Articles | Volume 13, issue 8
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

Related authors

An overview of the E3SM version 2 large ensemble and comparison to other E3SM and CESM large ensembles
John T. Fasullo, Jean-Christophe Golaz, Julie M. Caron, Nan Rosenbloom, Gerald A. Meehl, Warren Strand, Sasha Glanville, Samantha Stevenson, Maria Molina, Christine A. Shields, Chengzhu Zhang, James Benedict, Hailong Wang, and Tony Bartoletti
Earth Syst. Dynam., 15, 367–386,,, 2024
Short summary
New model ensemble reveals how forcing uncertainty and model structure alter climate simulated across CMIP generations of the Community Earth System Model
Marika M. Holland, Cecile Hannay, John Fasullo, Alexandra Jahn, Jennifer E. Kay, Michael Mills, Isla R. Simpson, William Wieder, Peter Lawrence, Erik Kluzek, and David Bailey
Geosci. Model Dev., 17, 1585–1602,,, 2024
Short summary
Dependence of strategic solar climate intervention on background scenario and model physics
John T. Fasullo and Jadwiga H. Richter
Atmos. Chem. Phys., 23, 163–182,,, 2023
Short summary

Related subject area

Climate and Earth system modeling
Implementing detailed nucleation predictions in the Earth system model EC-Earth3.3.4: sulfuric acid–ammonia nucleation
Carl Svenhag, Moa K. Sporre, Tinja Olenius, Daniel Yazgi, Sara M. Blichner, Lars P. Nieradzik, and Pontus Roldin
Geosci. Model Dev., 17, 4923–4942,,, 2024
Short summary
Modeling biochar effects on soil organic carbon on croplands in a microbial decomposition model (MIMICS-BC_v1.0)
Mengjie Han, Qing Zhao, Xili Wang, Ying-Ping Wang, Philippe Ciais, Haicheng Zhang, Daniel S. Goll, Lei Zhu, Zhe Zhao, Zhixuan Guo, Chen Wang, Wei Zhuang, Fengchang Wu, and Wei Li
Geosci. Model Dev., 17, 4871–4890,,, 2024
Short summary
Hector V3.2.0: functionality and performance of a reduced-complexity climate model
Kalyn Dorheim, Skylar Gering, Robert Gieseke, Corinne Hartin, Leeya Pressburger, Alexey N. Shiklomanov, Steven J. Smith, Claudia Tebaldi, Dawn L. Woodard, and Ben Bond-Lamberty
Geosci. Model Dev., 17, 4855–4869,,, 2024
Short summary
Evaluation of CMIP6 model simulations of PM2.5 and its components over China
Fangxuan Ren, Jintai Lin, Chenghao Xu, Jamiu A. Adeniran, Jingxu Wang, Randall V. Martin, Aaron van Donkelaar, Melanie S. Hammer, Larry W. Horowitz, Steven T. Turnock, Naga Oshima, Jie Zhang, Susanne Bauer, Kostas Tsigaridis, Øyvind Seland, Pierre Nabat, David Neubauer, Gary Strand, Twan van Noije, Philippe Le Sager, and Toshihiko Takemura
Geosci. Model Dev., 17, 4821–4836,,, 2024
Short summary
Assessment of a tiling energy budget approach in a land surface model, ORCHIDEE-MICT (r8205)
Yi Xi, Chunjing Qiu, Yuan Zhang, Dan Zhu, Shushi Peng, Gustaf Hugelius, Jinfeng Chang, Elodie Salmon, and Philippe Ciais
Geosci. Model Dev., 17, 4727–4754,,, 2024
Short summary

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,, 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,, 2019. 
Box, G. E. P.: Science and statistics, J. Am. Stat. Assoc., 71, 791–799,, 1976. 
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.