Articles | Volume 10, issue 5
https://doi.org/10.5194/gmd-10-1889-2017
© 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/gmd-10-1889-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Methods for assessment of models
| 
12 May 2017
Methods for assessment of models |
| 12 May 2017
Exploring precipitation pattern scaling methodologies and robustness among CMIP5 models
Atmospheric Sciences and Global Change Division, Pacific Northwest National Laboratory, Richland, WA, USA
Cary Lynch
Joint Global Change Research Institute, Pacific Northwest National Laboratory, College Park, MD, USA
Corinne Hartin
Joint Global Change Research Institute, Pacific Northwest National Laboratory, College Park, MD, USA
Ben Bond-Lamberty
Joint Global Change Research Institute, Pacific Northwest National Laboratory, College Park, MD, USA
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- Using high-resolution climate change information in water management: a decision-makers' perspective H. Orr et al. 10.1098/rsta.2020.0219
- Does integrating climate change projection with agriculture policy improve agricultural adaptation and food security? Evidence from Bangladesh Z. Ahmed et al. 10.1007/s00704-023-04643-6
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Latest update: 12 May 2025
Short summary
Pattern scaling is a way of approximating regional changes without needing to run a full, complex global climate model. We compare two methods of pattern scaling for precipitation and evaluate which methods is
betterin particular circumstances. We also decompose precipitation into a CO2 portion and a non-CO2 portion. The methodologies discussed in this paper can help provide precipitation fields for other models for a wide variety of scenarios of future climate change.
Pattern scaling is a way of approximating regional changes without needing to run a full,...
