Hurricane Simulation Via Action Minimization

David Plotkin, University of Chicago

A postulated impact of climate change is an increase in intensity of tropical cyclones (TCs) owing to the fact that TCs are powered by the ocean mixed layer and a warmer ocean surface has more available energy. However, the fine convective structures (with length scales of less than 1 km) present in TCs have made prediction of changes in TC intensity difficult since general circulation models (GCMs) have horizontal resolutions of tens of kilometers. The models are therefore unable to capture these features, which are critical to accurately simulating cyclone structure and intensity. Further, TCs are rare events, meaning that long (e.g., many decades) simulations are necessary to generate meaningful statistics about TC activity. This adds to the computational expense. While there is progress towards GCM simulation at high enough resolution to predict TC changes, it is likely to remain infeasible for the foreseeable future.

We take an alternative approach, applying action minimization techniques developed in molecular dynamics to the WRF weather/climate model. We construct artificial model trajectories that lead from quiescent (TC-free) states to TC states, then minimize the deviation of these trajectories from true model dynamics. This allows for: 1) selective interrogation of model states with TCs; 2) finding the likeliest paths for transitions between TC-free and TC states; and 3) an increase in horizontal resolution due to computational savings achieved by reducing time spent simulating TC-free states. This increase in resolution, coupled with a decrease in simulation time, allows for prediction of the change in TC frequency and intensity distributions resulting from climate change.

Abstract Author(s): D. Plotkin, J. Weare, D. Abbot