This study attempts to identify the factors affecting annual tropical cyclone (TC) activity in the South China Sea (SCS) using data during the period 1965-2005. The results indicate that the total number of TCs and number of TCs entering the SCS from the Western North Pacific are below normal in El Niño events but above normal during La Niña events. However, for TCs formed inside the SCS, the difference in numbers between the two phases of the El Niño-Southern Oscillation (ENSO) is not as obvious. In addition, the positive phase of the Pacific Decadal Oscillation (PDO) generally favours less TCs in all categories, while the negative PDO phase favours more. These results may be explained by the fact that the ENSO and the PDO affect TC behaviour through altering the conditions in the WNP to be favourable or unfavourable for TC genesis and movement into the SCS.
This paper investigates the factors affecting the annual number of tropical cyclones (TCs) passing within 100 km of the coast of Korea and Japan (KJ). Using a training set consisting of the coefficients of empirical orthogonal functions of these factors between 1965 and 2005, equations are derived to predict the annual number of these TCs over the whole season in April, and to update this prediction for the July-November (JN) season in June. Results show that the El Niño-Southern Oscillation (ENSO) plays a key role in determining the behaviour of TCs affecting KJ, with more TCs affecting the region during El Niño and less during La Niña. This difference can be attributed to ENSO modifying the flow patterns, which in turn affects TC behaviour. The prediction equations suggest that the 500-hPa geopotential height is more important in determining the number of TCs affecting KJ in the whole season, while both the 850-hPa geopotential height and 850-hPa vorticity play a role in the JN season. Both prediction schemes are able to produce acceptable results, with forecast skills of 42.3 and 33.3% over climatology for the whole, and JN seasons, respectively. The predicted TC number for
This study describes an improved statistical scheme for predicting the annual number of tropical cyclones (TCs) making landfall along the coast of south China using data from 1965 to 2005. Based on the factors affecting TC behavior inside the South China Sea (SCS), those responsible for TCs making landfall are identified. Equations are then developed using the coefficients of empirical orthogonal functions of these factors to predict, in April, the number of these TCs in the early (May-August) and late (September-December) seasons, and in June, the number in the period between July to December. The new scheme achieves a forecast skill of 51% over climatology, or an improvement of about 11% compared to previous studies, when predicting landfalling TC for the whole season, and it seems to be able to capture the decrease in their number in the recent years. Analyses of the flow patterns suggest that the conditions inside the SCS are apparently the major factor affecting the number of landfalling TCs. In years in which this number is above normal, conditions inside the SCS are favorable for TC genesis, and vice versa. The strength of the 500-hPa subtropical high also seems to be a factor in determining whether TCs from the western North Pacific (WNP) could enter the SCS and make landfall.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.