The second version of the NCEP Climate Forecast System (CFSv2) was operational in March 2011. This version includes upgrades to nearly all aspects of the data assimilation and forecast model components. A coupled reanalysis was conducted over 32 years (1979–2010) to provide initial conditions for a comprehensive reforecast over 29 years (1982–2010). This was done to obtain consistent and stable calibrations and skill estimates for the operational subseasonal and seasonal predictions. The operational implementation of the full system ensures continuity of the climate record and provides a valuable up-to-date dataset for studying predictability on seasonal and subseasonal scales. Evaluation of the reforecasts shows that CFSv2 increases the length of skillful MJO forecasts from 6 to 17 days, nearly doubles the skill of seasonal forecasts of 2-m temperatures over the United States, and significantly improves global SST forecasts. CFSv2 provides greatly improved guidance at these time scales and creates many more products for subseasonal and seasonal forecasting with an extensive set of retrospective forecasts for users to calibrate their forecast products. These retrospective and real-time operational forecasts will be used by a wide community of users in their decision-making processes in areas such as water management, agriculture, transportation, energy use, and seasonal prediction of the hurricane season. CFSv2 has improvements in all four components mentioned, including an upgraded four-level soil model, an interactive three-layer sea ice model, and historically prescribed CO₂ concentrations. CFSv2 was designed to improve consistency between the model states and the initial states produced by the data assimilation system. The CFSv2 model, the design of the retrospective forecasts, and some results from these forecasts are described. The performance of the CFSv2 retrospective forecasts can be split into four time scales. The shortest time scale is the subseasonal, mainly geared toward the prediction of the Madden–Julian oscillation (MJO) and more generally forecasts for the week 2–6 period over the United States. The next time scale is the "long lead" seasonal prediction, out to 9 months. For both the subseasonal and seasonal, we have a very precise comparison between skill of prediction by the CFSv1 and CFSv2 systems evaluated over exactly the same hindcast years. The final two time scales are decadal and centennial. Here the emphasis is less on forecast skill, and more on the general behavior of the model in extended integrations for climate studies. The paper makes simple comparisons between aspects of CFSv1 and CFSv2 performance and discusses changes relative to CFSv1. The CFSv2 model, the design of the retrospective forecasts, and some results from these forecasts are described. The performance of the CFSv2 retrospective forecasts can be split into four time scalesThe second version of the NCEP Climate Forecast System (CFSv2) was operational in March 2011. This version includes upgrades to nearly all aspects of the data assimilation and forecast model components. A coupled reanalysis was conducted over 32 years (1979–2010) to provide initial conditions for a comprehensive reforecast over 29 years (1982–2010). This was done to obtain consistent and stable calibrations and skill estimates for the operational subseasonal and seasonal predictions. The operational implementation of the full system ensures continuity of the climate record and provides a valuable up-to-date dataset for studying predictability on seasonal and subseasonal scales. Evaluation of the reforecasts shows that CFSv2 increases the length of skillful MJO forecasts from 6 to 17 days, nearly doubles the skill of seasonal forecasts of 2-m temperatures over the United States, and significantly improves global SST forecasts. CFSv2 provides greatly improved guidance at these time scales and creates many more products for subseasonal and seasonal forecasting with an extensive set of retrospective forecasts for users to calibrate their forecast products. These retrospective and real-time operational forecasts will be used by a wide community of users in their decision-making processes in areas such as water management, agriculture, transportation, energy use, and seasonal prediction of the hurricane season. CFSv2 has improvements in all four components mentioned, including an upgraded four-level soil model, an interactive three-layer sea ice model, and historically prescribed CO₂ concentrations. CFSv2 was designed to improve consistency between the model states and the initial states produced by the data assimilation system. The CFSv2 model, the design of the retrospective forecasts, and some results from these forecasts are described. The performance of the CFSv2 retrospective forecasts can be split into four time scales. The shortest time scale is the subseasonal, mainly geared toward the prediction of the Madden–Julian oscillation (MJO) and more generally forecasts for the week 2–6 period over the United States. The next time scale is the "long lead" seasonal prediction, out to 9 months. For both the subseasonal and seasonal, we have a very precise comparison between skill of prediction by the CFSv1 and CFSv2 systems evaluated over exactly the same hindcast years. The final two time scales are decadal and centennial. Here the emphasis is less on forecast skill, and more on the general behavior of the model in extended integrations for climate studies. The paper makes simple comparisons between aspects of CFSv1 and CFSv2 performance and discusses changes relative to CFSv1. The CFSv2 model, the design of the retrospective forecasts, and some results from these forecasts are described. The performance of the CFSv2 retrospective forecasts can be split into four time scales