BGS Hosted Metadata
Downscaled ERA5 monthly precipitation data using Multi-Fidelity Gaussian Processes between 1980 and 2012 for the Upper Beas and Sutlej Basins, Himalayas
The dataset is the output of a statistical model which downscales ERA5 monthly precipitation data using gauge measurements from the Upper Beas and Sutlej Basins in the Western Himalayas. Multi-Fidelity Gaussian Processes (MFGPs) are used to generate more accurate precipitation values between 1980 and 2012, including over ungauged areas of the basins. MFGPs are a probabilistic machine learning method that provides principled uncertainty estimates via the prediction of probability distributions. These predictions can therefore be used to estimate the likelihood of extreme precipitation events which have led to droughts, floods, and landslides.
Funding from UK Engineering and Physical Sciences Research Council [grant number: 2270379].
Simple
- Date (Creation)
- 2023-08-09
- Date (Revision)
- 2023-08-09
- Date (Publication)
- 2023-08-09
- Date (released)
- 2023-08-09
- Edition
-
1.0
- Unique resource identifier
- https://doi.org/10.5285/b2099787-b57c-44ae-bf42-0d46d9ec87cc
- Codespace
-
doi
- Unique resource identifier
- GB/NERC/BAS/PDC/01769
- Codespace
- Other citation details
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Please cite this item as: Tazi, K. (2023). Downscaled ERA5 monthly precipitation data using Multi-Fidelity Gaussian Processes between 1980 and 2012 for the Upper Beas and Sutlej Basins, Himalayas (Version 1.0) [Data set]. NERC EDS UK Polar Data Centre. https://doi.org/10.5285/b2099787-b57c-44ae-bf42-0d46d9ec87cc
- Credit
-
No credit.
- Status
- Completed
- Point of contact
-
Organisation name Individual name Electronic mail address Role British Antarctic Survey Tazi, Kenza Author University of Cambridge Tazi, Kenza Author NERC EDS UK Polar Data Centre Point of contact
- Maintenance and update frequency
- As needed
- Maintenance note
- Completed
- Theme
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ERA5
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Himalayas
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downscaling
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machine learning
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precipitation
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- Place
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Upper Beas Basin, Himalayas Asia
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Upper Sutlej Basin, Himalayas Asia
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GEMET - INSPIRE themes, version 1.0
- 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
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Data supplied under Open Government Licence v3.0
- Use constraints
- Other restrictions
- Other constraints
-
No restrictions apply.
- 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
- Cross reference
- Spatial representation type
- Text, table
- Language
- English
- Character set
- UTF8
- Topic category
-
- Climatology, meteorology, atmosphere
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- Begin date
- 1980-01-01
- End date
- 2012-12-01
Vertical extent
- Minimum value
- 306.0
- Maximum value
- 6295.0
Vertical CS
Vertical datum
- 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
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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
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 Distributor
- Distributor format
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Name Version text/plain text/csv application/x-hdf application/netcdf
- Units of distribution
-
bytes
- Transfer size
- 234881024
- OnLine resource
-
Protocol Linkage Name WWW:LINK-1.0-http--link
https://ramadda.data.bas.ac.uk/repository/entry/show?entryid=b2099787-b57c-44ae-bf42-0d46d9ec87cc Get Data
- Units of distribution
-
bytes
- Transfer size
- 234881024
- OnLine resource
-
Protocol Linkage Name WWW:LINK-1.0-http--link
https://ramadda.data.bas.ac.uk/repository/entry/show?entryid=b2099787-b57c-44ae-bf42-0d46d9ec87cc Get Data
- Units of distribution
-
bytes
- Transfer size
- 234881024
- OnLine resource
-
Protocol Linkage Name WWW:LINK-1.0-http--link
https://ramadda.data.bas.ac.uk/repository/entry/show?entryid=b2099787-b57c-44ae-bf42-0d46d9ec87cc Get Data
- Units of distribution
-
bytes
- Transfer size
- 234881024
- OnLine resource
-
Protocol Linkage Name WWW:LINK-1.0-http--link
https://ramadda.data.bas.ac.uk/repository/entry/show?entryid=b2099787-b57c-44ae-bf42-0d46d9ec87cc Get Data
- Hierarchy level
- Dataset
- Statement
-
Methodology:
The MFGP model is trained using all stations data from Bannister et al. and ERA5 data over the study area (30 degrees North - 33.5 degrees North, 75.5 degrees East - 83 degrees East) between 1980 and 2012. The model takes as inputs time, latitude, longitude, and elevation. The raw model outputs the predictions at ERA5 and gauge fidelity levels in the form of normal distributions. The distributions need to be transformed to get the monthly precipitation values in mm/day. The dataset includes the raw mean and variance of the model output for both fidelity levels. The dataset also includes the transformed mean and upper and lower 95 percent confidence interval bounds for the high-fidelity output. This corresponds to the accurately downscaled data. The user can transform the data on their own via inverse Box-Cox transformations using the scaling factors separately provided.
Data collection:
Python v3.10
Data quality:
Data is a model output so should be complete. NaNs in the netCDF file correspond to locations outside of the study areas.
Metadata
- File identifier
- b2099787-b57c-44ae-bf42-0d46d9ec87cc XML
- Metadata language
- English
- Character set
- UTF8
- Hierarchy level
- Dataset
- Hierarchy level name
-
dataset
- Date stamp
- 2023-08-09
- 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 Point of contact
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