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CAMELS Extended Maurer Forcing Data


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Type: Resource
Storage: The size of this resource is 120.6 MB
Created: Jul 18, 2019 at 11:15 a.m.
Last updated: Dec 17, 2019 at 8:34 a.m.
DOI: 10.4211/hs.17c896843cf940339c3c3496d0c1c077
Citation: See how to cite this resource
Sharing Status: Published
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Abstract

This repository contains drop-in replacements for the basin mean Maurer forcing data files of the CAMELS data set. Compared to the original files contained in the CAMELS data set, these files contain daily minimum and maximum temperature. In the original publications both of those variables contained the daily mean temperature. These files were generated for our HESS manuscript "Towards learning universal, regional, and local hydrological behaviors via machine learning applied to large-sample datasets" and will be merged into the official CAMELS data set in the next update.
The same TERMS OF USE apply as for the original CAMELS data set.

Subject Keywords

Coverage

Spatial

Coordinate System/Geographic Projection:
WGS 84 EPSG:4326
Coordinate Units:
Decimal degrees
North Latitude
50.3568°
East Longitude
-59.0856°
South Latitude
24.7829°
West Longitude
-130.1012°

Content

README.md

Updated Maurer forcing data

This repository contains drop-in replacements for the basin mean Maurer forcing data files of the CAMELS data set. Compared to the original files contained in the CAMELS data set, these files contain daily minimum and maximum temperature. In the original publications both of those variables contained the daily mean temperature. These files were generated for our HESS manuscript "Towards learning universal, regional, and local hydrological behaviors via machine learning applied to large-sample datasets" and will be merged into the official CAMELS data set in the next update.

License / Terms of use

The same terms of use as of the original CAMELS data set apply here.

Contact

  • Frederik Kratzert (kratzert@ml.jku.at)

  • Andrew Newman (anewman@ucar.edu)

Related Resources

This resource is described by A. J. Newman, M. P. Clark, K. Sampson, A. Wood, L. E. Hay, A. Bock, R. J. Viger, D. Blodgett, L. Brekke, J. R. Arnold, T. Hopson, and Q. Duan: Development of a large-sample watershed-scale hydrometeorological dataset for the contiguous USA: dataset characteristics and assessment of regional variability in hydrologic model performance. Hydrol. Earth Syst. Sci., 19, 209-223, doi:10.5194/hess-19-209-2015, 2015
This resource is referenced by Kratzert, F., Klotz, D., Shalev, G., Klambauer, G., Hochreiter S., and Nearing, G.: Towards learning universal, regional, and local hydrological behaviors via machine learning applied to large-sample datasets, Hydrol. Earth Syst. Sci., 2019.

How to Cite

Kratzert, F. (2019). CAMELS Extended Maurer Forcing Data, HydroShare, https://doi.org/10.4211/hs.17c896843cf940339c3c3496d0c1c077

This resource is shared under the Creative Commons Attribution CC BY.

http://creativecommons.org/licenses/by/4.0/
CC-BY

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