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PCMDI > WCRP CMIP3 Model Output > Diagnostic Subprojects Printer Friendly Version
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  • Wang M., J.E. Overland, V. Kattsov, J.E. Walsh, X. Zhang, T. Pavlova, 2007: ntrinsic versus forced variation in coupled climate model simulations over the Arctic during the 20th Century. Journal of Climate, 20, 1084-1098.

There were two major multi-year, Arctic-wide (60-90N) warm anomalies (> 0.7C) in land surface air temperature (LSAT) during the 20th century, between 1920-1950 and again at the end of the century after 1979. Reproducing this decadal and longer variability in coupled General Circulation Models (GCMs) is a critical test for understanding processes in the Arctic climate system and increasing the confidence in the IPCC model projections. Our study evaluated 63 realizations generated by 20 coupled GCMs made available for the IPCC 4th Assessment for their 20th century simulations (20C3M) and corresponding control runs (PIcntrl). Warm anomalies in the Arctic during the last two decades are reproduced by all ensemble members, with considerable variability in amplitude among models. In contrast only eight models generated warm anomaly amplitude at least 2/3 of the observed mid-century warm event in at least one realization, but not its timing. The durations of the mid-century warm events in all the models are decadal, while that of the observed was interdecadal. The variance of the control runs in nine models was comparable with the variance in the observations. The random timing of mid-century warm anomalies in 20C3M simulations and the similar variance of the control runs in about half of the models suggest that the observed mid-century warm period is consistent with intrinsic climate variability. Five models were considered to compare somewhat favorably to Arctic observations in matching both the variance of the observed temperature record in their control runs and representing the decadal mean temperature anomaly amplitude in their 20C3M simulations. Seven additional models could be given further consideration. Our results support selecting a subset of GCMs when making predictions for future climate by using performance criteria based on comparison with retrospective data.

Last Updated: 2007-08-13

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