Coupled Climate System Modeling

Dear Colleagues,

Numerical modeling is an essential tool for understanding and predicting the complex climate system. The timescales of modeling range from day to millennia due to the intrinsic nature of each component of the climate system, including atmosphere, ocean, land, sea ice, among others. Although the capabilities of numerical modeling have advanced by leaps and bounds over the past few decades, large uncertainties can still be found in results derived from the coupled climate models due to the complexity of the climate system. Thus, it is a huge challenge to accurately reproduce the true nature using coupled climate models. Model development and evaluation is the first important task in the modeling community.

Coupled climate models can be used in the prediction and projection of the climate system. In the former aspect, coupled data assimilation techniques are developed in coupled climate models to provide accurate initial conditions of each component of the climate system, which can be beneficial to more precise predictions of various matters, from the daily weather forecast to decadal prediction. Another essential aspect of the usage of coupled climate models is to project future climate from a global spatial scale to a regional spatial scale. More than one hundred versions of climate/earth system models are participating a new phase of the Coupled Model Intercomparison Project (CMIP6). More analysis efforts should be dedicated using these outputs from multiple coupled models to understand how future climate would be, e.g., in the second half of this century.

Thus, this Special Issue focuses on the development, evaluation, and application of the coupled model of the complex climate system. Topics in this Special Issue include, but are not limited to:

• Development of the coupled climate/earth system model;
• Evaluation of the CMIP6 models and improvements from CMIP3 to CMIP6;
• Coupled model data assimilation technique;
• Short-term climate prediction using coupled model assimilation;
• Analysis of output from the Flux-Anomaly-Forced Model Intercomparison Project (FAFMIP);
• Ocean change in a warming background using coupled model simulations.

Dr. Xiao Dong
Dr. Jiangbo Jin
Dr. Hao Luo
Guest Editors

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