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,

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

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[1] Evidence is presented that exchanges of water and energy between the vegetation and the atmosphere play an important role in east Asian and West African monsoon development and are among the most important mechanisms governing the development of the monsoon. The results were obtained by conducting simulations for five months of 1987 using a general circulation model (GCM) coupled with two different land surface parameterizations, with and without explicit vegetation representations, referred to as the GCM/vegetation and the GCM/soil, respectively. The two land surface models produced similar results at the planetary scale but substantial differences at regional scales, especially in the monsoon regions and some of the large continental areas. In the simulation with GCM/soil, the east Asian summer monsoon moisture transport and precipitation were too strong in the premonsoon season, and an important east Asian monsoon feature, the abrupt monsoon northward jump, was unclear. In the GCM/ vegetation simulation, the abrupt northward jump and other monsoon evolution processes were simulated, such as the large-scale turning of the low-level airflow during the early monsoon stage in both regions. With improved initial soil moisture and vegetation maps, the intensity and spatial distribution of the summer precipitation were also improved. The two land surface representations produced different longitudinal and latitudinal sensible heat gradients at the surface that, in turn, influenced the low-level temperature and pressure gradients, wind flow (through geostrophic balance), and moisture transport. It is suggested that the great east-west thermal gradient may contribute to the abrupt northward jump and the latitudinal heating gradient may contribute to the clockwise and counterclockwise turning of the low-level wind. The results showed that under unstable atmospheric conditions, not only low-frequency mean forcings from the land surface, such as monthly mean albedo, but also the perturbation processes of vegetation were important to the monsoon evolution, affecting its intensity, the spatial distribution of precipitation, and associated circulation at the continental scale.