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Title: ENSO Simulation in Coupled Ocean-Atmosphere Models: Are the Current Models Better?

Journal Article · · Climate Dynamics
OSTI ID:883752

Maintaining a multi-model database over a generation or more of model development provides an important framework for assessing model improvement. Using control integrations, we compare the simulation of the El Nino/Southern Oscillation (ENSO), and its extratropical impact, in models developed for the 2007 Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report with models developed in the late 1990's (the so-called Coupled Model Intercomparison Project-2 [CMIP2] models). The IPCC models tend to be more realistic in representing the frequency with which ENSO occurs, and they are better at locating enhanced temperature variability over the eastern Pacific Ocean. When compared with reanalyses, the IPCC models have larger pattern correlations of tropical surface air temperature than do the CMIP2 models during the boreal winter peak phase of El Nino. However, for sea-level pressure and precipitation rate anomalies, a clear separation in performance between the two vintages of models is not as apparent. The strongest improvement occurs for the modeling groups whose CMIP2 model tended to have the lowest pattern correlations with observations. This has been checked by subsampling the multi-century IPCC simulations in a manner to be consistent with the single 80-year time segment available from CMIP2. Our results suggest that multi-century integrations may be required to statistically assess model improvement of ENSO. The quality of the El Nino precipitation composite is directly related to the fidelity of the boreal winter precipitation climatology, highlighting the importance of reducing systematic model error. Over North America distinct improvement of El Nino forced boreal winter surface air temperature, sea-level pressure, and precipitation rate anomalies in the IPCC models occurs. This improvement, is directly proportional to the skill of the tropical El Nino forced precipitation anomalies.

Research Organization:
Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)
Sponsoring Organization:
USDOE
DOE Contract Number:
W-7405-ENG-48
OSTI ID:
883752
Report Number(s):
UCRL-JRNL-211903; CLDYEM; TRN: US200615%%213
Journal Information:
Climate Dynamics, Vol. 27, Issue 1; ISSN 0930-7575
Country of Publication:
United States
Language:
English

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