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Consistency of simulated and observed regional changes in temperature, sea level pressure and precipitation

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  • J. Bhend
  • P. Whetton

Abstract

There is increasing pressure from stakeholders for highly localised climate change projections. A comprehensive assessment of climate model performance at the grid box scale in simulating recent change, however, is not available at present. Therefore, we compare observed changes in near-surface temperature, sea level pressure (SLP) and precipitation with simulations available from the Coupled Model Intercomparison Projects 3 and 5 (CMIP3 and CMIP5). In both multi-model datasets we find coherent areas of inconsistency between observed and simulated local trends per degree global warming in both temperature and SLP in the majority of models. Localised projections should thus take into account the possibility of regional biases shared across models. In contrast, simulated changes in precipitation are not significantly different from observations due to low signal-to-noise ratio of local precipitation changes. Therefore, recent regional rainfall change is likely not providing useful constraints for future projections as of yet. Comparing the two most recent sets of internationally coordinated climate model experiments, we find no indication of improvement in the models’ ability to reproduce local trends in temperature, SLP and precipitation. Copyright Springer Science+Business Media Dordrecht 2013

Suggested Citation

  • J. Bhend & P. Whetton, 2013. "Consistency of simulated and observed regional changes in temperature, sea level pressure and precipitation," Climatic Change, Springer, vol. 118(3), pages 799-810, June.
    • Handle: RePEc:spr:climat:v:118:y:2013:i:3:p:799-810
    DOI: 10.1007/s10584-012-0691-2
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    References listed on IDEAS

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    1. Xuebin Zhang & Francis W. Zwiers & Gabriele C. Hegerl & F. Hugo Lambert & Nathan P. Gillett & Susan Solomon & Peter A. Stott & Toru Nozawa, 2007. "Detection of human influence on twentieth-century precipitation trends," Nature, Nature, vol. 448(7152), pages 461-465, July.
    2. Jun, Mikyoung & Knutti, Reto & Nychka, Douglas W, 2008. "Spatial Analysis to Quantify Numerical Model Bias and Dependence," Journal of the American Statistical Association, American Statistical Association, vol. 103(483), pages 934-947.
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