Using High-Resolution Global Simulations to Study the Effects of Climate Change on the Spatiotemporal Characteristics of Tropical Cyclones

Prior research suggests that a warming climate could have a significant impact on tropical cyclone (TC) activity worldwide. There is agreement regarding potential decreases in TC frequency and increases in storm intensity in the future. However, there is a lack of consensus regarding future changes in TC seasonality or geographical activity. In the past, efforts to unravel these questions have been hindered by the coarse resolution of most global climate models (GCM).

The present study aims to quantify those spatiotemporal changes in TC activity over the Northern Hemisphere using high resolution, TC resolving model simulations. Present day and future climate simulations were performed using the Model for Prediction Across Scales (MPAS) for the Northern Hemisphere, all with 15 km grid spacing. There are ten present-climate simulations and ten “future climate” simulations which were altered to mimic the IPCC Representative Pathway Concentration (RCP) 8.5 scenario (with a corresponding CO2 increase in the model). Each of the twenty simulations is 14.5 months in duration, with the first 2.5 months eliminated as spin-up. The SST in each present-day simulation is based on reanalysis data, and for the corresponding future simulations, a GCM-derived “delta” is applied; the ten simulations span the ENSO parameter space. Tropical cyclones in the model simulations were tracked using the TempestExtremes algorithm (Ulrich and Zarzycki, 2016) to represent the present and future TC climatology.

Preliminary analysis of these results shows that the current MPAS simulations adequately capture observed environmental patterns and TC climatology year-round and across the Northern Hemisphere. Discrete changes in TC activity between current simulations and observations, like fewer storms in the North Atlantic Main Development Region (MDR) and over the Gulf of Mexico, were found to be linked to localized model biases in the environmental conditions that are favorable to cyclogenesis. Additional analysis into the future climate MPAS simulations will allow for a detailed understanding of how a warming climate may impact parameters like the times and locations of cyclogenesis, cyclolysis, and lifetime maximum intensity (LMI), along with changes to storm count, storm intensity, track density, average storm translation speeds, accumulated cyclonic energy (ACE) and general environmental conditions.