The representation of the CFSv2 ocean-atmosphere ensemble hindcasts is investigated during Dec-Jan-Feb (DJF) and Jun-Jul-Aug (JJA) from 1983 to 2010. The skill anomaly correlations showed that in some continents the forecasts do not have dependency with changes in the initial conditions. Also, in both seasons the model has a higher skill at the 0-month lead time with the largest spatial biases occurring over the North America, South America, and Oceania. Over the continents the largest biases in the nonlinearity of El Ni？o minus La Ni？a events are found over the eastern South Africa, part of Oceania, and central-southeastern parts of South America. During DJF the main biases are related to double-ITCZ, strengthening of SPCZ, and deepening of the Aleutian and Icelandic low pressures. The simulation of a warmer SST on the eastern of most austral oceans, the strengthening (weakening) of the Subtropical (Polar) Jet over the Southern Hemisphere, and the weakening of the zonal circulation near the Antarctic continent are also found in both seasons. Over the central-eastern Equatorial Pacific a cooler bias in SST is found during JJA. These biases are interpreted by analyses of the simulated global mean-state and their impact on the main patterns of variability. 1. Introduction It is fair to say that the Ocean-Atmosphere Global Climate Models (OAGCMs) have become indispensable tools for the climate sciences. Despite the complexity of the climate system, many efforts have been made to improve the climate modeling in recent years. The Climate Forecast System version 2 (CFSv2) model is one example of such progress whose hindcasts and real-time operational forecasts have been provided by the National Centers for Environmental Prediction (NCEP) since March 2011. The hindcasts (reforecasts) are designed to test the models; that is, inputs from the past climate are used to the forecasts and allow evaluating how well the predictions approach to the observed climate. CFSv2 is initialized by the CFS Reanalysis (CFSR) that cover the period from 1979 to present and the main characteristics are described by Saha et al. [1]. The hindcasts performance can be assessed by many metrics and some recent papers have focused on assessing the global CFSv2 ability. For the 1982–2009 period Yuan et al. [2] and Wood et al. [3] provided a first look on the CFSv2 hydrological seasonal forecasting skill by comparing it with the CFSv1 reforecasts. Over the continents the CFSv2 increases the skill for monthly surface air temperature and precipitation by 37% and 29%, respectively, compared to
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