A Comparison of Tropical Cyclone Projections in a High-Resolution Global Climate Model and from Downscaling by Statistical and Statistical-Deterministic Methods

In this study, we investigate the response of tropical cyclones (TCs) to climate change by using the Princeton environment-dependent probabilistic tropical cyclone (PepC) model and a statistical-deterministic method to downscale TCs using environmental conditions obtained from the Geophysical Fluid Dynamics Laboratory (GFDL) High-Resolution Forecast-Oriented Low Ocean Resolution (HiFLOR) model, under the representative concentration pathway 4.5 (RCP4.5) emissions scenario for the North Atlantic Ocean basin. The downscaled TCs for the historical climate (1986-2005) are compared with those in the middle (2016-35) and late twenty-first century (2081-2100). The downscaled TCs are also compared with TCs explicitly simulated in HiFLOR. We show that, while significantly more storms are detected in HiFLOR toward the end of the twenty-first century, the statistical-deterministic model projects a moderate increase in TC frequency and PepC projects almost no increase in TC frequency. The changes in storm frequency in all three datasets are not significant in the mid-twenty-first century. All three project that storms will become more intense and the fraction of major hurricanes and category-5 storms will significantly increase in the future climates. However, HiFLOR projects the largest increase in intensity, and PepC projects the least. The results indicate that HiFLOR's TC projection is more sensitive to climate change effects and that statistical models are less sensitive. Nevertheless, in all three datasets, storm intensification and frequency increase lead to relatively small changes in TC threat as measured by the return level of landfall intensity under the projected climate condition.

Automated summary

The study investigates the response of tropical cyclones to climate change using different models and methods. Results show that there will be an increase in intensity and frequency of storms in the future, with different models showing varying degrees of sensitivity to climate change effects.