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E. Kalnay, M. Kanamitsu, and W.E. Baker

In this paper we describe the global numerical weather prediction system of the National Meteorological Center, and review recent improvements, the evolution in skill, and current research projects and plans.

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E. Kalnay, Kingtse C. Mo, and J. Paegle


Studies by van Loon and Jenne, van Loon et al., Trenberth and others indicate that stationary waves in the Southern Hemisphere are dominated by planetary scales. Kalnay and Halem reported the presence of large amplitude, short-scale stationary waves during the month of January 1979 in the lee of South America and their disappearance in February 1979. In this paper we present further observational evidence of the January waves.

We also perform two 15-day forecast experiments with the GLAS Fourth-Order General Circulation Model, and initial conditions corresponding to 5 January and 4 February 1979. These factors reproduce reasonably well the presence of the January waves and their absence in February. Several mechanistic experiments to determine the origin of the waves are then performed.

The principal conclusions are

a) Large amplitude stationary Rossby waves with zonal wavenumber ≈7 were present between 20° and 40°S both in the South Pacific and east of South America during January 1979. They appear in satellite observations as enhanced bands of high clouds associated with the South Pacific Convergence Zone (SPCZ) and the Amazon. Examination of satellite observations during 1974–79 indicates a correlation between the intensity of stationary cloud bands in the two regions.

b) The stationary waves in the lee of South America are not of orographic origin since they are associated with a ridge rather than a trough east of the Andes. A “no Andes” forecast experiment confirms this argument.

c) The waves could not be produced by a CISK mechanism suggested by Kalnay and Halem, because of their rather barotropic vertical structure. Sea surface temperature (SST) anomalies in the South Atlantic were of the same scale as the waves, but stronger at the end of January. This, and strong correlation between low level atmospheric cyclonic vorticity and cold SST anomalies indicate that the atmospheric stationary waves were the cause of the ocean temperature anomalies, which in turn provided a negative feedback to the atmosphere.

d) Several experiments modifying the coefficient of latent heat lead to the conclusion that tropical heating is important in the maintenance of the waves. Furthermore, the convection in the subtropical waves themselves is important in sustaining their amplitude and phase, and the Walker type of circulation associated with the SPCZ is also a contributor to the maintenance of the South American waves. These results confirm the existence of a relationship between the occurrence of a strong South Pacific Convergence Zone, somewhat eastward from its climatological position, and the strong “South Atlantic Convergence Zone” observed in outgoing longwave radiation maps.

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M. Kanamitsu, K. C. Mo, and E. Kalnay


The NMC Global Spectral Model was integrated for one year. The model used is the same as the 1989 operational medium range forecast model except that the horizontal resolution was reduced from T80 to T40. Overall, the model was very successful in reproducing most of the characteristics of the atmospheric circulation and its seasonal evolution.

A comparison with the summer and winter integrations of Kinter et al., which were performed with the NMC model operational in 1985, shows that the changes made in the last few years in the NMC model have significantly improved its ability to reproduce the atmospheric circulation, particularly in the tropics and in the summer hemisphere. The simulation of precipitation is also much more realistic with the present model.

We also performed a 150 day simulation with a lower resolution (R16) version of the model. The stationary and transient eddy simulations were similar to that of T40 model but the zonal circulation was much poorer in the R16 model, particularly in the Southern Hemisphere. This indicates that for a global simulation study a horizontal resolution of at least T40 is necessary.

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M. Halem, E. Kalnay, W. E. Baker, and R. Atlas

This study investigates the degree to which data from the space-borne FGGE observing systems are able to determine the complete state of the atmosphere when incorporated into a global objective analysis cycle. Three data assimilation experiments are performed with the Goddard Laboratory for Atmospheric Sciences (GLAS) analysis/forecast system, using different combinations of the FGGE level II–b data collected during the first Special Observing Period (SOP-1), 5 January through 5 March 1979. The control experiment is an assimilation cycle with the complete FGGE II–b data. The other two assimilation/forecast experiments consist of i) the conventional system without the satellite data and special FGGE data sets; and ii) the FGGE II–b surface and satellite temperature soundings and cloud-track winds, aircraft data, and special FGGE data sets, but without the conventional rawinsonde/pilot balloon network.

From these experiments, we attempt to assess the accuracy of the inferred mass and motion fields over data-sparse regions, by examining their influence on analyses and forecasts over data-rich regions. The sensitivity of the analysis to the FGGE satellite data is shown by comparisons of the 6 h forecast error of the 300 mb geopotential height fields for these three experiments. It is found that large 6 h forecast errors downstream of data-sparse regions are reduced when the satellite observations are incorporated in the analysis. Forecast impact results from the initial states of these assimilation cycles show the geographical influence of the FGGE satellite observing system on short- to medium-range (two to five days) weather forecasting. Over North America and Europe, there is a small improvement in forecast skill from the use of the FGGE II–b data. Over Australia, as expected, the positive impact of satellite data is much larger. The number of skillful four- and five-day forecasts over North America and Europe has been increased substantially by the addition of the FGGE II–b data. Examples of useful eight-day forecasts, which occurred in periods of atmospheric blocking situations also are presented.

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Kingtse C. Mo, J. R. Zimmerman, E. Kalnay, and M. Kanamitsu


June 1988 has been classified as one of the hottest and driest months on record in the United States. This study used the NMC Medium-Range Forecast(MRF) T40 model to simulate circulation features of June 1988 and to investigate the relationship between sea surface temperature anomalies (SSTA) and circulation patterns in the Northern Hemisphere. Three control experiments have been performed using three different initial conditions, separated by one day (21, 22, and 23 May 1988) and using SSTA fixed at the starting date. The three forecasts, and their average, are remarkably skillful in the Northern Hemisphere. The observed anomaly of June 1988, a wave train with a persistent ridge in the north-central United States and a northward shifting of the jet stream in the Pacific–North America area, is very well simulated in each of the integrations. All three experiments were repeated using the same initial conditions, but with climatological SST. The wave train generated is similar to that in the control experiments, but it is not as robust. The simulated jet streams are also similar to those in the control experiments. Two experiments with the 1988 SSTA, but with initial conditions of 22 May 1987 and 22 May 1989 were also run. The circulation patterns generated by these runs are very different from those of 1988, indicating that the persistence of the anomalous ridge in the north-central United States after late May 1998 was not due to the SSTA of the May 1988 alone.

A barotropic analysis was done to obtain the normal modes associated with the 300-mb streamfuncton of the June climatology. The analysis indicates the existence of a slowly growing mode with structure similar to the anomalies of 1988. This result, as well as the numerical experiments, suggests that the persistence of the June 1988 wave train may be associated with initial conditions, which were in a rather stable regime. The SSTA may have helped to strengthen the pattern, but the wave train associated with the 1988 drought could not have been generated by SSTA alone.

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R. Balgovind, A. Dalcher, M. Ghil, and E. Kalnay


A simple model that yields the spatial correlation structure of global atmospheric mass-field forecast errors is derived. The model states that the relative potential vorticity of the forecast error is forced by spatially multi-dimensional white noise. The forecast error equation contains a nondimensional parameter c 0, which depends on the Rossby radius of deformation. From this stochastic-dynamic equation, a deterministic equation for the spatial covariance function of the 500 mb geopotential error field is obtained.

Three methods of solution are examined: 1) an analytic method based on spherical harmonics, 2) a numerical method based on stratified sampling of Monte-Carlo realizations of the stochastic-dynamic equation, and 3) a combined analytic-numerical method based on two successive applications of a fast Poisson solver to the deterministic covariance equation. The three methods are compared for accuracy and efficiency, and the third (combined) method is found to be clearly superior.

The model's covariance function is compared with global correlation data of forecast-minus-observed geopoteniial fields for the DST-6 period February–March 1976. The data are based on the GLAS forecast-assimilation system in use at that lime (Ghil et al., 1979).

The model correlations agree well with the latitude dependence of the data correlations. The fit between model and data confirms that the forecast error between 24 and 36 h is largely random, rather than systematic; the value of the parameter c 0 which gives the best fit suggests that much of this error can be attributed to baroclinic, rather than barotropic effects. Deterministic influences not included in the model appear at 12 and 48 h. They suggest possibilities of improving the forecast system by a better objective analysis and initialization procedure, and a better treatment of planetary-wave propagation, respectively.

An analytic formula is obtained which locally approximates well the model's global correlations. This formula is convenient to use in the calculation of weighting coefficients for analysis and assimilation schemes. It shows that Gaussian functions are a poor approximation for the forecast error correlations of the mass field, and their derivatives an even poorer approximation to wind field correlations.

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K. C. Mo, X. L. Wang, R. Kistler, M. Kanamitsu, and E. Kalnay


In preparation for the execution of the National Meteorological Center and National Center for Atmospheric Research (NMC/NCAR) Reanalysis Project, which will cover the period 1958–93, the impact of satellite data on both analyses and forecasts has been assessed. This was done by diagnosing two sets of analyses and forecasts made with and without the use of satellite data (SAT and NOSAT) within the data assimilation. The analyses and forecasts were performed using a state-of-the-art global data assimilation system and were evaluated for August 1985.

The impact of satellite data is smaller than that obtained in previous impact studies during the First GARP (Global Atmospheric Research Program) Global Experiment (FGGE) that took place in 1979, reflecting the effect of improvements that have been implemented in the global analysis scheme and the model. In the Northern Hemisphere (NH), there are no significant differences between SAT and NOSAT analyses for both primary variables and eddy transports. The satellite impact on the forecasts in the NH is positive but very small, reaching about 1% in the 5-day forecasts, as measured by the average rms errors and anomaly correlations. In the Southern Hemisphere (SH), the difference between the SAT and NOSAT analyses is estimated to be equivalent to the difference between 1.5-day SAT forecasts and the verifying analyses. After 5 days, the SAT forecasts are shown to be superior to the NOSAT forecasts by about 1 day, an advantage apparent whether they are verified against SAT or NOSAT analyses. A comparison of SAT and NOSAT analyses suggests that the NOSAT captures well over 90% of the valiance of monthly mean stationary waves of the SAT analyses in most of the Tropics and Southern Hemisphere from 20° to 60°S. The daily variability is captured at 70%–90% in the Tropics and Southern Hemisphere, except above 200 hPa and south of 60°S.

In several earlier satellite data impact studies performed using FGGE (1979) data, it was observed that satellite data, which cannot resolve smaller-scale features, have a damping effect on the apparent atmospheric circulation. With the improvements in data assimilation methods, it is seen that the smoothing effect is much less apparent. A comparison of the SAT and NOSAT monthly tropical precipitation derived from the 0–6-h forecast cycle shows a general agreement with the rain estimates from satellite data.

Overall, these results am very encouraging, indicating that a reanalysis spanning the years before and after satellite data was available should be useful. In the NH, the analyses are basically unaffected by the satellite data. Even in the SH a large component of both the monthly and the daily anomalies can be captured in the absence of the satellite data, except in the stratosphere and Antarctic region.

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S-C. Yang, E. Kalnay, M. Cai, M. Rienecker, G. Yuan, and Z. Toth


The breeding method has been implemented in the NASA Seasonal-to-Interannual Prediction Project (NSIPP) coupled general circulation model (CGCM) with the ultimate goal of improving operational seasonal to interannual climate predictions through ensemble forecasting and data assimilation. This is the first attempt to isolate the evolving ENSO instability and its corresponding global atmospheric response in a fully coupled ocean–atmosphere GCM. The results herein show that the growth rate of the coupled bred vectors (BVs) is sensitive to the ENSO phases of the evolving background flow and peaks about 3 months before an ENSO event. The structure of the dominant growing BV modes also evolves with the background ENSO and exhibits a larger amplitude in the eastern tropical Pacific, reflecting the natural dynamical sensitivity associated with the shallow thermocline at the eastern boundary. The key features of coupled bred vectors of the NSIPP CGCM are reproduced when using the NCEP CGCM, an independently developed coupled general circulation model.

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E. Kalnay, M. Kanamitsu, J. Pfaendtner, J. Sela, M. Suarez, J. Stackpole, J. Tuccillo, L. Umscheid, and D. Williamson
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R. Daley, A. Hollingsworth, J. Ploshay, K. Miyakoda, W. Baker, E. Kalnay, C. Dey, T. Krishnamurti, and E. Barker

A set of tables has been prepared which allows side-by-side comparison of the characteristics of six data assimilation systems (ECMWF, GFDL, GLAS, NMC, FSU, and NEPRF) used to produce FGGE IIIb analyses.

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