tropical cyclone frequency
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The present paper deals with the influence of Southern Oscillation (SO) on the frequency of tropical cyclones in the north Indian Ocean. The results show that during the negative phase of SO the frequency of tropical cyclones and depressions over the Bay of Bengal and the Arabian Sea diminishes in May which is most important pre-monsoon cyclone month. The correlation coefficient between the frequency of cyclones and depressions and the Southern Oscillation Index (SOI) is +0.3 which is significant at 99% level. Post-monsoon cyclone frequency in the Bay of Bengal during November shows a significant positive correlation with SOl implying that it also decreases during the negative phase of SO. Thus there is a reduction in the tropical cyclone frequency over the Bay of Bengal during both intense cyclone months May and November in EI-Nino/Southern Oscillation (ENSO) epochs. Therefore it would not be correct to say that ENSO has no impact on the cyclogenesis in the north Indian Ocean. It is true that ENSO has no significant impact on the frequency of cyclones in the Arabian Sea. ENSO also seems to affect the rate of intensification of depressions to cyclone stage. The rate of intensification increases in May and diminishes in November in the north Indian Ocean during ENSO. The results are based on the analysis of monthly frequencies of tropical cyclones and depressions and SOI for the 100 year period from 1891-1990.

Abstract. Deriving reliable estimates of design water levels and wave conditions resulting from tropical cyclones is a challenging problem of high relevance for, among others, coastal and offshore engineering projects and risk assessment studies. Tropical cyclone geometry and wind speeds have been recorded for the past few decades only, therefore resulting in poorly reliable estimates of the extremes, especially at regions characterized by a low number of past tropical cyclone events. In this paper, this challenge is overcome by using synthetic tropical cyclone tracks and wind fields generated by the open source tool TCWiSE (Tropical Cyclone Wind Statistical Estimation), to create thousands of realizations representative for 1,000 years of tropical cyclone activity for the Bay of Bengal. Each of these realizations is used to force coupled storm surge and wave simulations by means of the processed-based Delft3D Flexible Mesh Suite. It is shown that the use of synthetic tracks provides reliable estimates of the statistics of the first-order hazard (i.e. wind speed) compared to the statistics derived for historical tropical cyclones. Based on estimated wind fields, second-order hazards (i.e. storm surge and waves) are computed. The estimates of the extreme values derived for wind speed, wave height and storm surge are shown to converge within the 1,000 years of simulated cyclone tracks. Comparing second-order hazard estimates based on historical and synthetic tracks show that, for this case study, the use of historical tracks (a deterministic approach) leads to an underestimation of the mean computed storm surge up to −30 %. Differences between the use of synthetic versus historical tracks are characterized by a large spatial variability along the Bay of Bengal, where regions with a lower probability of occurrence of tropical cyclones show the largest difference in predicted storm surge and wave heights. In addition, the use of historical tracks leads to much larger uncertainty bands in the estimation of both storm surges and wave heights, with confidence intervals being +80 % larger compared to those estimated by using synthetic tracks (probabilistic approach). Based on the same tropical cyclone realizations, the effect that changes in tropical cyclone frequency and intensity, possibly resulting from climate change, may have on modelled storm surge and wave heights were computed. An increase in tropical cyclone frequency of +25.6 % and wind intensity of +1.6 %, based on literature values, could result in an increase of storm surge and wave heights of +11 % and +9 % respectively. This suggest that climate change could increase tropical cyclone induced coastal hazards more than just the actual increase in maximum wind speeds.

<p>Tropical cyclone (TC) activity has significant seasonal, interannual and interdecadal variations. Accurate prediction of TC seasonal activities before the onset of the coming TC season (June-November) can provide sufficient time for the government and the public to prepare for tropical cyclone disasters and minimize risks and life losses.<br>Based on COAWST model, we developed a new regional coupled seasonal forecasting system for the Northwest Pacific Ocean including a series of technology improvements. The results of multi-year hindcast experiments show that the coupled seasonal forecasting system can effectively improve the tropical cyclone frequency and intensity forecast compared to the CFSv2 real-time seasonal forecast, especially the tropical cyclone frequency forecast of the TC exceeding the typhoon level, but there is still a certain gap between the results in the forecasting system and the observed TC frequency and intensity, which is mainly reflected in the fact that the forecasting season has a higher frequency of TCs and the peak of strong TCs is relatively weaker. This gap may be caused by the forecasting bias of the sea surface temperature.</p>