May 14th, 2012
North Atlantic tropical storms (TS) are a major climate hazard to North America, and have exhibited variability and change on decadal timescales. Therefore, understanding and predicting future decadal TS activity on decadal timescales is central to NOAA’s mission and highly relevant to society.
Prior studies have shown divergent results for projections of future North Atlantic TS frequency over the current century, with some model projections showing an increase, others a decrease, and others showing almost no change at all. Identifying the sources of this diversity of projected sensitivities is necessary to improve future model projections and manage climate risks associated with tropical storms.
We use a novel statistical tropical storm frequency model developed in collaboration with Princeton University’s Civil and Environmental Engineering Department to identify the dominant sources of uncertainty in projections of future decadal TS frequency. Following on recently developed methodology, this study identifies three categories of uncertainties:
- Imperfect knowledge of future radiative forcing (e.g., greenhouse gas amount & and aerosol concentration), known as “Forcing Uncertainty”
- Imperfect knowledge of the response of the climate system to a given change in radiative forcing, known as “Response Uncertainty”
- Chaotic variations in the climate and weather system, unrelated to changes in radiative forcing, known as “Variability Uncertainty”.
These results suggest that efforts to understand the likely future course of North Atlantic hurricane activity should focus on improving the ability of global climate models to represent the processes that control patterns of sea surface temperature change, by improving the representation of fundamental process (e.g., cloud physics, atmospheric convection and oceanic processes), the response to diverse forcing (e.g., aerosols) and enhancing model fidelity through spatial resolution.
Further, though a substantial component of Variability Uncertainty is likely to remain irreducible, efforts should continue to build the observational, theoretical and modeling basis to understand (and exploit) multi-year to decadal predictability from initial conditions.