Seasonal prediction of summertime tropical cyclone activity over the East China Sea using the least absolute deviation regression and the Poisson regression

In the present study, we have employed two statistical models to predict summertime (July–September) tropical cyclone (TC) activity over the East China Sea using the least absolute deviation (LAD) regression and the Poisson regression method. Through a lagged correlation analysis of the relationship between the seasonal TC frequency in the target region and several pre-season environmental parameters for the period 1979–2003, physically interpretable and statistically significant large-scale environmental parameters were identified as potential predictors. After applying the predictor screening method based on the stepwise regression, three predictors, i.e. sea surface temperature, outgoing long-wave radiation and 850-hPa relative vorticity were finally chosen. They are related to the phase transition of El Nino/Southern Oscillation and the strength of the western North Pacific summer monsoon. The correlation coefficient between the predicted and the observed frequency is 0.75 for the LAD model and 0.78 for the Poisson model. The predictions using the two models have a skill improvement of about 60% compared to the reference forecasts. The present study suggests that both models are skillful in predicting summertime TC frequency over the East China Sea with the Poisson model being slightly more skillful than the LAD model. Copyright © 2009 Royal Meteorological Society

[1]  Johnny C. L. Chan,et al.  Global Warming and Western North Pacific Typhoon Activity from an Observational Perspective , 2004 .

[2]  Circulation features associated with the record‐breaking typhoon landfall on Japan in 2004 , 2005 .

[3]  Ronald W. Michener,et al.  A Poisson Regression Model of Highway Fatalities , 1992 .

[4]  Chang‐Hoi Ho,et al.  Dipole Structure of Interannual Variations in Summertime Tropical Cyclone Activity over East Asia. , 2005 .

[5]  Padhraic Smyth,et al.  Cluster Analysis of Typhoon Tracks. Part II: Large-Scale Circulation and ENSO , 2007 .

[6]  R. Elsberry,et al.  Large-Scale Circulation Variability over the Tropical Western North Pacific. Part I: Spatial Patterns and Tropical Cyclone Characteristics , 1995 .

[7]  Tetsuo Nakazawa,et al.  Madden-Julian Oscillation Activity and Typhoon Landfall on Japan in 2004 , 2006 .

[8]  K. Hodges,et al.  Seasonal prediction of hurricane activity reaching the coast of the United States , 2022 .

[9]  Kenneth J. Berry,et al.  Predicting Atlantic Basin Seasonal Tropical Cyclone Activity by 1 August , 1993 .

[10]  Kenneth J. Berry,et al.  Predicting Atlantic Seasonal Hurricane Activity 6–11 Months in Advance , 1992 .

[11]  P. Chu,et al.  Towards the monitoring and prediction of north‐east Brazil droughts , 1984 .

[12]  Mong-Ming Lu,et al.  Climate Prediction of Tropical Cyclone Activity in the Vicinity of Taiwan Using the Multivariate Least Absolute Deviation Regression Method , 2007 .

[13]  Russell L. Elsberry,et al.  Large-Scale Circulation Variability over the Tropical Western North Pacific. Part II: Persistence and Transition Characteristics , 1995 .

[14]  C. Schmertmann,et al.  Improving Extended-Range Seasonal Predictions of Intense Atlantic Hurricane Activity , 1993 .

[15]  Chang‐Hoi Ho,et al.  Systematic Variation of Summertime Tropical Cyclone Activity in the Western North Pacific in Relation to the Madden–Julian Oscillation , 2008 .

[16]  J. Chan,et al.  Seasonal Forecasting of Tropical Cyclone Activity over theWestern North Pacific and the South China Sea , 1998 .

[17]  H. Kwon,et al.  A Statistical Model for Prediction of the Tropical Cyclone Activity over the Western North Pacific , 2007 .

[18]  M. Kanamitsu,et al.  NCEP–DOE AMIP-II Reanalysis (R-2) , 2002 .

[19]  J. Chan,et al.  Climatological Characteristics and Seasonal Forecasting of Tropical Cyclones Making Landfall along the South China Coast , 2003 .

[20]  J. Elsner,et al.  Improving Seasonal Hurricane Predictions for the Atlantic Basin , 1995 .

[21]  John S. Woollen,et al.  NCEP-DOE AMIP-II reanalysis (R-2). Bulletin of the American Meteorological Society . , 2002 .

[22]  W. Briggs.  Statistical Methods in the Atmospheric Sciences , 2007 .

[23]  J. Elsner,et al.  Prediction Models for Annual U.S. Hurricane Counts , 2006 .

[24]  Chang‐Hoi Ho,et al.  Interdecadal Changes in Summertime Typhoon Tracks , 2004 .

[25]  Joseph P. Gerrity,et al.  A note on Gandin and Murphy's equitable skill score , 1992 .

[26]  Bin Wang,et al.  How Strong ENSO Events Affect Tropical Storm Activity over the Western North Pacific(. , 2002 .

[27]  N. Holbrook,et al.  A Poisson Regression Model of Tropical Cyclogenesis for the Australian–Southwest Pacific Ocean Region , 2004 .

[28]  Chang‐Hoi Ho,et al.  Possible influence of the Antarctic Oscillation on tropical cyclone activity in the western North Pacific , 2005 .

[29]  K. Lau,et al.  Interannual Variability of the Asian Summer Monsoon: Contrasts between the Indian and the Western North Pacific–East Asian Monsoons* , 2001 .

[30]  Bin Wang,et al.  A Contrast of the East Asian Summer Monsoon–ENSO Relationship between 1962–77 and 1978–93* , 2002 .

[31]  E. Cha,et al.  Statistical ensemble prediction of the tropical cyclone activity over the western North Pacific , 2007 .

[32]  S. Iizuka,et al.  A mechanism of interdecadal variability of tropical cyclone activity over the western North Pacific , 2003 .

[33]  W. Steiger,et al.  Least Absolute Deviations Curve-Fitting , 1980 .

[34]  D. E. Harrison,et al.  El Niño‐Southern Oscillation sea surface temperature and wind anomalies, 1946–1993 , 1998 .

[35]  J. Chan.  Interannual variations of intense typhoon activity , 2007 .

[36]  J. Chan,et al.  Improvements in the seasonal forecasting of tropical cyclone activity over the western North Pacific , 2001 .