Process Oriented Diagnostics of Tropical Cyclones in Climate Models

The simulation of tropical cyclone (TC) activity in climate models is still a challenging problem. While some models are able to simulate TC activity with characteristics very similar to those observed, many models have very strong biases. While increasing horizontal resolution often improves the characteristics of model TCs, resolution alone is not sufficient for high skill in simulating TC activity. We use process-based diagnostics to identify model characteristics that are responsible for a good simulation of TCs in global atmospheric and ocean-atmosphere coupled climate models.

First, we will examine the relationship of large-scale environmental variables, such as vertical wind shear and potential intensity as well as various integrated genesis indices, to standard TC activity measures. Then we will test process-based diagnostics to investigate the mechanisms of TC formation in climate models, in particular, the influence of model physics. The first type of diagnostics focus on how convection, moisture, clouds and related processes are coupled at individual grid points, and give information about how the convective parameterizations interact with resolved model dynamics. These diagnostics are strongly-based on diagnostics originally used to analyze the Madden-Julian Oscillation in climate models. The second type of diagnostics focuses on moisture-convection-radiation feedbacks and was originally developed to study the mechanisms of tropical convective organization. We will apply these diagnostics to explore the TC activity in four high-resolution climate models.