El Niño-Southern Oscillation and the seasonal predictability of tropical cyclones

Discussion and Conclusions

In section II, discussion centered on the need for favorable synoptic-scale variations of the environment to allow genesis and development of tropical cyclones to proceed. Since the El Niño-Southern Oscillation (ENSO) produces such large, widescale changes in the tropical circulation, perhaps it is not surprising that tropical cyclones are strongly altered by ENSO. However, these changes are not uniform throughout the global tropics. In some regions, an El Niño event would bring increases in tropical cyclone formation (e.g. the South Pacific and the North Pacific between 140^W to 160^E) while others see decreases (e.g. the North Atlantic, the Northwest Pacific west of 160^E, the Australian region). Las Niñas typically bring opposite conditions. These alterations in tropical cyclone activity are due to a variety of ENSO effects: by modulating the intensity of the local monsoon trough, by repositioning the location of the a monsoon trough and by altering the tropospheric vertical shear. Thus based on the global nature of ENSO alone, assumptions of independence between different tropical cyclone basins would be incorrect.

In addition to ENSO, three basins (the Atlantic, Southwest Indian and Northwest Pacific) show systematic alterations of tropical cyclone frequency by the stratospheric Quasi-Biennial Oscillation (QBO). This intuitively is unexpected given that tropical cyclones are primarily a tropospheric phenomenon, but may be due to alterations in the static stability and dynamics near the tropopause. Certainly more research is needed to provide a thorough explanation of these relationships. However, given the robustness of these alterations in tropical cyclone activity that match the QBO phases, it appears unlikely that the association is purely a chance correlation.

Interannual tropical cyclone variations have also been linked to more localized, basin-specific features such as sea surface temperatures (SST), monsoon strength and rainfall, sea level pressures and tropospheric vertical changes. These regional factors can be as large as the forcing due to ENSO, though most are not. Together with ENSO and the QBO, these factors produce changes in the frequency, intensity, formation region and track of tropical cyclones in all basins. However, understanding how tropical cyclone variability relates to the surrounding environmental conditions is hampered by having only a few decades worth of reliable tropical cyclone records. The emerging field of "paleotempestology" - the study of pre-historic tropical cyclones (e.g. Liu and Fearn 1993, Keen and Slingerland 1993) - may be able in coming years to assist in analyzing how and why tropical cyclones change from year to year.

Despite the current lack of accurate long-term tropical cyclone records, some of the tropical cyclone-environmental associations have led to methodologies in seasonal forecasting by the onset of the tropical cyclone season. Given that the typical lifecycle for a particular phase of ENSO of a year or greater, one can utilize this for the basis of seasonal predictions with lead times of up to several months. These are now being done (or can be performed) for the Atlantic basin tropical cyclones, those near Australia and in the South Pacific basin. These forecasts assume no knowledge of the future state of ENSO, except that the current ENSO phase will persist for at least the next few months in the future.

Over the last fifteen years, seasonal forecasting in various basins has evolved to the point that up to 50% (or more) of the tropical cyclone variability can be predicted at the start of the cyclone season. In addition to the frequency and intensity of the all basin storms, statistical methodologies have also introduced to forecast track frequency and the likelihood of hurricane landfall in certain coastal zones. Currently, such statistical models are the only feasible methodology for seasonal tropical cyclone forecasting, because the lack of skill in global circulation models (GCMs). Because of the complexity of difficulties faced in utilizing these numerical models, it may take a decade or two of concerted research effort before such GCM forecasting is feasible, if ever. However, for the current time, creative use of statistical regression schemes can provide and will continue to provide skilled and useful predictions of tropical cyclone activity around the world.

A sensible question would be how can seasonal forecasts of tropical cyclones be used when they are for large geographic regions such as the entire North Atlantic Ocean, Caribbean Sea and Gulf of Mexico. There are a number of reasons for issuing such predictions. Practically, most people in the general public cannot - and should not - utilize the forecast directly. As an example, it would be foolish if John Q. Public decided to ignore hurricane preparedness and mitigation plans because the year was one predicted to be below average. 1992 serves as an excellent warning against such actions: the Atlantic hurricane season was very successfully forecasted by Prof. Gray (see Table 2) as a quiet year with only four hurricanes, yet one of those was Hurricane Andrew - the most destructive U.S. hurricane on record (Mayfield et al. 1994). Strong wording should be added to any seasonal hurricane forecast to discourage an individual from using the forecast in such a way.

Corporations and governments, however, because of their size and scope of operations, are starting to make reasonable use of such forecasts each year. One large, private manufacturing company with interests all along the U.S. coastline serves as an example of the many utilizations that have been made with these predictions: decisions on the amount of "hurricane" liability insurance that covers preparations, damages and repair costs; determinations of annual budgets and preventative maintenance schedules; an aid in the production and inventory storing planning; plans for data processing disaster recovery; and schedules for workers' shifts in the upcoming year. Such usage can be better enhanced by increases in skill, by providing longer-range accurate predictions, and by regionalizing the forecast for smaller locales (such as being pursued by Lehmiller et al. [1997]).

Another justification for such forecasting efforts is that it leads to further advances in our understanding of linkages in the climate system. It was the failure of the 1989 seasonal Atlantic hurricane forecast (Table 2) that led to the discovery that the West African monsoon is intimately tied to the occurrence of Atlantic hurricanes on an interannual basis. Successes in seasonal tropical cyclone activity may also provide insight into forecasts of other tropical phenomena such as droughts/flooding associated with anomalous changes in the strength and location of the ITCZ and the monsoons (e.g. Hastenrath 1995).

Finally, the seasonal tropical cyclone forecasts at times generate public and media interest, whether or not individuals can actually make use of the predictions. A beneficial side effect of such interest is that it heightens the awareness of the public to the danger of hurricanes and hopefully prompts more people to take precautions and make preparations.