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

Oueslati, Boutheina; Bellon, Gilles

doi:10.1007/s00382-015-2468-6

Cited by 151 publications

(122 citation statements)

References 44 publications

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“…Biases commonly found in the simulated mean precipitation from CMIP5 models include too little precipitation along the Equator in the western Pacific associated with oceanatmosphere feedbacks (Collins et al, 2010) and too-high precipitation amounts in the tropics south of the Equator related to an unrealistic double ITCZ in many models, particularly in the Pacific (Oueslati and Bellon, 2015). Figure 2 shows the biases in annual mean precipitation averaged over the 20-year period 1986-2005 from the CMIP5 and EMBRACE simulations compared with data from the Global Precipitation Climatology Project (GPCP; Adler et al, 2003).…”

Section: Total Precipitationmentioning

confidence: 99%

Process-level improvements in CMIP5 models and their impact on tropical variability, the Southern Ocean, and monsoons

et al. 2018

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Abstract. The performance of updated versions of the four earth system models (ESMs) CNRM, EC-Earth, HadGEM, and MPI-ESM is assessed in comparison to their predecessor versions used in Phase 5 of the Coupled Model Intercomparison Project. The Earth System Model Evaluation Tool (ESMValTool) is applied to evaluate selected climate phenomena in the models against observations. This is the first systematic application of the ESMValTool to assess and document the progress made during an extensive model development and improvement project. This study focuses on the South Asian monsoon (SAM) and the West African monsoon (WAM), the coupled equatorial climate, and Southern Ocean clouds and radiation, which are known to exhibit systematic biases in present-day ESMs.The analysis shows that the tropical precipitation in three out of four models is clearly improved. Two of three updated coupled models show an improved representation of tropical sea surface temperatures with one coupled model not exhibiting a double Intertropical Convergence Zone (ITCZ). Simulated cloud amounts and cloudradiation interactions are improved over the Southern Ocean. Improvements are also seen in the simulation of the SAM and WAM, although systematic biases remain in regional details and the timing of monsoon rainfall. Analysis of simulations with EC-Earth at different horizontal resolutions from T159 up to T1279 shows that the synoptic-scale variability in precipitation over the SAM and WAM regions improves with higher model resolution. The results suggest that the reasonably good agreement of modeled and observed mean WAM and SAM rainfall in lower-resolution models may be a result of unrealistic intensity distributions.

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Section: Total Precipitationmentioning

confidence: 99%

Process-level improvements in CMIP5 models and their impact on tropical variability, the Southern Ocean, and monsoons

et al. 2018

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“…First, it provides remarkably little leverage in improving overall model skill once a reasonable part of parameter space has been identified -for instance, tuning has been unable to resolve the persistent so-called "double ITCZ" problem (Lin, 2007;Oueslati and Bellon, 2015). Second, improvements in one field are often accompanied by degradation in others, and thus the final choice of parameters involves subjective judgments about the relative importance of different aspects of the simulations.…”

Section: Why Is Climate Model Tuning Necessary?mentioning

confidence: 99%

Practice and philosophy of climate model tuning across six US modeling centers

et al. 2017

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Abstract. Model calibration (or "tuning") is a necessary part of developing and testing coupled ocean-atmosphere climate models regardless of their main scientific purpose. There is an increasing recognition that this process needs to become more transparent for both users of climate model output and other developers. Knowing how and why climate models are tuned and which targets are used is essential to avoiding possible misattributions of skillful predictions to data accommodation and vice versa. This paper describes the approach and practice of model tuning for the six major US climate modeling centers. While details differ among groups in terms of scientific missions, tuning targets, and tunable parameters, there is a core commonality of approaches. However, practices differ significantly on some key aspects, in particular, in the use of initialized forecast analyses as a tool, the explicit use of the historical transient record, and the use of the present-day radiative imbalance vs. the implied balance in the preindustrial era as a target.

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“…On a global scale, important work has been done to investigate model representation of clouds and water vapor (e.g., Jiang et al 2012;Klein et al 2013), tropical circulation (e.g., Niznik and Lintner 2013;Oueslati and Bellon 2015), and modes of variability (e.g., Guilyardi et al 2009;Kim et al 2009). This process-oriented evaluation is fundamental to inform model development.…”

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confidence: 99%