Abstract
A global atmospheric model with roughly 50-km horizontal grid spacing is used to simulate the interannual variability of tropical cyclones using observed sea surface temperatures (SSTs) as the lower boundary condition. The model’s convective parameterization is based on a closure for shallow convection, with much of the deep convection allowed to occur on resolved scales. Four realizations of the period 1981–2005 are generated. The correlation of yearly Atlantic hurricane counts with observations is greater than 0.8 when the model is averaged over the four realizations, supporting the view that the random part of this annual Atlantic hurricane frequency (the part not predictable given the SSTs) is relatively small (<2 hurricanes per year). Correlations with observations are lower in the east, west, and South Pacific (roughly 0.6, 0.5, and 0.3, respectively) and insignificant in the Indian Ocean. The model trends in Northern Hemisphere basin-wide frequency are consistent with the observed trends in the International Best Track Archive for Climate Stewardship (IBTrACS) database. The model generates an upward trend of hurricane frequency in the Atlantic and downward trends in the east and west Pacific over this time frame. The model produces a negative trend in the Southern Hemisphere that is larger than that in the IBTrACS.
The same model is used to simulate the response to the SST anomalies generated by coupled models in the World Climate Research Program Coupled Model Intercomparison Project 3 (CMIP3) archive, using the late-twenty-first century in the A1B scenario. Results are presented for SST anomalies computed by averaging over 18 CMIP3 models and from individual realizations from 3 models. A modest reduction of global and Southern Hemisphere tropical cyclone frequency is obtained in each case, but the results in individual Northern Hemisphere basins differ among the models. The vertical shear in the Atlantic Main Development Region (MDR) and the difference between the MDR SST and the tropical mean SST are well correlated with the model’s Atlantic storm frequency, both for interannual variability and for the intermodel spread in global warming projections.
Corresponding author address: Dr. Ming Zhao, NOAA/Geophysical Fluid Dynamics Laboratory, Princeton University, Forrestal Campus/U.S. Route 1, P.O. Box 308, Princeton, NJ 08542. Email: ming.zhao@noaa.gov