A Comprehensive Assessment of CFS Seasonal Forecasts over the Tropics

Abstract

he 15-member ensemble hindcasts performed with the National Centers for Environmental Prediction Climate Forecast System (CFS) for the period 1981?2005, as well as real-time forecasts for the period 2006?09, are assessed for seasonal prediction skills over the tropics, from deterministic (anomaly correlation), categorical (Heidke skill score), and probabilistic (rank probability skill score) perspectives. Further, persistence, signal-to-noise ratio, and root-mean-square error analyses are also performed. The CFS demonstrates high skill in forecasting El Niño?Southern Oscillation (ENSO) related sea surface temperature (SST) anomalies during developing and mature phases, including that of different types of El Niño. During ENSO, the space?time evolution of anomalous SST, 850-hPa wind, and rainfall along the equatorial Pacific, as well as the mechanisms involved in the teleconnection to the tropical Indian Ocean, are also well represented. During ENSO phase transition and in the summer, the skill of forecasting Pacific SST anomalies is modest. An examination of CFS ability in forecasting seasonal rainfall anomalies over the U.S. Affiliated Pacific Islands (USAPI) indicates that forecasting the persistence of dryness from El Niño winter into the following spring/summer is skillful at leads > 3 months. During strong El Niño years the persistence is predicted by all members with a 6-month lead time. Also, the model is skillful in predicting regional rainfall responses during different types of El Niño. Since both deterministic and probabilistic skill scores converge, the suggestion is that the forecast is useful. The model?s skill in the real-time forecasts for the period 2006?09 is also discussed. The results suggest the feasibility that a dynamical-system-based seasonal prediction of precipitation over the USAPI can be considered.