Articles | Volume 9, issue 1
https://doi.org/10.5194/essd-9-281-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/essd-9-281-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Review article
| 
15 May 2017
Review article |
| 15 May 2017
An open-access CMIP5 pattern library for temperature and precipitation: description and methodology
Pacific Northwest National Laboratory, Joint Global Change Research Institute, 5825 University Research Court, Suite 3500, College Park, MD 20740, USA
Corinne Hartin
Pacific Northwest National Laboratory, Joint Global Change Research Institute, 5825 University Research Court, Suite 3500, College Park, MD 20740, USA
Ben Bond-Lamberty
Pacific Northwest National Laboratory, Joint Global Change Research Institute, 5825 University Research Court, Suite 3500, College Park, MD 20740, USA
Ben Kravitz
Atmospheric Sciences and Global Change Division, Pacific Northwest National Laboratory, 902 Battelle Boulevard, Richland, WA 99352, USA
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Total article views: 3,121 (including HTML, PDF, and XML)
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Latest update: 06 Jul 2025
Short summary
Pattern scaling climate model output is a computationally efficient way to produce a large amount of data for purposes of uncertainty quantification. Using a multi-model ensemble we explore pattern scaling methodologies across two future forcing scenarios. We find that the simple least squares approach to pattern scaling produces a close approximation of actual model output, and we use this as a justification for the creation of an open-access pattern library at multiple time increments.
Pattern scaling climate model output is a computationally efficient way to produce a large...
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