A new coupled global NCEP Reanalysis for the period 1979-present is now available, at much higher temporal and spatial resolution, for climate studies. T he first reanalysis at NCEP (all acronyms are defined in the appendix), conducted in the 1990s, resulted in the NCEP-NCAR reanalysis (Kalnay et al. 1996), or R1 for brevity, and ultimately covered many years, from 1948 to the present (Kistler et al. 2001). It is still being executed at NCEP, to the benefit of countless users for monthly, and even daily, updates of the current state of the atmosphere. At the same time, other reanalyses were being conducted, namely, ERA-15 (Gibson et al. 1997) was executed for a more limited period (1979-93) at the ECMWF, COLA conducted a short reanalysis covering the May 1982-November 1983 period (Paolino et al. 1995), and NASA GSFC conducted a reanalysis covering the 1980-94 period (Schubert et al. 1997). The general purpose of conducting reanalyses is to produce multiyear global state-of-the-art gridded representations of atmospheric states, generated by a constant model and a constant data assimilation system. To use the same model and data assimilation over a very long period was the great advance during the 1990s, because gridded datasets available before 1995 had been created in real time by ever-changing models and analysis methods, even by hand analyses prior to about 1965. The hope was that a reanalysis,

The second version of the NCEP Climate Forecast System (CFSv2) was made operational at NCEP in March 2011. This version has upgrades to nearly all aspects of the data assimilation and forecast model components of the system. A coupled reanalysis was made over a 32-yr period , which provided the initial conditions to carry out a comprehensive reforecast over 29 years . This was done to obtain consistent and stable calibrations, as well as skill estimates for the operational subseasonal and seasonal predictions at NCEP with CFSv2. The operational implementation of the full system ensures a continuity of the climate record and provides a valuable up-to-date dataset to study many aspects of predictability on the seasonal and subseasonal scales. Evaluation of the reforecasts show that the CFSv2 increases the length of skillful MJO forecasts from 6 to 17 days (dramatically improving subseasonal forecasts), nearly doubles the skill of seasonal forecasts of 2-m temperatures over the United States, and significantly improves global SST forecasts over its predecessor. The CFSv2 not only provides greatly improved guidance at these time scales but also 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 for rivers and agriculture, transportation, energy use by utilities, wind and other sustainable energy, and seasonal prediction of the hurricane season.

The Climate Forecast System (CFS), the fully coupled ocean–land–atmosphere dynamical seasonal prediction system, which became operational at NCEP in August 2004, is described and evaluated in this paper. The CFS provides important advances in operational seasonal prediction on a number of fronts. For the first time in the history of U.S. operational seasonal prediction, a dynamical modeling system has demonstrated a level of skill in forecasting U.S. surface temperature and precipitation that is comparable to the skill of the statistical methods used by the NCEP Climate Prediction Center (CPC). This represents a significant improvement over the previous dynamical modeling system used at NCEP. Furthermore, the skill provided by the CFS spatially and temporally complements the skill provided by the statistical tools. The availability of a dynamical modeling tool with demonstrated skill should result in overall improvement in the operational seasonal forecasts produced by CPC. The atmospheric component of the CFS is a lower-resolution version of the Global Forecast System (GFS) that was the operational global weather prediction model at NCEP during 2003. The ocean component is the GFDL Modular Ocean Model version 3 (MOM3). There are several important improvements inherent in the new CFS relative to the previous dynamical forecast system. These include (i) the atmosphere–ocean coupling spans almost all of the globe (as opposed to the tropical Pacific only); (ii) the CFS is a fully coupled modeling system with no flux correction (as opposed to the previous uncoupled “tier-2” system, which employed multiple bias and flux corrections); and (iii) a set of fully coupled retrospective forecasts covering a 24-yr period (1981–2004), with 15 forecasts per calendar month out to nine months into the future, have been produced with the CFS. These 24 years of fully coupled retrospective forecasts are of paramount importance to the proper calibration (bias correction) of subsequent operational seasonal forecasts. They provide a meaningful a priori estimate of model skill that is critical in determining the utility of the real-time dynamical forecast in the operational framework. The retrospective dataset also provides a wealth of information for researchers to study interactive atmosphere–land–ocean processes.

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A new global coupled atmosphere-ocean forecast system model (CFS03) has recently been developed at the National Centers for Environmental Prediction (NCEP). The new coupled model consists of a T62L64 version of the operational NCEP Atmospheric Global Forecast System model and the Geophysical Fluid Dynamics Laboratory Modular Ocean Model version 3, and is expected to replace the current NCEP operational coupled seasonal forecast model. This study assesses the performance of the new coupled model in simulating El Niño-Southern Oscillation (ENSO), which is considered to be a desirable feature for models used for seasonal prediction. The diagnoses indicate that the new coupled model simulates ENSO variability with realistic frequency. The amplitude of the simulated ENSO is similar to that of the observed strong events, but the ENSO events in the simulation occur more regularly than in observations. The model correctly simulates the observed ENSO seasonal phase locking with the peak amplitude near the end of the year. On average, however, simulated warm events tend to start about 3 months earlier and persist longer than observed. The simulated ENSO is consistent with the delayed oscillator, recharge oscillator, and advective-reflective oscillator theories, suggesting that each of these mechanisms may operate at the same time during the ENSO cycle. The diagnoses of the simulation indicate that the model may be suitable for real-time prediction of ENSO.