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James C. Mcwilliams and Colin Y. Shen

covariances between modalstreamfunction and velocity fields. The former is found to be approximately zero and the latter havesignificant extrema at lag distances comparable to an eddy radius. Furthermore, the dominant contribution to these coupling signals comes from the time-averaged (over a little more than two months) mesoscale field, which from lengthy moored observations we can identify as an instantaneous realization ofthe very low frequency "secular scale" described by Schmitz (1978). Forecasts

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James A. Carton, Gennady Chepurin, Xianhe Cao, and Benjamin Giese

model forecast and its effects on the analysis. We then use SODA to construct a retrospective analysis of temperature, salinity, and current in the upper layers of the ocean globally during the past five decades. The constraint algorithm is based on optimal interpolation data assimilation. This technique uses a numerical forecast model to provide a first guess of the mass and momentum field at each analysis time. Statistical estimates of the forecast error are computed a priori and are assumed to be

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Shi Jiang and Michael Ghil

techniques widely used in current numerical prediction systems, such as optimal interpolation (hereafter OI, Gandin 1963), incorporate observations into models in terms of empirical correlationfunctions and cannot be expected to preserve a fullrange of physical relationships. In fact, an inadequatespecification of the correlation functions could seriouslydamage the accuracy of predictions and sometimeseven result in failure of forecasts. For example, a disastrous coastal storm over England in October

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Mojib Latif and Nicholas E. Graham

upper-ocean temperatures in the tropical Pacific has been used as a predictor in a statisticalprediction scheme to forecast SST anomalies in this region. The temperature variations were taken from theoutput of an oceanic general circulation model that was forced by observed winds for the period 1961 to 1985.Since such model data are presently used as initial conditions in prediction experiments with coupled oceanatmosphere models, it is of particular interest to investigate up to what lead time

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Werner Kramer, Henk A. Dijkstra, Stefano Pierini, and Peter Jan van Leeuwen

observations procedures and issues, see Langland (2005) . An objective procedure, based on, for example, singular vectors, is used to determine regions with fast-growing initial errors. A targeted observation is considered, when the forecast error can be decreased by assimilating additional observation data. Baker and Daley (2000) argued that none of the traditional techniques consider the characteristics of the data-assimilation systems used. As such, interaction with the background field of the

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Tal Ezer and George L. Mellor

withoutassimilation. A more detailed description of the OTISsystem is given later. Experiments by Ezer et al. (1992), using the OTISdata to initialize the same model presented here,showed some forecast skill, better than persistence (aforecast based on no change), for at least two weeks.The evaluation of the assimilation technique is especially difficult because of the differences in the variability of the OTIS fields and the Geosat altimeter data,as indicated by Ezer et al. (1993). However, it providesa first

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Warren B. White, Stephen E. Pazan, and Masamichi Inoue

significant peak in that yearmay be due to limitations on this technique imposedby computational restrictions (see Appendix); this limitation may be alleviated in the future. The model forecasting index is trending upwards at the end of 1985,indicating an ENSO event in 1986; at the time of thiswriting (i.e., March 1986), a weak event appears to beoccurring in the eastern tropical Pacific.7. Conclusions The results contained in Fig. 14 are a statistical verification of a known linear dynamical

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P. E. Dexter

have been developed for hindcasting orforecasting sea waves which result from given surfacewind fields. Initially these techniques were manual,requiring the services of a skilled "wave forecaster,"but the need to provide forecast (hindcast) data overlarge ocean areas, the desire to remove the subjectivityinherent in manual methods, the general amenabilityof wave generation and decay functions to numericalcomputational methods, and the continued improvement in computing capabilities, have all led to

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Michele M. Rienecker, Christopher N. K. Mooers, and Allan R. Robinson

root-mean-squaredifference (determined by a linear least-squares regression of the forecast values on the data, giving theregression estimate, f)and an unsystematic root-meansquare difference, defined byRMSU = ((fIn each case in this study, the root-mean-square difference measures is normalized by the standard deviation of the data. REFERENCESBretherton, F. P., R. E. Davis and C. B. Fandry, 1976: A technique for objective analysis and design of oceanographic experiments applied to MODE

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Hervé Giordani, Guy Caniaux, and Louis Prieur

comparison with those in the past because it assimilates directly the current data instead of the mass fields. The technique is also very useful and efficient in preventing strong drifts during long simulations and shocks associated with sequential assimilation data. Nevertheless some limitations of the approach have to be mentioned. Geostrophic currents have to be provided with a forecasting/analysis system or climatologies. Consequently, this model is only viable when nested with a geostrophic currents

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