Advance and prospectus of seasonal prediction: assessment of the APCC/CliPAS 14-model ensemble retrospective seasonal prediction (1980–2004)

We assessed current status of multi-model ensemble (MME) deterministic and probabilistic seasonal prediction based on 25-year (1980–2004) retrospective forecasts performed by 14 climate model systems (7 onetier and 7 two-tier systems) that participate in the Climate Prediction and its Application to Society (CliPAS) project sponsored by the Asian-Pacific Economic Cooperation Climate Center (APCC). We also evaluated seven DEMETER models’ MME for the period of 1981–2001 for comparison. Based on the assessment, future direction for improvement of seasonal prediction is discussed. We found that two measures of probabilistic forecast skill, the Brier Skill Score (BSS) and Area under the Relative Operating Characteristic curve (AROC), display similar spatial patterns as those represented by temporal correlation coefficient (TCC) score of deterministic MME forecast. A TCC score of 0.6 corresponds approximately to a BSS of 0.1 and an AROC of 0.7 and beyond these critical threshold values, they are almost linearly correlated. The MME method is demonstrated to be a valuable approach for reducing errors and quantifying forecast uncertainty due to model formulation. The MME prediction skill is substantially better than the averaged skill of all individual models. For instance, the TCC score of CliPAS one-tier MME forecast of Niño 3.4 index at a 6-month lead initiated from 1 May is 0.77, which is significantly higher than the B. Wang (&) J.-Y. Lee X. Fu P. Liu Department of Meteorology and International Pacific Research Center, IPRC, School of Ocean and Earth Science and Technology, University of Hawaii, Honolulu, HI 96822, USA e-mail: [email protected] I.-S. Kang J.-S.Kug School of Earth and Environmental Sciences, Seoul National University, Seoul, South Korea J. Shukla E. K. Jin J. Kinter B. Kirtman Climate Dynamics Program, George Mason University and COLA, Calverton, MD, USA C.-K.Park APEC Climate Center, Busan, South Korea A. Kumar J. Schemm Climate Prediction Center/NCEP, Camp Springs, MD, USA S. Cocke T. Krishnamurti Florida State University, Tallahassee, FL, USA J.-J.Luo T. Yamagata Frontier Research Center for Global Chnage, Yokohama, Japan T. Zhou B. Wang LASG/Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, China W.-T.Yun Korean Meteorological Administration, Seoul, South Korea O. Alves Bureau of Meteorology Research Center, Melburne, Australia N. C. Lau T. Rosati W. Stern Geophysical Fluid Dynamics Laboratory/NOAA, Princeton University, Princeton, NJ, USA W. Lau P. Pegion S. Schubert M. Suarez Godard Space Flight Center/NASA, Greenbelt, MD, USA T. Yamagata University of Tokyo, Tokyo, Japan 123 Clim Dyn (2009) 33:93–117 DOI 10.1007/s00382-008-0460-0