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Climate Dynamics

, Volume 48, Issue 1–2, pp 71–88 | Cite as

Dynamical–statistical seasonal prediction for western North Pacific typhoons based on APCC multi-models

  • Ok-Yeon KimEmail author
  • Hye-Mi Kim
  • Myong-In Lee
  • Young-Mi Min
Article

Abstract

This study aims at predicting the seasonal number of typhoons (TY) over the western North Pacific with an Asia-Pacific Climate Center (APCC) multi-model ensemble (MME)-based dynamical–statistical hybrid model. The hybrid model uses the statistical relationship between the number of TY during the typhoon season (July–October) and the large-scale key predictors forecasted by APCC MME for the same season. The cross validation result from the MME hybrid model demonstrates high prediction skill, with a correlation of 0.67 between the hindcasts and observation for 1982–2008. The cross validation from the hybrid model with individual models participating in MME indicates that there is no single model which consistently outperforms the other models in predicting typhoon number. Although the forecast skill of MME is not always the highest compared to that of each individual model, the skill of MME presents rather higher averaged correlations and small variance of correlations. Given large set of ensemble members from multi-models, a relative operating characteristic score reveals an 82 % (above-) and 78 % (below-normal) improvement for the probabilistic prediction of the number of TY. It implies that there is 82 % (78 %) probability that the forecasts can successfully discriminate between above normal (below-normal) from other years. The forecast skill of the hybrid model for the past 7 years (2002–2008) is more skillful than the forecast from the Tropical Storm Risk consortium. Using large set of ensemble members from multi-models, the APCC MME could provide useful deterministic and probabilistic seasonal typhoon forecasts to the end-users in particular, the residents of tropical cyclone-prone areas in the Asia-Pacific region.

Keywords

Seasonal tropical cyclones Western North Pacific Multimodel ensemble Deterministic and probabilistic forecasts 

Notes

Acknowledgments

This research was supported by the APEC Climate Center. The authors acknowledge the APCC MME Producing Centres for making their hindcast/forecast data available for analysis and the APEC Climate Center for collecting and archiving them and for organizing APCC MME prediction. The single-model and multimodel predictions used in the paper are available at the APCC Data Service System (ADSS, http://apcc21.sbis.co.kr/). However, some of models cannot be redistributed through the APCC due to their security issues (e.g., JMA).

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Copyright information

© Springer-Verlag Berlin Heidelberg 2016

Authors and Affiliations

  • Ok-Yeon Kim
    • 1
    Email author
  • Hye-Mi Kim
    • 2
  • Myong-In Lee
    • 3
  • Young-Mi Min
    • 1
  1. 1.APEC Climate Center (APCC)BusanKorea
  2. 2.School of Marine and Atmospheric SciencesStony Brook UniversityNYUSA
  3. 3.School of Urban and Environmental EngineeringUNISTUlsanKorea

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