Articles | Volume 13, issue 8
https://doi.org/10.5194/gmd-13-3627-2020
https://doi.org/10.5194/gmd-13-3627-2020
Methods for assessment of models
 | 
21 Aug 2020
Methods for assessment of models |  | 21 Aug 2020

Evaluating simulated climate patterns from the CMIP archives using satellite and reanalysis datasets using the Climate Model Assessment Tool (CMATv1)

John T. Fasullo

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Cited articles

Adler, R., Sapiano, M., Huffman, G., Bolvin, D., Gu, G., Wang, J., and Schneider, U.: The new version 2.3 of the Global Precipitation Climatology Project (GPCP) monthly analysis product, University of Maryland, April, pp. 1072–1084, 2016. 
Adler, R. F., Gu, G., Huffman, G. J., Sapiano, M. R., and Wang, J. J.: GPCP and the Global Characteristics of Precipitation, in: Satellite Precipitation Measurement, pp. 677–697, Springer, Cham, 2020. 
Baker, N. C. and Taylor, P. C.: A framework for evaluating climate model performance metrics, J. Climate, 29, 1773–1782, https://doi.org/10.1175/JCLI-D-15-0114.1, 2016. 
Borovikov, A., Cullather, R., Kovach, R., Marshak, J., Vernieres, G., Vikhliaev, Y., and Li, Z.: GEOS-5 seasonal forecast system, Clim. Dynam., 53, 7335–7361, https://doi.org/10.1007/s00382-017-3835-2, 2019. 
Box, G. E. P.: Science and statistics, J. Am. Stat. Assoc., 71, 791–799, https://doi.org/10.1080/01621459.1976.10480949, 1976. 
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Short summary
The fidelity of climate model simulations included in the WCRP Coupled Model Intercomparison Project Versions 3 through 6 is evaluated using best estimates of fields considered by the community to be critical for climate change projections. The analysis benchmarks patterns of the mean state and variability (seasonal/interannual) both within and across model generations, highlighting progress and quantifying persisting biases across models.
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