NERC Data Catalogue Service
Precipitation and temperature data from statistically downscaled CMIP5 models, Cordillera Blanca and Vilcanota-Urubamba regions, Peru, from 2019 to 2100
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).
Simple
- Date (Creation)
- 2023-04-11
- Date (Revision)
- 2023-04-11
- Date (Publication)
- 2023-04-11
- Date (released)
- 2023-04-11
- Edition
- 1.0
- Unique resource identifier
- https://doi.org/10.5285/67ceb7c8-218c-46e1-9927-cfef2dd95526
- Codespace
- doi
- Unique resource identifier
- GB/NERC/BAS/PDC/01729
- Codespace
- https://data.bas.ac.uk/
- Unique resource identifier
- NE/S013296/1
- Codespace
- award
- Unique resource identifier
- NE/S013318/1
- Codespace
- award
- Other citation details
- 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
- Credit
- No credit.
- Status
- completed Completed
https://www.bas.ac.uk/team/business-teams/information-services/uk-polar-data-centre/
- Maintenance and update frequency
- asNeeded As needed
- Maintenance note
- completed Completed
- Global Change Master Directory (GCMD) Science Keywords
-
- 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
-
- Andes
- CMIP
- Peru
- downscaling
- future projections
- Place
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- Cordillera Blanca including Rio Santa River Basin Peru
- Vilcanota-Urubamba River Basin Peru
- GEMET - INSPIRE themes, version 1.0
- Access constraints
- otherRestrictions Other restrictions
- Other constraints
- no limitations to public access
- Access constraints
- otherRestrictions Other restrictions
- Other constraints
- no limitations
- Use constraints
- license License
- Other constraints
- Open Government Licence v3.0
- Use constraints
- otherRestrictions Other restrictions
- Other constraints
- Data supplied under Open Government Licence v3.0
- Use constraints
- otherRestrictions Other restrictions
- Other constraints
- No restrictions apply.
- Unique resource identifier
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- Spatial representation type
- textTable Text, table
- Metadata language
- engEnglish
- Character set
- utf8 UTF8
- Topic category
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- Climatology, meteorology, atmosphere
))
- Begin date
- 2019-01-01
- End date
- 2100-12-31
- Supplemental Information
- 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.
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https://www.bas.ac.uk/team/business-teams/information-services/uk-polar-data-centre/
- Name
- application/x-hdf
- Name
- application/netcdf
- Units of distribution
- bytes
- Transfer size
- 703300894720
- OnLine resource
-
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- Units of distribution
- bytes
- Transfer size
- 703300894720
- OnLine resource
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- Hierarchy level
- dataset Dataset
- Statement
-
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.
- File identifier
- 67ceb7c8-218c-46e1-9927-cfef2dd95526 XML
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- engEnglish
- Character set
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- Hierarchy level
- dataset Dataset
- Hierarchy level name
- dataset
- Date stamp
- 2023-04-11
- Metadata standard name
- ISO 19115 Geographic Information - Metadata
- Metadata standard version
- ISO 19115:2003(E)
https://www.bas.ac.uk/team/business-teams/information-services/uk-polar-data-centre/
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