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the claim

Studies compare different climate models on their historical forecasting accuracy

the verdict
SUPPORTED
the evidence backs this
Recorded sources
4 sources for · 0 against

Counts group repeated records of the same source within each side. They do not measure evidence strength or source independence.

Is it true that studies compare different climate models on their historical forecasting accuracy?

Yes. Multiple studies evaluate and compare the historical forecasting and hindcasting accuracy of various climate models.

Verdict: SUPPORTED · 4 sources for, 0 against · Last checked

The analysis

The claim asserts that studies compare different climate models on their historical forecasting accuracy. Multiple papers in the provided set (e.g., papers 1, 3, 4, 9) explicitly perform hindcast experiments and evaluate the historical predictive skill of different climate models or model ensembles (such as CMIP generations and various Earth System Models). There are no refuting papers. Therefore, the verdict is SUPPORTED.

Evidence for · 4
Evaluation of forecasts by accuracy and spread in the MiKlip decadal climate prediction system
2016
Evaluates temperature and precipitation forecasts from the MiKlip decadal climate prediction system using historical hindcast experiments.
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Kadow, C., Illing, S., Kunst, O., Rust, H., Pohlmann, H., Müller, W., & Cubasch, U. (2016). Evaluation of forecasts by accuracy and spread in the MiKlip decadal climate prediction system. doi.org. https://doi.org/10.1127/METZ/2015/0639

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More for · 3
Initialized near-term regional climate change prediction.
2013
Examines near-term climate predictions from Coupled Model Intercomparison Project experiments, verifying model skill against historical observations over the past 50 years.
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FJ, D., I, A., Y, C., J, G., V, G., M, K., T, M., LR, R., & GJ, v. O. (2013). Initialized near-term regional climate change prediction.. doi.org. https://doi.org/10.1038/ncomms2704

The hindcast skill of the CMIP ensembles for the surface air temperature trend
2012
Evaluates linear trends of surface air temperature simulated by historical CMIP3 and CMIP5 climate model ensembles against observations.
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Sakaguchi, K., Zeng, X., & Brunke, M. A. (2012). The hindcast skill of the CMIP ensembles for the surface air temperature trend. doi.org. https://doi.org/10.1029/2012jd017765

Predictability of phases and magnitudes of natural decadal climate variability phenomena in CMIP5 experiments with the UKMO HadCM3, GFDL-CM2.1, NCAR-CCSM4, and MIROC5 global earth system models.
2019
Assesses the hindcasting ability of multiple global earth system models (HadCM3, GFDL-CM2.1, NCAR-CCSM4, MIROC5) regarding natural decadal climate variability phenomena.
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VM, M., K, M., & H, W. (2019). Predictability of phases and magnitudes of natural decadal climate variability phenomena in CMIP5 experiments with the UKMO HadCM3, GFDL-CM2.1, NCAR-CCSM4, and MIROC5 global earth system models.. doi.org. https://doi.org/10.1007/s00382-018-4321-1

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Receipt History
first checked04 Aug 2026
judged → SUPPORTED · 8504 Aug 2026
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