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.

No abstract

NCEP's newly developed second-generation operational seasonal forecast system aims at a seamless suite of forecasts and provides much more comprehensive datasets for users.n April 2000, a new dynamical seasonal prediction system was introduced at the National Centers for Environmental Prediction (NCEP; the acronyms used in this paper are summarized in the appendix). The transition to the new system was hastened by a computer fire in September 1999 and subsequent changeover from a Cray C90 to an IBM-SP computer system. This article will be a reference for people who are using the NCEP numerical seasonal forecast products.The first-generation dynamical seasonal prediction model was based on the notion that the seasonal predictability in the Northern Hemisphere extratropics

[1] The upper atmosphere and ionosphere exhibit variability on spatial and temporal scales characteristic of tides and planetary waves originating in the lower atmosphere. To study their generation, vertical propagation, possible nonlinear interactions and effects a new Whole Atmosphere Model (WAM) has been developed as part of the Integrated Dynamics through Earth's Atmosphere (IDEA) project. WAM is a 150-layer general circulation model based on the US National Weather Service's operational Global Forecast System (GFS) model extended upward to cover the atmosphere from the ground to about 600 km. First simulations reveal the presence of migrating and nonmigrating tides modulated at planetary wave periods in the upper atmosphere. Comparisons with observations from the TIMED satellite in the lower thermosphere show that WAM reproduces the seasonal variability of tides remarkably well, including the diurnal eastward harmonic with zonal wavenumber 3 (DE3) recently implicated in the observed spatial morphology of the ionosphere. Citation: Akmaev, R.

Abstract. Here we present the first steps in developing a global multi-model aerosol forecasting ensemble intended for eventual operational and basic research use. Drawing

[1] A whole atmosphere model has been developed to demonstrate the impact of terrestrial weather on the upper atmosphere. The dynamical core is based on the NWS Global Forecast System model, which has been extended to cover altitudes from the ground to 600 km. The model includes the physical processes responsible for the stochastic nature of the lower atmosphere, which is a source of variability for the upper atmosphere. The upper levels include diffusive separation, wind induced transport of major species, and uses specific enthalpy as the dependent variable, to accommodate composition dependent gas constants and specific heats. A one-year model simulation reveals planetary waves explicitly up to 100 km altitude. At higher altitude, multi-day periodicities in the dynamics appear as a modulation of tidal amplitudes, particularly the migrating semi-diurnal tide in the lower thermosphere dynamo region. The penetration of planetary wave periodicities from tropospheric weather into the upper atmosphere can explain terrestrial weather sources of variability in the thermospheric and ionospheric. Citation: Fuller-Rowell, T. J., et al. (2008), Impact of terrestrial weather on the upper atmosphere, Geophys.