Japan Meteorological Agency/Meteorological Research Institute-Coupled Prediction System version 1 (JMA/MRI-CPS1) for operational seasonal forecasting

Climate Dynamics(2016)

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摘要
This paper describes the operational seasonal prediction system of the Japan Meteorological Agency (JMA), the Japan Meteorological Agency/Meteorological Research Institute-Coupled Prediction System version 1 (JMA/MRI-CPS1), which was in operation at JMA during the period between February 2010 and May 2015. The predictive skill of the system was assessed with a set of retrospective seasonal predictions (reforecasts) covering 30 years (1981–2010). JMA/MRI-CPS1 showed reasonable predictive skill for the El Niño–Southern Oscillation, comparable to the skills of other state-of-the-art systems. The one-tiered approach adopted in JMA/MRI-CPS1 improved its overall predictive skills for atmospheric predictions over those of the two-tiered approach of the previous uncoupled system. For 3-month predictions with a 1-month lead, JMA/MRI-CPS1 showed statistically significant skills in predicting 500-hPa geopotential height and 2-m temperature in East Asia in most seasons; thus, it is capable of providing skillful seasonal predictions for that region. Furthermore, JMA/MRI-CPS1 was superior overall to the previous system for atmospheric predictions with longer (4-month) lead times. In particular, JMA/MRI-CPS1 was much better able to predict the Asian Summer Monsoon than the previous two-tiered system. This enhanced performance was attributed to the system’s ability to represent atmosphere–ocean coupled variability over the Indian Ocean and the western North Pacific from boreal winter to summer following winter El Niño events, which in turn influences the East Asian summer climate through the Pacific–Japan teleconnection pattern. These substantial improvements obtained by using an atmosphere–ocean coupled general circulation model underpin its success in providing more skillful seasonal forecasts on an operational basis.
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关键词
Seasonal prediction,Coupled model,ENSO,Asian monsoon
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