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Multiple Linear Regression Model for Prediction of Summer Tropical Cyclone Genesis Frequency over the Western North Pacific

북서태평양 태풍발생빈도 예측을 위한 다중회귀모델 개발

  • Choi, Ki-Seon (National Typhoon Center, Korea Meteorological Administration) ;
  • Cha, Yu-Mi (National Typhoon Center, Korea Meteorological Administration) ;
  • Chang, Ki-Ho (National Typhoon Center, Korea Meteorological Administration) ;
  • Lee, Jong-Ho (National Typhoon Center, Korea Meteorological Administration)
  • Received : 2013.07.05
  • Accepted : 2013.08.14
  • Published : 2013.08.30

Abstract

This study has developed a multiple linear regression model (MLRM) for the seasonal prediction of the summer tropical cyclone genesis frequency (TCGF) over the western North Pacific (WNP) using the four teleconnection patterns. These patterns are representative of the Siberian high Oscillation (SHO) in the East Asian continent, the North Pacific Oscillation (NPO) in the North Pacific, Antarctic oscillation (AAO) near Australia, and the circulation in the equatorial central Pacific during the boreal spring (April-May). This statistical model is verified by analyzing the differences hindcasted for the high and low TCGF years. The high TCGF years are characterized by the following anomalous features: four anomalous teleconnection patterns such as anticyclonic circulation (positive SHO phase) in the East Asian continent, pressure pattern like north-high and south-low in the North Pacific, and cyclonic circulation (positive AAO phase) near Australia, and cyclonic circulation in the Nino3.4 region were strengthened during the period from boreal spring to boreal summer. Thus, anomalous trade winds in the tropical western Pacific (TWP) were weakened by anomalous cyclonic circulations that located in the subtropical western Pacific (SWP) in both hemispheres. Consequently, this spatial distribution of anomalous pressure pattern suppressed convection in the TWP, strengthened convection in the SWP instead.

Acknowledgement

Supported by : Korea Meteorological Administration (KMA)

References

  1. Chan, J.C.L., Shi, J.E., and Liu, K.S., 2001, Improvements in the seasonal forecasting of tropical cyclone activity over the western North Pacific. Weather and Forecasting, 16, 491-498. https://doi.org/10.1175/1520-0434(2001)016<0491:IITSFO>2.0.CO;2
  2. Chen, T.C., Weng, S.P., Yamazaki, N., and Kiehne, S., 1998, Interannual variation in the tropical cyclone formation over the western North Pacific. Monthly Weather Review, 126, 1080-1089. https://doi.org/10.1175/1520-0493(1998)126<1080:IVITTC>2.0.CO;2
  3. Choi, K.S., Kang, K. R., Kim, D. W., Hwang, H. S., and Lee, S. R., 2009, A study on the characteristics of tropical cyclone passage frequency over the western North Pacific using Empirical Orthogonal Function. Journal of Korean Earth Science Society, 30, 721-733.(In Korea) https://doi.org/10.5467/JKESS.2009.30.6.721
  4. Choi, K.S. and Kim, T.R., 2011a, Development of a diagnostic index on the approach of typhoon affecting Korean Peninsula. Journal of Korean Earth Science Society, 32, 347-359.(In Korea) https://doi.org/10.5467/JKESS.2011.32.4.347
  5. Choi, K.S. and Kim, T.R., 2011b, Regime shift of the early 1980s in the characteristics of the tropical cyclone affecting Korea. Journal of Korean Earth Science Society, 32, 453-460. https://doi.org/10.5467/JKESS.2011.32.5.453
  6. Chu, P.S. and Zhao, X., 2007, A Bayesian regression approach for predicting seasonal tropical cyclone activity over the central North Pacific. Journal of Climate, 20, 4002-4013. https://doi.org/10.1175/JCLI4214.1
  7. Chu, P.S., Zhao, X., Lee, C.T., and Lu, M. M., 2007, Climate prediction of tropical cyclone activity in the vicinity of Taiwan using the multivariate least absolute deviation regression approach. Terrestrial Atmospheric and Oceanic Sciences, 18, 805-825. https://doi.org/10.3319/TAO.2007.18.4.805(A)
  8. Clark, J.D. and Chu, P.S., 2002, Interannual variation of tropical cyclone activity in the central North Pacific. Journal of Meteorological Society of Japan, 80, 403-418. https://doi.org/10.2151/jmsj.80.403
  9. DeMaria, M., Knaff, J.A., and Connell, B.H., 2001, A tropical cyclone genesis parameter for the tropical Atlantic. Weather and Forecasting, 16, 219-233. https://doi.org/10.1175/1520-0434(2001)016<0219:ATCGPF>2.0.CO;2
  10. Fan, K., 2007, North Pacific sea ice cover, a predictor for the western North Pacific typhoon frequency? Science China Series D: Earth Sciences, 50, 1251-1257. https://doi.org/10.1007/s11430-007-0076-y
  11. Gong, D.Y. and Wang, S., 1999, Definition of Antarctic oscillation index. Geophysical Research Letter, 26, 459-462. https://doi.org/10.1029/1999GL900003
  12. Gray, W.M., 1975, Tropical cyclone genesis. Dept. of Atmospheric Science Paper 234, Colorado State University, Fort Collins, CO, 121 pp.
  13. Ho, C.H., Kim J.H., Kim, H.S., Sui, C.H., and Gong, D.Y., 2005, Possible influence of the Antarctic Oscillation on tropical cyclone activity in the western North Pacific. Journal of Geophyical. Research, 110, D19104, doi:10.1029/2005JD005766. https://doi.org/10.1029/2005JD005766
  14. Jeong, Y.K. and Renwick, J.A., 2008, Locations of the Siberian high centers of action and associated propagation of wave-like Patterns in the Northern Hemisphere winter. Asia-Pacific Journal of Atmospheric Sciences, 44, 149-171.
  15. Kalnay, E., Kanamitsu, M., Kistler, R., Collins, W., Deaven, D., Gandin, L., Iredell, M., Saha, S., White, G., Woollen, J., Zhu, Y., Chelliah, M., Ebisuzaki, W., Higgins, W., Janowiak, J., Mo, K.C., Ropelewski, C., Wang, J., Leetmaa, A., Reynolds, R., Jenne, R., and Joseph, D., 1996, The NCEP/NCAR 40-Year Reanalysis Project. Bulletin of American Meteorological Society, 77, 437-471. https://doi.org/10.1175/1520-0477(1996)077<0437:TNYRP>2.0.CO;2
  16. McDonnell, K.A. and Holbrook H.J., 2004, A Poisson regression model of tropical cyclogenesis for the Australian-Southwest Pacific Ocean region. Weather and Forecasting, 19, 440-455. https://doi.org/10.1175/1520-0434(2004)019<0440:APRMOT>2.0.CO;2
  17. Rogers, J.C., 1981: The North Pacific oscillation. International Journal of Climatology, 1, 39-57. https://doi.org/10.1002/joc.3370010106
  18. Royer, J.F., Chauvin, F., Timbal, B., Araspin, P., and Grimal, D., 1998, A GCM study of the impact of greenhouse gas increase on the frequency of occurrence of tropical cyclones. Climate Change, 38, 307-343. https://doi.org/10.1023/A:1005386312622
  19. Ryan, B.F., Watterson, I.G., and Evans, J.L., 1992, Tropical cyclone frequencies inferred from Gray's yearly genesis parameter: Validation of GCM tropical climates. Geophysical Research Letters, 19, 1831-1834. https://doi.org/10.1029/92GL02149
  20. Walker, G.T., and Bliss, E.W., 1932, World Weather. Memorial of Royal Meteorological Society, 4, 53-84.
  21. Wang, H.J. and Fan, K., 2007, Relationship between the Antarctic oscillation and the western North Pacific typhoon frequency. Chinese Science Bulletin, 52, 561-565. https://doi.org/10.1007/s11434-007-0040-4
  22. Wang, H.J., Sun, J.Q., and Fan, K., 2007, Relationships between the North Pacific Oscillation and the typhoon/hurricane frequencies. Science in China Series D: Earth Science, 50, 1409-1416. https://doi.org/10.1007/s11430-007-0097-6
  23. Watterson, I.G., Evans, J.L., and Ryan, B.F., 1995, Seasonal and interannual variability of tropical cyclogenesis: Diagnostics from large-scale fields. Journal of Climate, 8, 3052-3066. https://doi.org/10.1175/1520-0442(1995)008<3052:SAIVOT>2.0.CO;2

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