DOI QR코드

DOI QR Code

Development of a Probability Prediction Model for Tropical Cyclone Genesis in the Northwestern Pacific using the Logistic Regression Method

  • 투고 : 2010.02.03
  • 심사 : 2010.05.10
  • 발행 : 2010.09.30

초록

A probability prediction model for tropical cyclone (TC) genesis in the Northwestern Pacific area was developed using the logistic regression method. Total five predictors were used in this model: the lower-level relative vorticity, vertical wind shear, mid-level relative humidity, upper-level equivalent potential temperature, and sea surface temperature (SST). The values for four predictors except for SST were obtained from difference of spatial-averaged value between May and January, and the time average of Ni$\tilde{n}$o-3.4 index from February to April was used to see the SST effect. As a result of prediction for the TC genesis frequency from June to December during 1951 to 2007, the model was capable of predicting that 21 (22) years had higher (lower) frequency than the normal year. The analysis of real data indicated that the number of year with the higher (lower) frequency of TC genesis was 28 (29). The overall predictability was about 75%, and the model reliability was also verified statistically through the cross validation analysis method.

키워드

참고문헌

  1. Camargo, S.J. and Sobel, A.H., 2005, Western North Pacific tropical cyclone intensity and ENSO. Journal of Climate, 18, 2996-3006. https://doi.org/10.1175/JCLI3457.1
  2. Chan, J.C.L., 1985, Tropical cyclone activity in the northwest Pacific in relation to the El Niño/Southern Oscillation phenomenon. Monthly Weather Review, 113, 599-606. https://doi.org/10.1175/1520-0493(1985)113<0599:TCAITN>2.0.CO;2
  3. Chan, J.C.L., 1998, Seasonal forecasting of tropical cyclone activity over the western North Pacific and the South China Sea. Weather and Forecasting, 13, 997-1004. https://doi.org/10.1175/1520-0434(1998)013<0997:SFOTCA>2.0.CO;2
  4. Chan, J.C.L., 2008, A simple seasonal forecast update of tropical cyclone activity. Weather and Forecasting, 23, 1016-1021. https://doi.org/10.1175/2008WAF2007061.1
  5. 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, 1080-1090. https://doi.org/10.1175/1520-0493(1998)126<1080:IVITTC>2.0.CO;2
  6. Chia, H.H. and Ropelewski, C.F., 2002, The interannual variability in the genesis location of tropical cyclones in the Northwest Pacific. Journal of Climate, 15, 2934-2944. https://doi.org/10.1175/1520-0442(2002)015<2934:TIVITG>2.0.CO;2
  7. Choi, K.-S., Moon, J.-Y., Chu, P.-S., and Kim, D.-W., 2010, Seasonal prediction of tropical cyclone genesis frequency over the western North Pacific using teleconnection patterns. Theoretical and Applied Climatology, 100, 191-206, doi: 10.1007/s00704-009-0182-1.
  8. Crosby, S.C. and Ferraro, R.R., 1995, Estimating the probability of rain in an SSM/I FOV using logistic regression. Journal of Applied Meteorology, 34, 2476-2480. https://doi.org/10.1175/1520-0450(1995)034<2476:ETPORI>2.0.CO;2
  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. Dong, K.Q., 1988, El Nino and tropical cyclone frequency in the Australian region and the northwest Pacific. Australian Meteorological Magazine, 28, 219-225.
  11. Elsner, J.B. and Schmertmann, C.P., 1993, Improving extendedrange seasonal predictions of intense Atlantic hurricane activity. Weather and Forecasting, 8, 345-351. https://doi.org/10.1175/1520-0434(1993)008<0345:IERSPO>2.0.CO;2
  12. Elsner, J.B., Liu, K.B., and Kocher, B., 2000, Spatial variations in major U.S. hurricane activity: Statistics and a physical mechanism. Journal of Climate, 13, 2293-2305. https://doi.org/10.1175/1520-0442(2000)013<2293:SVIMUS>2.0.CO;2
  13. Frei, C. and Schar, C., 2001, Detection Probability of Trends in Rare Events: Theory and Application to Heavy Precipitation in the Alpine Region. Journal of Climate, 14, 1568-1583. https://doi.org/10.1175/1520-0442(2001)014<1568:DPOTIR>2.0.CO;2
  14. Gray, W.M., 1968, Global view of the origin of tropical disturbances and storms. Monthly Weather Review, 96, 669-700. https://doi.org/10.1175/1520-0493(1968)096<0669:GVOTOO>2.0.CO;2
  15. Gray, W.M., Landsea, C.W., Mielke, Jr.P.W., and Berry, K.J., 1992, Predicting Atlantic basin seasonal hurricane activity 6-11 months in advance. Weather and Forecasting, 7, 440-455. https://doi.org/10.1175/1520-0434(1992)007<0440:PASHAM>2.0.CO;2
  16. Gray, W.M., Landsea, C.W., Mielke, Jr.P.W., and Berry, K.J., 1993, Predicting Atlantic basin seasonal tropical cyclone activity by 1 August. Weather and Forecasting, 8, 73-86. https://doi.org/10.1175/1520-0434(1993)008<0073:PABSTC>2.0.CO;2
  17. Gray, W.M., Landsea, C.W., Mielke, Jr. P.W., and Berry, K.J., 1994, Predicting Atlantic basin seasonal tropical cyclone activity by 1 June. Weather and Forecasting, 9, 103-115. https://doi.org/10.1175/1520-0434(1994)009<0103:PABSTC>2.0.CO;2
  18. Greene, W.H., 2000, Econometric Analysis (Fourth edition). Prentice-Hall, NJ, USA, 256 p.
  19. Hess, J.C., Elsner, J.B., and LaSeur, N.E., 1995, Improving seasonal hurricane predictions for the Atlantic basin. Weather and Forecasting, 10, 425-432. https://doi.org/10.1175/1520-0434(1995)010<0425:ISHPFT>2.0.CO;2
  20. Jagger, T.H., Elsner, J.B., and Niu, X., 2001, A dynamic probability model of hurricane winds in coastal counties of the United States. Journal of Applied Meteorology, 40, 853-863. https://doi.org/10.1175/1520-0450(2001)040<0853:ADPMOH>2.0.CO;2
  21. Jagger, T.H., Niu, X., and Elsner, J.B., 2002, A space-time model for seasonal hurricane prediction. International Journal of Climatology, 22, 451-465. https://doi.org/10.1002/joc.755
  22. Kalnay, E., Kanamitsu, M., Kistler, R., Collins, W., Deaven, D., Gandin, L., Iredell, M., Saha, S., White, G., Woollen, J., Zhu, Y., Leetmaa, A., Reynolds, R., Chelliah, M., Ebisuzaki, W., Higgins, W., Janowiak, J., Mo, K.C., Ropelewski, C., Wang, J., 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
  23. Kistler, R., Kalnay, E., Collins, W., Saha, S., White, G., Woollen, J., Chelliah, M., Ebisuzaki, W., Kanamitsu, M., Kousky, V., Dool, H., Jenne, R., and Fiorino, M., 2001, The NCEP/NCAR 50-year reanalysis. Bulletin of the American Meteorological Society, 82, 247-267. https://doi.org/10.1175/1520-0477(2001)082<0247:TNNYRM>2.3.CO;2
  24. Kwon, H.-J., Lee, W.-J., Won, S.-H., and Cha, E.-J., 2007, Statistical ensemble prediction of the tropical cyclone activity over the western North Pacific. Geophysical Research Letters, 34, L24805, doi: 10.1029/2007GL032308.
  25. Lee, W.-J., Park, J.-S., and Kwon, H.-J., 2007, A statistical model for prediction of the tropical cyclone activity over the western North Pacific. Journal of the Korean Meteorological Society, 43, 175-183.
  26. Lehmiller, G.S., Kimberlain, T.B., and Elsner, J.B., 1997, Seasonal prediction models for North Atlantic basin hurricane location. Monthly Weather Review, 125, 1780-1791. https://doi.org/10.1175/1520-0493(1997)125<1780:SPMFNA>2.0.CO;2
  27. Leroy, A. and Wheeler, M.C., 2008, Statistical prediction of weekly tropical cyclone activity in the Southern Hemisphere. Monthly Weather Review, 136, 3637-3654. https://doi.org/10.1175/2008MWR2426.1
  28. McDonnell, K.A. and Holbrook, N.J., 2004, A Poisson regression model of tropical cyclogenesis for the Australian-southwest Pacific Ocean region. Weather and Forecasting, 19, 440-454. https://doi.org/10.1175/1520-0434(2004)019<0440:APRMOT>2.0.CO;2
  29. Mestre, O. and Hallegatte, S., 2008, Predictors of tropical cyclone numbers and extreme hurricane intensities over the North Atlantic using generalized additive and linear model. Journal of Climate, 22, 633-648.
  30. Nicholls, N., 1992, Recent performance of a method for forecasting Australian seasonal tropical cyclone activity. Australian Meteorological Magazine, 40, 105-110.
  31. 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. Climatic Change, 38, 307-343. https://doi.org/10.1023/A:1005386312622
  32. 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 Letter, 19, 1831-1834. https://doi.org/10.1029/92GL02149
  33. Vislocky, R.L. and Young, G.Y., 1989, The use of perfect prog forecasts to improve model output statistics forecasts of precipitation probability. Weather and Forecasting, 4, 202-209. https://doi.org/10.1175/1520-0434(1989)004<0202:TUOPPF>2.0.CO;2
  34. Vislocky, R.L. and Fritsch, J.M., 1995b, Improved model output statistics forecasts through model consensus. Bulletin of American Meteorological Society, 76, 1157-1164. https://doi.org/10.1175/1520-0477(1995)076<1157:IMOSFT>2.0.CO;2
  35. Wang, B. and Chan, J.C.L., 2002, How strong ENSO events affect tropical storm activity over the western North Pacific. Journal of Climate, 15, 1643-1658. https://doi.org/10.1175/1520-0442(2002)015<1643:HSEEAT>2.0.CO;2
  36. Ward, G.F.A., 1995, Prediction of tropical cyclone formation in terms of sea-surface temperature, vorticity and vertical wind shear. Australian Meteorological Magazine, 44, 61-70.
  37. 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
  38. Webster, P.J., Holland, G.J., Curry, J.A., and Chang, H.R., 2005, Changes in tropical cyclone number, duration, and intensity in a warming environment. Science, 309, 1844-1846. https://doi.org/10.1126/science.1116448
  39. Wilks, D.S., 1995, Statistical Methods in the Atmospheric Sciences. Academic Press, UK, 240 p.
  40. Wu, G. and Lau, N.C., 1992, A GCM simulation of the relationship between tropical storm formation and ENSO. Monthly Weather Review, 120, 958-977. https://doi.org/10.1175/1520-0493(1992)120<0958:AGSOTR>2.0.CO;2