Abstract
Time–frequency localization of model-data discrepancies may provide useful information for climate models inter-comparison, and especially for the goals of climate model refinement and improvement. CMIP5 models of the long-term historical (1850–2005) run experiment are compared using wavelet-based multiscale descriptive and diagnostic techniques with interesting results. Wavelet coherence maps can visualize the ability of alternative CMPI5 models to capture the observed climate variability at different time scales, while the performance of each CMIP5 model is assessed using goodness of fit relative measures on a scale-by-scale basis. Finally, the plots of wavelet decompositions of CMIP5 models and observed temperature series at different scales can detect and locate model/data disagreements across frequencies and over time, thus providing useful information to researchers for model diagnostic refinement and improvement.
Highlights
The Coupled Model Intercomparison Project (CMIP) makes available to climate scientists a coordinated multi-model experiment that provides simulations of historical climate variability and change (Meehl and Coauthors 2007, Taylor et al, 2012)
This paper evaluates the performance of CMIP5 climate model simulations using wavelet coherence maps and scale-based goodness of fit relative measures, such as the root mean square error (RMSE)
Exploratory diagnostic graphical analysis suggests the existence of recurrent model-dataagreements at different scales of variability, high coherence at lower frequencies
Summary
The Coupled Model Intercomparison Project (CMIP) makes available to climate scientists a coordinated multi-model experiment that provides simulations of historical climate variability and change (Meehl and Coauthors 2007, Taylor et al, 2012). CMIP5 model simulations are able to reproduce the observed trend in the global-scale surface temperature. CMIP5 climate models are able to reproduce the observed warming observed over the last 150 years and the other recent climate changes. Large inter-model spreads relative to the model mean change and systematic errors are still evident, as well as differences between simulated and
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