67ceb7c8-218c-46e1-9927-cfef2dd95526 eng utf8 dataset dataset NERC EDS UK Polar Data Centre +44 (0)1223 221400 British Antarctic Survey, High Cross, Madingley Road Cambridge Cambridgeshire CB3 0ET United Kingdom polardatacentre@bas.ac.uk https://www.bas.ac.uk/team/business-teams/information-services/uk-polar-data-centre/ information pointOfContact 2023-04-11 ISO 19115 Geographic Information - Metadata ISO 19115:2003(E) European Petroleum Survey Group (EPSG) Geodetic Parameter Registry 2008-11-12 publication European Petroleum Survey Group EPSGadministrator@iogp.org https://www.epsg-registry.org/ EPSG Geodetic Parameter Dataset The EPSG Geodetic Parameter Dataset is a structured dataset of Coordinate Reference Systems and Coordinate Transformations, accessible through this online registry. information publisher urn:ogc:def:crs:EPSG::3031 6.18.3 Precipitation and temperature data from statistically downscaled CMIP5 models, Cordillera Blanca and Vilcanota-Urubamba regions, Peru, from 2019 to 2100 2023-04-11 creation 2023-04-11 revision 2023-04-11 publication 2023-04-11 released 1.0 https://doi.org/10.5285/67ceb7c8-218c-46e1-9927-cfef2dd95526 doi GB/NERC/BAS/PDC/01729 https://data.bas.ac.uk/ NE/S013296/1 award NE/S013318/1 award Please cite this item as: Potter, E., Fyffe, C., Orr, A., Quincey, D., Ross, A., Rangecroft, S., Medina, K., Burns, H., Llacza, A., Jacome, G., Hellstrom, R., Castro, J., Cochachin, A., Montoya, N., Loarte, E., & Pellicciotti, F. (2023). Precipitation and temperature data from statistically downscaled CMIP5 models, Cordillera Blanca and Vilcanota-Urubamba regions, Peru, from 2019 to 2100 (Version 1.0) [Data set]. NERC EDS UK Polar Data Centre. https://doi.org/10.5285/67ceb7c8-218c-46e1-9927-cfef2dd95526 Precipitation and near-surface temperature data from the Coupled Model Intercomparison Project phase 5 (CMIP5 models) are statistically downscaled to create these gridded datasets over the Rio Santa River Basin (in the Cordillera Blanca; d02) and the Vilcanota-Urubamba region (d03) at 4 km horizontal resolution, from 2019-2100. The bias-corrected WRF data found in the related dataset are used as the observational truth for the historical period 1980-2018, and the data are downscaled using an empirical quantile mapping technique. Two representative concentration pathways (RCP) have been downscaled, RCP 4.5 and RCP 8.5, from 30 CMIP5 models. The daily total precipitation and daily minimum and maximum temperature at 2 m are downscaled, and the daily average and monthly average temperatures are calculated using the hourly temperature (not archived due to space constraints). The potential evapotranspiration is estimated from the downscaled precipitation and temperature data, using the Hargreaves equation. These data were corrected as part of the PEGASUS (Producing EnerGy and preventing hAzards from SUrface water Storage in Peru) and Peru GROWS (Peruvian Glacier Retreat and its Impact on Water Security) projects. The datasets were created to assess future climate in the Peruvian Andes, as a basis to determine future climate in the region, and as an input for glaciological and hydrological models. The data were created on the JASMIN supercomputer. The creation of this data was conducted under the Peru GROWS and PEGASUS projects, which were both funded by NERC (grants NE/S013296/1 and NE/S013318/1, respectively) and CONCYTEC through the Newton-Paulet Fund. The Peruvian part of the Peru GROWS project was conducted within the framework of the call E031-2018-01-NERC "Glacier Research Circles", through its executing unit FONDECYT (Contract No. 08-2019-FONDECYT). No credit. completed Potter, Emily University of Leeds Researcher author Fyffe, Catriona Northumbria University Researcher author Orr, Andrew British Antarctic Survey Researcher author Quincey, Duncan University of Leeds Researcher author Ross, Andrew University of Leeds Researcher author Rangecroft, Sally University of Plymouth Researcher author Medina, Katy Instituto Nacional de Investigacion en Glaciares y Ecosistemas de Montana Researcher author Burns, Helen University of Leeds Researcher author Llacza, Alan Servicio Nacional de Meteorologia e Hidrologia del Peru Researcher author Jacome, Gerardo Servicio Nacional de Meteorologia e Hidrologia del Peru Researcher author Hellstrom, Robert Bridgewater State University Researcher author Castro, Joshua Universidad Nacional de San Antonio Abad del Cusco Researcher author Cochachin, Alejo Autoridad Nacional del Agua Researcher author Montoya, Nilton Universidad Nacional de San Antonio Abad del Cusco Researcher author Loarte, Edwin Instituto Nacional de Investigacion en Glaciares y Ecosistemas de Montana Researcher author Pellicciotti, Francesca Northumbria University Researcher author NERC EDS UK Polar Data Centre +44 (0)1223 221400 British Antarctic Survey, High Cross, Madingley Road Cambridge Cambridgeshire CB3 0ET United Kingdom PDCServiceDesk@bas.ac.uk https://www.bas.ac.uk/team/business-teams/information-services/uk-polar-data-centre/ information pointOfContact asNeeded completed EARTH SCIENCE > Atmosphere > Atmospheric Temperature > Air Temperature EARTH SCIENCE > Atmosphere > Atmospheric Temperature > Maximum/Minimum Temperature EARTH SCIENCE > Atmosphere > Atmospheric Temperature > Surface Air Temperature EARTH SCIENCE > Atmosphere > Atmospheric Water Vapor > Evapotranspiration EARTH SCIENCE > Atmosphere > Precipitation > Precipitation Rate theme Global Change Master Directory (GCMD) Science Keywords 2026-01-27 publication 23 Global Change Data Center, Science and Exploration Directorate, Goddard Space Flight Center (GSFC) National Aeronautics and Space Administration (NASA) Greenbelt MD United States of America https://earthdata.nasa.gov/about/gcmd/global-change-master-directory-gcmd-keywords Global Change Master Directory (GCMD) Keywords The information provided on this page seeks to define how the GCMD Keywords are structured, used and accessed. It also provides information on how users can participate in the further development of the keywords. information publisher Andes CMIP Peru downscaling future projections theme Cordillera Blanca including Rio Santa River Basin Peru Vilcanota-Urubamba River Basin Peru place Atmospheric conditions theme GEMET - INSPIRE themes, version 1.0 2021-01-06 revision otherRestrictions no limitations to public access otherRestrictions no limitations license Open Government Licence v3.0 otherRestrictions Data supplied under Open Government Licence v3.0 otherRestrictions No restrictions apply. doi doi crossReference doi doi crossReference url url crossReference url url crossReference url url crossReference url url crossReference url url crossReference doi doi crossReference url url largerWorkCitation url url largerWorkCitation textTable eng utf8 climatologyMeteorologyAtmosphere -79.5 -76.3 -10.8 -7.5 2019-01-01 2100-12-31 It is recommended that careful attention be paid to the contents of any data, and that the author be contacted with any questions regarding appropriate use. If you find any errors or omissions, please report them to polardatacentre@bas.ac.uk. NERC EDS UK Polar Data Centre +44 (0)1223 221400 British Antarctic Survey, High Cross, Madingley Road Cambridge Cambridgeshire CB3 0ET United Kingdom PDCServiceDesk@bas.ac.uk https://www.bas.ac.uk/team/business-teams/information-services/uk-polar-data-centre/ information distributor application/x-hdf application/netcdf bytes 703300894720 https://data.ceda.ac.uk/pdc/GB-NERC-BAS-PDC-01729 WWW:LINK-1.0-http--link Get Data Download data download bytes 703300894720 https://data.ceda.ac.uk/pdc/GB-NERC-BAS-PDC-01729 WWW:LINK-1.0-http--link Get Data Download data download dataset Methodology: First, the CMIP5 models are regridded to the horizontal resolution of the WRF grid using bilinear interpolation. The statistical downscaling follows the empirical quantile mapping technique described in Cannon et al. (2015). This method preserves the large-scale trends from the CMIP5 models at each quantile (i.e. the trends in both the median and the extremes are preserved), while adjusting the number of wet days and the magnitude of precipitation and temperature based on the values from 1980-2018. The hourly temperature is calculated by scaling the raw WRF output to the bias-corrected minimum and maximum daily temperatures. Full details of the methodology can be found in Potter et al., (2023). Data collection: See the reference materials for information on the CMIP5 models. Data quality: There are no known quality issues with the data. asNeeded completed