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Martin L. M. Wong

1. Introduction Shallow-water theory predicts that equatorial waves are governed by certain dispersion relations ( Matsuno 1966 ). Observational identification of these waves and verification of the dispersion relations require analysis in both the frequency and (zonal) wavenumber domain. Using Fourier analysis, Wheeler and Kiladis (1999 , hereafter WK99 ) obtained wavenumber–frequency spectra of the outgoing longwave radiation (OLR). The results provide evidences for the existence of

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Y. Ramanatnan, Padma Kulkarni, and D. R. Sikka

1318 JOURNAl, OF APPLIEI) METEOROLOGY VOLUMEllA Comparative Study of Fourier Analysis Procedure and Cressman's Method in Obiective Analysis of the Wind Field-. RAMANATHAN, PADMA KULKARNI A~;D D. R. $IKKAIndian Institute o.f Tropical Meteorology, POOHS(Manuscript received 10 May 1972, in revised form 14 August 1972)ABSTRACT The value of a meteorolog4cal parameter at a grid point can be derived from

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Yonggang Liu, X. San Liang, and Robert H. Weisberg

1. Introduction Wavelet analysis may be advantageous over the classical Fourier analysis in that it unfolds a time series not only in frequency but also in time, which is especially useful when the signal is nonstationary. Because of this property, wavelet analysis has been widely applied across disciplines since its introduction in the early 1980s. See Daubechies (1992) , Chui (1992) , Meyer (1992) , Strang and Nguyen (1997) , Percival and Walden (2000) , and references therein, for a

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Steven A. Lack, George L. Limpert, and Neil I. Fox

Fourier transform–based object identification scheme that results in the delineation of objects at a range of spatial scales is included here, as well as means of dealing with unequal numbers of objects in the forecast and observed fields, and weighting of error components to provide comparable quantitative values. Section 3 contains the results of a controlled set of “fake” forecasts used to test the system, which include a series of idealized geometric objects and perturbed forecasts. Section 4

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Guy Cautenet, Michel Legrand, Yaya Coulibaly, and Christian Boutin

MARCH 1986 CAUTENET, LEGRAND, COULIBALY AND BOUTIN 277Computation of Ground Surface Conduction Heat Fluxby Fourier Analysis of Surface TemperatureGUY CAUTENET, MICHEL LEGRAND AND YAYA COULIBALY Ddpartement de Physique, Facultd des Sciences, Abidjan, Cote d'lvoire CHRISTIAN BOUTINLAMP-IOPG, Universitd de Clermont-Ferrand, Aubiere, France(Manuscript received 20 February 1985, in final form 17 August 1985)ABSTRACT A method for

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D. Gautier and I. Revah

MA-1975 D. GAUTIER AND I. REVAH 881Sounding of Planetary Atmospheres: A Fourier Analysis of the Radiative Transfer Equation D. GAuz~R Groupe Plan~tes, Obse. rvatoire de Meudon, France I. R~v^aCentre ~ ational d'Etudes des TgI~communlcations, Issy Les Moulineaux, France(Manuscript received 3 October 1974, in revised form 23 January 1975)ABSTRACT In

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D. Brent McRoberts and John W. Nielsen-Gammon

properties of the radar precipitation estimates. This self-reliance means that gauge data, which were not used at all in either the beam blockage detection or the QPE adjustment, can be used as an independent data source to assess the validity of the algorithm. At each grid cell, the algorithm computed a time series of B GC to assess the underestimation bias related to beam blockage, using the Fourier series analysis as a reference to do so. Where gauges are available, we can similarly assess the gauge

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Cheng Sun and Jianping Li

of circulation variability in the SH. Space–time spectral analysis is an effective tool with which to investigate the space–time characteristics of atmospheric circulation. In early studies, information was obtained by a one-dimensional (1D) Fourier analysis of the field at a given latitude or of the latitudinally averaged field, followed by computation of the time–power spectrum of each spatial Fourier component ( Kao 1968 ; Hayashi 1979 ; Dell'Aquila et al. 2007 ). However, the meridional

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Clement Guilloteau, Efi Foufoula-Georgiou, Pierre Kirstetter, Jackson Tan, and George J. Huffman

. Spectral representations such as the Fourier transform or wavelet transform are designated tools to analyze the dynamics of spatiotemporal variables ( Yiou et al. 1996 ; Kyriakidis and Journel 1999 ; Oreopoulos et al. 2000 ; Harris et al. 2001 ; Ghil et al. 2002 ). In particular, using a multidimensional space–time spectral analysis allows one to consider jointly spatial and temporal dynamics. Unlike the sample statistics, the space–time Fourier spectral analysis provides information on the size

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Oliver T. Schmidt, Gianmarco Mengaldo, Gianpaolo Balsamo, and Nils P. Wedi

Atlantic region. Similarly, Mac Veigh et al. (1987) applies EOF to wind stress curl over the North Atlantic. Gamage and Blumen (1993) present a wavelet- and a Fourier-based EOF to capture localized low-level cold fronts, and compare them against traditional EOF. Kawamura (1994) applies a varimax-rotated empirical orthogonal function analysis to monthly mean sea surface temperature anomalies. Brunet (1994) generalizes the EOF theory in the context of normal modes on unidirectional sheared flows

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