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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
Point of contact
Organisation name Individual name Electronic mail address Role
University of Leeds Potter, Emily Author
Northumbria University Fyffe, Catriona Author
British Antarctic Survey Orr, Andrew Author
University of Leeds Quincey, Duncan Author
University of Leeds Ross, Andrew Author
University of Plymouth Rangecroft, Sally Author
Instituto Nacional de Investigacion en Glaciares y Ecosistemas de Montana Medina, Katy Author
University of Leeds Burns, Helen Author
Servicio Nacional de Meteorologia e Hidrologia del Peru Llacza, Alan Author
Servicio Nacional de Meteorologia e Hidrologia del Peru

Jacome, Gerardo

Author
Bridgewater State University Hellstrom, Robert Author
Universidad Nacional de San Antonio Abad del Cusco Castro, Joshua Author

Autoridad Nacional del Agua

Cochachin, Alejo

Author
Universidad Nacional de San Antonio Abad del Cusco Montoya, Nilton Author
Instituto Nacional de Investigacion en Glaciares y Ecosistemas de Montana Loarte, Edwin Author
Northumbria University Pellicciotti, Francesca Author
NERC EDS UK Polar Data Centre

PDCServiceDesk@bas.ac.uk

Point of contact
Maintenance and update frequency
As needed
Maintenance note
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
  • Cordillera Blanca including Rio Santa River Basin Peru

  • Vilcanota-Urubamba River Basin Peru

GEMET - INSPIRE themes, version 1.0

  • Atmospheric conditions
Access constraints
Other restrictions
Other constraints
no limitations to public access
Access constraints
Other restrictions
Other constraints
no limitations
Use constraints
License
Other constraints
Open Government Licence v3.0
Use constraints
Other restrictions
Other constraints

Data supplied under Open Government Licence v3.0

Use constraints
Other restrictions
Other constraints

No restrictions apply.

Unique resource identifier
doi
Codespace

doi

Association Type
Cross reference
Unique resource identifier
doi
Codespace

doi

Association Type
Cross reference
Unique resource identifier
url
Codespace

url

Association Type
Cross reference
Unique resource identifier
url
Codespace

url

Association Type
Cross reference
Unique resource identifier
url
Codespace

url

Association Type
Cross reference
Unique resource identifier
url
Codespace

url

Association Type
Cross reference
Unique resource identifier
url
Codespace

url

Association Type
Cross reference
Unique resource identifier
doi
Codespace

doi

Association Type
Cross reference
Unique resource identifier
url
Codespace

url

Association Type
Larger work citation
Unique resource identifier
url
Codespace

url

Association Type
Larger work citation
Spatial representation type
Text, table
Language
English
Character set
UTF8
Topic category
  • Climatology, meteorology, atmosphere
N
S
E
W
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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.

Title

European Petroleum Survey Group (EPSG) Geodetic Parameter Registry

Date (Publication)
2008-11-12
Cited responsible party
Organisation name Individual name Electronic mail address Role

European Petroleum Survey Group

EPSGadministrator@iogp.org

Publisher
Unique resource identifier
urn:ogc:def:crs:EPSG::3031
Version

6.18.3

Distributor

Distributor contact
Organisation name Individual name Electronic mail address Role
NERC EDS UK Polar Data Centre

PDCServiceDesk@bas.ac.uk

Distributor
Distributor format
Name Version
application/x-hdf
application/netcdf
Units of distribution

bytes

Transfer size
703300894720
OnLine resource
Protocol Linkage Name

WWW:LINK-1.0-http--link

https://data.ceda.ac.uk/pdc/GB-NERC-BAS-PDC-01729

Get Data

Units of distribution

bytes

Transfer size
703300894720
OnLine resource
Protocol Linkage Name

WWW:LINK-1.0-http--link

https://data.ceda.ac.uk/pdc/GB-NERC-BAS-PDC-01729

Get Data

Hierarchy level
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.

Metadata

File identifier
67ceb7c8-218c-46e1-9927-cfef2dd95526 XML
Metadata language
English
Character set
UTF8
Hierarchy level
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)

Metadata author
Organisation name Individual name Electronic mail address Role
NERC EDS UK Polar Data Centre

polardatacentre@bas.ac.uk

Point of contact
 
 

Overviews

Spatial extent

thumbnail

Keywords

Andes CMIP Peru downscaling future projections
GEMET - INSPIRE themes, version 1.0

Atmospheric conditions
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


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