Journal cover Journal topic
Geoscientific Model Development An interactive open-access journal of the European Geosciences Union
Geosci. Model Dev., 10, 1889-1902, 2017
http://www.geosci-model-dev.net/10/1889/2017/
doi:10.5194/gmd-10-1889-2017
© Author(s) 2017. This work is distributed
under the Creative Commons Attribution 3.0 License.
Methods for assessment of models
12 May 2017
Exploring precipitation pattern scaling methodologies and robustness among CMIP5 models
Ben Kravitz1, Cary Lynch2, Corinne Hartin2, and Ben Bond-Lamberty2 1Atmospheric Sciences and Global Change Division, Pacific Northwest National Laboratory, Richland, WA, USA
2Joint Global Change Research Institute, Pacific Northwest National Laboratory, College Park, MD, USA
Abstract. Pattern scaling is a well-established method for approximating modeled spatial distributions of changes in temperature by assuming a time-invariant pattern that scales with changes in global mean temperature. We compare two methods of pattern scaling for annual mean precipitation (regression and epoch difference) and evaluate which method is better in particular circumstances by quantifying their robustness to interpolation/extrapolation in time, inter-model variations, and inter-scenario variations. Both the regression and epoch-difference methods (the two most commonly used methods of pattern scaling) have good absolute performance in reconstructing the climate model output, measured as an area-weighted root mean square error. We decompose the precipitation response in the RCP8.5 scenario into a CO2 portion and a non-CO2 portion. Extrapolating RCP8.5 patterns to reconstruct precipitation change in the RCP2.6 scenario results in large errors due to violations of pattern scaling assumptions when this CO2-/non-CO2-forcing decomposition is applied. The methodologies discussed in this paper can help provide precipitation fields to be utilized in other models (including integrated assessment models or impacts assessment models) for a wide variety of scenarios of future climate change.

Citation: Kravitz, B., Lynch, C., Hartin, C., and Bond-Lamberty, B.: Exploring precipitation pattern scaling methodologies and robustness among CMIP5 models, Geosci. Model Dev., 10, 1889-1902, doi:10.5194/gmd-10-1889-2017, 2017.
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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 better in 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,...
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