Wednesday, 26 January 2011: 11:15 AM
604 (Washington State Convention Center)
Understanding the genesis, development and evolution of Atlantic tropical cyclones (TC) is of great scientific and practical interest. Advances in meteorological observing systems and dynamic models continue to improve the short-term forecast (few days) of individual TC. At seasonal time scale, two approaches are currently employed: a) use Global Circulation Models (GCMs) to simulate TC and understand the physical interactions between ocean and atmosphere in the North Atlantic region, and b) utilize statistical methods to forecast TC activity (mainly the number of tropical storms and their intensity) based on large scale average predictors such as: sea surface temperature anomalies (SSTA), vertical wind shear, Quasi-Biennial Oscillation (QBO), El Nino - Southern Oscillation (ENSO), and the phase of Atlantic Multidecadal Oscillation (AMO). Operational schemes for the seasonal outlook of TC activity have demonstrated the role of ENSO events. In this study we use the NOAA Extended Reconstructed Sea Surface Temperature (SST) and the TC counts in North Atlantic from the National Hurricane Center's North Atlantic hurricane database (HURDAT) to investigate the statistical relationship between significant ENSO events and TC during the hurricane season. The statistical model is based on data from the time interval 1950 2009. The model has predictive capability during significant ENSO events, provided that a preliminary forecast of ENSO is available. Based on other recent studies, strong ENSO events are predictable with increasing degree of accuracy by a range of dynamic and statistical methods. We illustrate a statistical method to forecast ENSO SSTA a few months in advance the peak of Atlantic hurricane season. Forecasted ENSO SSTA can be used as predictors of TC in North Atlantic region, with significant skill. A series of potential uncertainties and model limitations are discussed, particularly due to possible alterations of ENSO, AMO, and TC activity caused by global warming. Such issues are presented and illustrated in the context of current efforts to understand climate predictability relevant to North Atlantic tropical storms.
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