Spectral Decomposition of Two-Dimensional Atmospheric Fields on Limited-Area Domains Using the Discrete Cosine Transform (DCT)

By B. Denis, Jean Côté, René Laprise. 2002

242 citations recorded by the source corpus.

For most atmospheric fields, the larger part of the spatial variance is contained in the planetary scales. When examined over a limited area, these atmospheric fields exhibit an aperiodic structure, with large trends across the domain. Trying to use a standard (periodic) Fourier transform on regional domains results in the aliasing of largescale variance into shorter scales, thus destroying all usefulness of spectra at large wavenumbers. With the objective of solving this particular problem, the authors have evaluated and adopted a spectral transform called the discrete cosine transform (DCT). The DCT is a widely used transform for compression of digital images such as MPEG and JPEG, but its use for atmospheric spectral analysis has not yet received widespread attention. First, it is shown how the DCT can be employed for producing power spectra from two-dimensional atmospheric fields and how this technique compares favorably with the more conventional technique that consists of detrending the data before applying a periodic Fourier transform. Second, it is shown that the DCT can be used advantageously for extracting information at specific spatial scales by spectrally filtering the atmospheric fields. Examples of applications using data produced by a regional climate model are displayed. In particular, it is demonstrated how the 2D-DCT spectral decomposition is successfully used for calculating kinetic energy spectra and for separating mesoscale features from large scales.

Subfields: Atmospheric Science, Global and Planetary Change

View Paper: https://www.semanticscholar.org/paper/01027afea02572d8d72f649951c3b6f5ed14f0ce

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Citations in the corpus

Downscaling ability of one-way nested regional climate models: the Big-Brother Experiment (2001, background): “Readers are referred to Staniforth (1997) for a theoretical discussion and to Davies and Turner (1977) , Baumhefner and Perkey (1982), Robert and Yakimiw (1986) and Yakimiw and Robert (1990) for basic validation experiments of some nesting formulations.”
Flow‐dependent background‐error covariances for a convective‐scale data assimilation system (2012, background): “(1997) and Derber and Bouttier (1999) for global NWP systems, and adapted by Berre (2000) for limited-area NWP systems.”
NOTES AND CORRESPONDENCE A Spatial Two-Dimensional Discrete Filter for Limited-Area-Model Evaluation Purposes (2005, methodology): “The discrete cosine-filter method suggested by Denis et al. (2002) is better in describing spatial trends, but it also maps all variability on wavy components, so that any recombination of a subset of these components, which is needed for formulating a filter, may generate artificial wavy contributi”
Mesoscale to submesoscale transition in the California current system. Part III: Energy balance and flux (2008, methodology): “…residual to the momentum discrepancy associated with barotropic mode splitting in the time integration of ROMS 2 An alternative approach consists of periodizing the fields to be analyzed by two mirror symmetries; this amounts to performing a discrete cosine transform (DCT) [Denis et al. (2002)].”
Regional climate model sensitivity to domain size (2006, methodology): “The methodology presented here is inspired from Denis et al. (2002b) in order to use the "BigBrother" protocol for testing the sensitivity of a RCM to the size of its domain.”
Spectral nudging in a spectral regional climate model (2008, methodology): “…the regional climate models several studies used idealized experiments, among which the so-called ‘Big Brother Experiment’ approach developed by Denis et al. (2002b) (see also de Elı́a et al., 2002; Denis et al., 2003; Antic et al., 2004; Dimitrijevic and Laprise, 2005; Herceg et al., 2006).”
Background‐error covariances for a convective‐scale data‐assimilation system: AROME–France 3D‐Var (2011, methodology): “These spectra have been computed in both DA systems using a discrete cosine transform (Denis et al., 2002).”