2研ロゴ

Prediction of Mean location of Typhoon Formations

Japanese
left parenthis Introduction right parenthis

We investigate the feasibility of dynamical seasonal predictions of the interannual variability of the mean location of typhoon formation in the western North Pacific and its physical mechanisms during the active typhoon season from June to October. We performed seven-month integrations for 28 years starting from late April using the El Nino Southern Oscillation (ENSO) prediction system of the Japan Meteorological Agency. Typhoons detected with an objective method using model outputs are verified with best track data from the Regional Specialized Meteorological Center, Tokyo.

left parenthis Number of Typhoon Formation right parenthis

The climatological number of typhoon formation during the active typhoon season June to October, is 19.6 per year in observation and 18.5 per year in seasonal prediction experiment. We focus on the inverannual variability number of typhoon foramton.
As seen in Fig. 1, the correlation coefficient of the interannual variability of the number of typhoon formation during the active typhoon season is low (0.36) for the whole period (1979 to 2006) with 90% statistical significance level, comparable to that of AGCM simulations forced with the observed SST (Camargo et al. 2005).

Figure 1

Fig. 1: Comparison of the interannual variability of the number of typhoon formation during the active typhoon season between the observation and the CGCM ensemble prediction. Left: Interannual variability of the number of typhoons formed. The solid line denotes the best track value of the observation. The modified version of the box-and-whisker plot depicts the smallest, third smallest, mean, third largest, and largest values of the ensemble members. The gray area represents the standard deviation. Right: Scatter plot of the number of typhoon formation between the observation and the prediction.

left parenthis Mean location of Typhoon Formation right parenthis

The mean location of typhoon formation is correlated with El Nino Southern Oscillation phenomena (ENSO) Wang and Chan). ENSO is one of the most predictable phenomena in the seasonal predictions. Then, is the mean location related to ENSO predictable?
The good overall deterministic skill in predicting the interannual variability of the mean location of typhoon formation (Fig. 2) fundamentally stems from the ability to predict the interannual variability of the atmospheric circulation in the western North Pacific influenced by ENSO. The interannual variability of indices representing a latitudinal shift of the atmospheric circulation in the western North Pacific is better predicted than that of indices representing a longitudinal shift in this experiment. This difference in skill among these indices provides a physical basis for the difference in prediction skill between the mean latitude and longitude regarding the interannual variability of typhoon formation (Fig. 3). The correlation coefficients for mean longitude and latitude are 0.36 and -0.82, respectively.

第2図

Fig. 2: Comparison of the interannual variability of the mean location of typhoon formation during the active typhoon season between the observation and the CGCM ensemble prediction. Upper left: Interannual variability of the mean longitude. Upper right: Scatter plot of the mean longitude between the observation and prediction. Lower left: Same as in upper left but for the mean latitude. Lower right: Same as in upper right but for the mean latitude.



Figure 3

Fig. 3: Relationship between Nino3.4 sea surface temperature anomalies and the mean location of typhoon formation. Upper: Longitude. Lower: Latitude. Closed circles represent the observation, and open squares represent the CGCM ensemble mean prediction.

Probabilistic predictions also demonstrate the skillful predictions of the mean location of typhoon formation for tercile-based categories. Therefore, both deterministic and probabilistic predictions using our ENSO prediction system provide useful information about the mean location of typhoon formation.

References

  • Y. Takaya, T. Yasuda, T. Ose, and T. Nakaegawa. 2009. Seasonal prediction of mean location of Typhoon formation, JMSJ, 88(5), 799-812. Click here for Full Paper


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