The tropical mean climate and tropical variability, such as the El Nino/Southern Oscillation (ENSO) and the Madden-Julian Oscillation (MJO), play a key role for weather predictions, climate predictions and climate projections. However, they are not well simulated by the state-of-the-art general circulation models (GCMs) used for predictions and projections, and the problems are generally referred to as the “tropical biases”. The most prominent tropical biases are the double-ITCZ problem, the ENSO problem, and the MJO problem.
These tropical biases have been persisting in the last several generations of GCMs. The major difficulties for understanding and alleviating these biases are twofold: (1) They all involve some forms of feedback, such as the ocean-atmosphere feedback and the wave-heating feedback, making it difficult to determine the real cause of the bias; and (2) The biases need to be traced back to specific model characteristics, such as certain aspect of the physical parameterizations, in order to provide useful guidance on how to improve the model simulations.
Multiple-model intercomparison, when combined with feedback
analysis and model physics evaluation, provide a good way to overcome
these difficulties. It can help us to understand the physical reasons
of the tropical biases, find systematic dependence of the biases on
specific model characteristics, and transfer the success of some of the
models to other more bias-challenged models. We will present the
results of several recent studies that include an analysis of the
physical mechanisms of the double-ITCZ problem in 22 IPCC AR4 coupled
GCMs; a newly discovered “coupled wave oscillator” mechanism of ENSO,
and its implications for the ENSO problem in coupled GCMs; and GCM
sensitivity experiments trying to improve the simulations of MJO and
convectively coupled equatorial waves.