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Evaluating the performance of past climate model projections
- Publication Year :
- 2020
-
Abstract
- Author Posting. © American Geophysical Union, 2020. This article is posted here by permission of American Geophysical Union for personal use, not for redistribution. The definitive version was published in Geophysical Research Letters 47(1), (2020): e2019GL085378, doi:10.1029/2019GL085378.<br />Retrospectively comparing future model projections to observations provides a robust and independent test of model skill. Here we analyze the performance of climate models published between 1970 and 2007 in projecting future global mean surface temperature (GMST) changes. Models are compared to observations based on both the change in GMST over time and the change in GMST over the change in external forcing. The latter approach accounts for mismatches in model forcings, a potential source of error in model projections independent of the accuracy of model physics. We find that climate models published over the past five decades were skillful in predicting subsequent GMST changes, with most models examined showing warming consistent with observations, particularly when mismatches between model‐projected and observationally estimated forcings were taken into account.<br />Z. H. conceived the project, Z. H. and H. F. D. created the figures, and Z. H., H. F. D., T. A., and G. S. helped gather data and wrote the article text. A public GitHub repository with code used to analyze the data and generate figures and csv files containing the data shown in the figures is available online (https://github.com/hausfath/OldModels). Additional information on the code and data used in the analysis can be found in the supporting information. We would like to thank Piers Forster for providing the ensemble of observationally‐informed radiative forcing estimates. No dedicated funding from any of the authors supported this project.<br />2020-06-04
Details
- Database :
- OAIster
- Publication Type :
- Electronic Resource
- Accession number :
- edsoai.on1195523683
- Document Type :
- Electronic Resource