SOI - based forecast of Australian region tropical cyclone activity

contributed by N.Nicholls

Bureau of Meteorology Research Centre, Melbourne, Australia

The tropical cyclone season around northern Australia (105E-165E) extends from November to May. The average number of cyclones per season is 9.4 (mean from 1949/50 season to 1995/96 season), with a standard deviation of 3.3. Cyclone activity in this region is related to the El Niño - Southern Oscillation, with fewer than normal cyclones during El Niño episodes, and is predictable from prior observations of simple indices of the El Niño - Southern Oscillation (Nicholls, 1979, 1984, 1985, 1992; Solow and Nicholls, 1990). Figure 1 shows time series of October Southern Oscillation Index (SOI) and the number of tropical cyclones (TCs). The SOI values were provided by the National Climate Centre, Bureau of Meteorology, Melbourne, and are the standardized (mean = 0, standard deviation = 10) difference between Darwin and Tahiti pressures. The correlation (1949-50 to 1994/95) is +.47, significant at better than 1%.

Solow and Nicholls (1990) and Nicholls (1992) noted that the relationship between the SOI and TCs is weakened by apparently artificial long term variations in TC activity (eg., the gradual increase in numbers up to the mid-1970s, as observation systems improved). Nicholls (1992) suggested that correlating first differences (i.e., year₀ minus year_-1 differences) of the SOI and TC numbers would reduce the influence of any artificial trends. The correlation between the first differences is +.71, also significant at better than 1%. The linear regression, with zero intercept, between the first differences is: TCs = 0.22*SOI_October where TCs is the predicted difference in TC numbers from last season to the coming season, and SOI_October is the observed difference in SOI from October last year to the current year. Since the number of TCs occurring in the previous season is known, this equation can be used to predict the coming year's TC numbers. Nicholls (1992) demonstrated that such an approach can lead to skillful forecasts, by calculating the regression between the first differences from 1959/69 to 1978/79 data and then applying it to 1979/80 to 1990/91 data. The RMS error of the hindcasts on the independent data was 2.8. The RMS error of a persistence forecast for the same period would have been 4.8.

The change in October SOI from 1997 to 1998 was +28.7. The above equation therefore led to a prediction that TC numbers in 1998/99 would be about 6 more than in 1997/98, i.e., about 15, well above average. The actual number was 12, i.e., above average.

The October 1999 SOI was +9.1, and the change from the October 1998 value was -1.8. The above equation therefore leads to a prediction that TC numbers in 1999/00 would be about the same as in 1998/99, i.e., about 12, i.e., above average.

References:

Nicholls, N., 1979: A possible method for predicting seasonal tropical cyclone activity in the Australian region. Mon. Weath. Rev., 107, 1221-4.

Nicholls,N., 1984: The Southern Oscillation, sea-surface-temperature, and interannual fluctuations in Australian tropical cyclone activity. J. Climatol., 4, 661.70.

Nicholls,N., 1985: Predictability of interannual variations of Australian seasonal tropical cyclone activity. Mon. Weath. Rev., 113, 1144-9.

Nicholls,N., 1992: Recent performance of a method for forecasting Australian seasonal tropical cyclone activity. Aust. Meteorol. Mag., 40, 105-110.

Solow,A., and N.Nicholls, 1990: The relationship between the Southern Oscillation and tropical cyclone frequency in the Australian region. J. Climate, 3, 1097-1101.

Figure 1. Time series of October SOI and the number of tropical cyclones around northern Australia in the ensuing cyclone season (November-May).