Modeling and Predicting Global Climate Variability and Climate Change

The scale and complexity of the climate system have rendered computer models an indispensible tool in our effort to understand and predict the behavior of the climate system. The ultimate test of our understanding of the working of the climate system is how well our models simulate and predict the behavior of the climate system. Our efforts in helping to build better and better models are currently focused on diagnosing the causes of outstanding biases in the state-of-the-art climate models--Coupled General Circulation Models (CGCMs) (or Climate System Models). We are currently working with modelers at NCAR, GFDL, and NASA, attempting to understand the causes of outstanding tropical biases in CGCMs. A problem of a paticular interest to us is the excessive cold-tongue and the associated double ITCZ syndrome in the climate models. We are also particularly concerned with the fidelity of the models in simulating ENSO--its diabatic and nonlinear aspects in particular. Relatedly, we are also interested in assessing whether the coupled tropical Pacific system or the other regional systems or the climate system as a whole as represented in the climate models is in the same dynamic regime as in observations. As few processes are not coupled, key to diagnosing the causes of biases in climate simulations by CGCMs is to evaluate the various feedbacks in the models and understand the climatic roles of feedbacks. A precise knowledge of the major feedbacks in the climate system, such as the feedbacks of water vapor and clouds, is also necessary for understanding the causes of the observed climate change and for predicting future climate. In addition to helping with the improvement of climate models that are primarily used for climate simulation and projection, we are also working with modelers and forecasters at NCEP in improving the interannual and decadal forecasts through the use of NCEP Climate Forecast System (CFS)