M. G., Huang, X.-Y., Wang, W., and Powers, J. G., 2008, A Description of the Advanced Research WRF Version 3 (No. NCAR/TN-475+STR). University Corporation for Atmospheric Research. doi:10.5065/D68S4MVH