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The double ITCZ bias in CMIP5 models: interaction between SST, large-scale circulation and precipitation
The double ITCZ bias in CMIP5 models: interaction between SST, large-scale circulation and precipitation
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The double ITCZ bias in CMIP5 models: interaction between SST, large-scale circulation and precipitation
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The double ITCZ bias in CMIP5 models: interaction between SST, large-scale circulation and precipitation
The double ITCZ bias in CMIP5 models: interaction between SST, large-scale circulation and precipitation

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The double ITCZ bias in CMIP5 models: interaction between SST, large-scale circulation and precipitation
The double ITCZ bias in CMIP5 models: interaction between SST, large-scale circulation and precipitation
Journal Article

The double ITCZ bias in CMIP5 models: interaction between SST, large-scale circulation and precipitation

2015
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Overview
The double intertropical convergence zone (ITCZ) bias still affects all the models that participate to CMIP5 (Coupled Model Intercomparison Project, phase 5). As an ensemble, general circulation models have improved little between CMIP3 and CMIP5 as far as the double ITCZ is concerned. The present study proposes a new process-oriented metrics that provides a robust statistical relationship between atmospheric processes and the double ITCZ bias, additionally to the existing relationship between the sea surface temperature (SST) and the double ITCZ bias. The SST contribution is examined using the THR-MLT index (Bellucci et al. in J Clim 5:1127–1145, 2010 ), which combines biases on the representation of local SSTs and the SST threshold leading to the onset of ascent in the double ITCZ region. As a metrics of a model’s bias in simulating the interaction between circulation and precipitation, we propose to use the Combined Precipitation Circulation Error (CPCE). It is computed as the quadratic error on the contribution of each vertical regime to the total precipitation over the tropical oceans. CPCE is a global measure of the circulation-precipitation coupling that characterizes the model physical parameterizations rather than the regional characteristics of the eastern Pacific. A linear regression analysis shows that most of the double ITCZ spread among CMIP5 coupled ocean–atmosphere models is attributed to SST biases, and that the precipitation large-scale dynamics relationship explains a significant fraction of the bias in these models, as well as in the atmosphere-only models.