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Xiaolin Zhang and Allan J. Clarke

where correlations are lower the least squares regression coefficient is biased.] Zonal current monthly anomalies for all three datasets were filtered with a Trenberth (1984) , 11-point, symmetric, nonrecursive, interannual filter and then a separate EOF analysis done on each. In all three cases, the first EOF describes over 80% of the variance ( Fig. 11 ). The principal components are highly correlated, and the meridional structures are similar, indicating that, at least at 156°E, much of the

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Ian A. Renfrew, G. W. K. Moore, Peter S. Guest, and Karl Bumke

temperature to within 0.5°C. Longwave and shortwave radiative fluxes were also measured. The IMET data were sampled every second, with 15-s averages stored. For analysis purposes, records of 5-min averages were generated. For comparison with the model analyses, 6-hourly “instant” and “average” time series have been created. The 5-min data are used to create the instant time series. The same data are averaged into 6-h periods, starting at the reference time, to create the average time series. These data

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Lixin Qu and Robert Hetland

in Fig. 7 (right); the offset between σ ^ NG | δ = 0 and σ ^ NG,Flat Asym is presumably due to the approximation and truncation of the asymptotic analysis of Stone (1970) . But both the analytical and numerical solutions suggest that (1 + Ri −1 ) −1/2 is the controlling number in the nongeostrophic limit with flat bathymetry. Fig . 7. (a) Normalized maximum growth rates, σ ^ BG and σ ^ M , as functions of δ r − 1 . Gray dashed lines are the linear regression; y = 0.301 x + 0

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Barbara-Ann Juszko, Richard F. Marsden, and Sherman R. Waddell

. (6).Since the rms sea height showed the largest correlationwith u,, we have included Fig. 6d, which shows thescatterplot of (f4E(f)) against u,, with the averagingperformed over the same frequency range as (S(f)),and the accompanying regression values are listed inTable 1. There are two features to note: 1 ) fewer recordsthan in the (S(f)) analysis could be included due tothe occurrence of unrealistically large values of(f4E(f)) and 2) there is a marked increase in thenoise level and

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Ellen D. Brown and W. Brechner Owens

1,~74 JOURNAL OF PHYSICAL OCEANOGRAPHYObservations of the Horizontal Interactions between the Internal Wave Field and the Mesoscale Flow~ ELLEN D. BROWN AND W. BRECHNER OWENSWoods Hole Oceanographic Institution, Woods Hole. MA 02543(Manuscript received I December 1980, in final form 17 $uly 1981)ABSTRACT Momentum and energy transfers from the mesoscale horizontal velocity shear to the internal wavefield have been deduced from an analysis of a closely

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

(up to 28) profilesfrom cruises in summer 1985. The stability, and representativeness, of the eofs in the upper 300 m, calculated from only 11 profiles, is remarkable, as shownby a comparison with eofs calculated from 460 shallowprofiles in module 0, Fig. 8c. The principal componentsof each subprofile were regressed onto the principalcomponents of the full profile eofs (see appendix A).In this way, the signal in the upper water column wasused to estimate, by regression analysis, the signal below

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F. L. Scarpace and T. Green III

periodicities. Trans. Amer. Geophys, Union, 36, 1073-1084. - and E.J. Hannan, 1968: Time series regression of sea level on weather. Rev. Geophys. 6, No. 2, 129-174. Hickey, Barbara, 1975: The relationship between fluctuations in sea level, wind stress, and sea surface temperature in the Equatorial Pacific. J. Phys. Oceanogr., 6, 460-475. Lisitzen, Eugenie, 1974: Sea-Level Changes. Elsevier, 286 pp. Reid, Joseph L., and Arnold W. Mantyla, 1976: The effect of the geostrophic flow upon coastal sea

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J. A. Battjes, T. J. Zitman, and L. H. Holthuusen

in thedirection of wave propagation at the spectral peak. Withthe approximation cos0 m 1, we have &m m 2*r~, inwhich case substitution of (B4) into (B3) gives /~ = 0.006(2;r)--'45Cd--'%--'45 ~ 0.068 ~-o.4~. (B5) REFERENCESDonelan, M. A., J. Hamilton and W. H. Hui, 1985: Directional spectra of wind-generated waves. Phil. Trans. Roy. Soc. London, A315, 509-562.Draper, N. R., and H. Smith, 1981: Applied Regression Analysis, 2nd ed., Wiley.Forristall, G. Z., 1981: Measurements

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Gary S. E. Lagerloef

mode method is based on the regression of integrated temperature profiles on the set ofvertical modes as a means of estimating the EOF amplitudes of those modes. It is thus anticipated that reduction in the rms error will occur with increasing thenumber of modes in the analysis, as finer details of thevertical structure are included. On a statistical basis,only one or two modes would be justified. It was found,however, that use of six modes improved the fit byabout 10% over the use of a single mode

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J. H. Churchill and G. T. Csanady

near-shore currentshowed no appreciable velocity between the drogueand the surrounding water. c. Data analysis Drogue and ship positions were calculated by a nonlinear regression technique which included all three slant ranges. Each position calculated by this method minimizes the quantity 3 SS = ~ (SLi - sri)2, (4) i=1 where SLi is the slant range between transponder i and the drogue or ship hydrophone, as

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