A dynamical-statistical forecast model for the annual frequency of western Pacific tropical cyclones based on the NCEP Climate Forecast System version 2

A dynamical-statistical forecast model for the annual tropical cyclones over the western North Pacific is developed based on the empirical relationship between the actual annual number of tropical cyclones (ANTCs) and the dynamical predictions of large-scale variables by the Climate Forecast System version 2 of the National Centers for Environmental Prediction (NCEP). On interannual time scales, the ANTCs are significantly and negatively correlated with the July-October tropical North Atlantic sea surface temperature, tropical western Pacific vertical zonal wind shear (WPVZWS), and subtropical Pacific geopotential height at 500 hPa (HGT500). They are also positively correlated with the zonal wind at 850 hPa over the tropical Pacific Ocean. Skillful forecasts of the above four potential predictors are made with the 24-member ensemble predictions by the NCEP model. The two-predictor model with the HGT500 and the WPVZWS shows the most skillful hindcasts at 0-2 month leads assessed by the leave-one-out cross validation for the ANTCs over the 31 year record between 1982 and 2012. The corresponding correlation coefficients and the root-mean-square errors (RMSEs) between the observed and hindcast ANTCs are in the ranges from 0.73 to 0.79 and from 3.11 to 2.75, respectively. Observed ANTCs during El Niño-Southern Oscillation events are generally well captured with RMSEs ranging from 3.12 to 3.04 during El Niño years and from 3.62 to 2.44 during La Niña years. The forecast skill of the model for the past 10 years (2003-2012) is competitive with the current forecast schemes. The forecast model initialized in March, May, and June 2013 suggests an inactive season for 2013, with about 22 tropical cyclones. Key Points Evaluate skill of NCEP CFS for tropical cyclone prediction Identify predictors for tropical cyclones in both observation and model Improve skill of tropical cyclone prediction ©2013. American Geophysical Union. All Rights Reserved.