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Norman A. Phillips

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Norman A. Phillips

Abstract

Variational analysis with a geostrophic constraint is used to estimate a critical accuracy for a satellite lidar wind measuring system. This accuracy is such that the combination of satellite winds with satellite temperatures can produce analyses with an accuracy equal to that obtained from a rawinsonde network. An important assumption allowing this estimate to be made is that the satellite wind and temperature measurements are made with a spatial density equal to that of the rawinsonde network.

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Norman A. Phillips

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The Baer-Tribbia nonlinear modal initialization method implies that large-scale meteorological analyses should focus on analysis of slow mode fields. An idealized multi-variate optimum interpolation analysis is shown to produce grid point results that contain only slow modes. Variational analysis with a slow mode constraint is therefore unnecessary.

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Norman A. Phillips

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An experimental colocation and statistical regression scheme is used to verify the hypothesis that large consistent mean errors in the cloudy oceanic satellite temperature retrievals north of 30°N from TIROS-N are due to a continental bias in the statistical colocation base. Sea surface water temperature is a useful predictor for these conditions. Significant improvement in these retrievals is possible. However, much of this improvement requires the presence in the colocation base of the, mid-ocean radiosondes from the ocean weather ships.

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NORMAN A. PHILLIPS

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A 48-hr. forecast for the entire Northern Hemisphere of a barotropic hydrostatic atmosphere is made with the “primitive equations.” Overlapping Mercator and stereographic grids are used, together with the finite-difference scheme proposed by Eliassen. Initial data corresponded to a Haurwitz-type pattern of wave number 4. The initial wind field was nondivergent and the initial geopotential field satisfied the balance equation. The computations seem to be stable and well behaved, except for two small temporary irregularities. The amplitude of the gravity-inertia waves present in the forecast geopotential field is about 1/30 that of the large-scale field. It can be shown that this is due to the neglect, in the initial data, of the quasi-geostrophically conditioned divergence field. The computational technique itself therefore does not give any unreal prominence to the “meteorological noise.” The computational characteristics and stability criterion of the Eliassen finite-difference system are investigated for a linearized version of the equations.

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Norman A. Phillips and Simon W. Chang

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The principles of variational analysis are reviewed in a symbolic manner, with emphasis on the error introduced by a failure to use an exact constraint. A technique to approximate a nonlinear exact constraint is suggested, with the object of avoiding error magnification in regions of good data, in the process of analyzing slow mode amplitudes for nonlinear mode initialization. The technique amounts to subtractingall fast modes from the data fields that form the input to the variational analysis. The analysis procedure is then focused on only the analysis of slow mode fields. These general considerations are demonstrated by computations with the vortex model of Tribbia, and show how nonlinear mode techniques can improve initial analyses in a more significant way than the mere elimination of noise. A review of the relative merits and weaknesses of optimum interpolation and variational analysis suggests a logical way to use both techniques in an operational analysis system.

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