Implementation of implicit filters for spatial spectra extraction

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Foilsithe in:Geoscientific Model Development vol. 18, no. 18 (2025), p. 6541-6552
Príomhchruthaitheoir: Nowak, Kacper
Rannpháirtithe: Danilov, Sergey, Müller, Vasco, Liu, Caili
Foilsithe / Cruthaithe:
Copernicus GmbH
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Rochtain ar líne:Citation/Abstract
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022 |a 1991-962X 
022 |a 1991-9603 
024 7 |a 10.5194/gmd-18-6541-2025  |2 doi 
035 |a 3255246783 
045 2 |b d20250101  |b d20251231 
084 |a 123629  |2 nlm 
100 1 |a Nowak, Kacper  |u Alfred Wegener Institute, Helmholtz Center for Polar and Marine Research, Bremerhaven, Germany 
245 1 |a Implementation of implicit filters for spatial spectra extraction 
260 |b Copernicus GmbH  |c 2025 
513 |a Journal Article 
520 3 |a Scale analysis based on coarse graining has been proposed recently as an alternative to Fourier analysis. It is now broadly used to analyze energy spectra and energy transfers in eddy-resolving ocean simulations. However, for data from unstructured-mesh models it requires interpolation to a regular grid. We present a high-performance Python implementation of an alternative coarse-graining method which relies on implicit filters using discrete Laplacians. This method can work on arbitrary (structured or unstructured) meshes and is applicable to the direct output of unstructured-mesh ocean circulation atmosphere models. The computation is split into two phases: preparation and solving. The first one is specific only to the mesh. This allows for auxiliary arrays that are then computed to be reused, significantly reducing the computation time. The second part consists of sparse matrix algebra and solving the linear system. Our implementation is accelerated by GPUs to achieve excellent performance and scalability. This results in processing data based on meshes with more than 10 million surface vertices in a matter of seconds. As an illustration, the method is applied to compute spatial spectra of ocean currents from high-resolution FESOM2 simulations. 
653 |a Fourier analysis 
653 |a Energy spectra 
653 |a Spatial analysis 
653 |a Computation 
653 |a Data processing 
653 |a Spectra 
653 |a Apexes 
653 |a Ocean models 
653 |a Granulation 
653 |a Atmospheric circulation 
653 |a Atmospheric models 
653 |a Ocean currents 
653 |a Illustrations 
653 |a Linear systems 
653 |a Approximation 
653 |a Matrix algebra 
653 |a Boundary conditions 
653 |a Filters 
653 |a Water circulation 
653 |a General circulation models 
653 |a Oceans 
653 |a Ocean circulation 
653 |a Fourier transforms 
653 |a Interpolation 
653 |a Sparse matrices 
653 |a Finite element analysis 
653 |a Unstructured data 
653 |a Geometry 
653 |a Environmental 
700 1 |a Danilov, Sergey  |u Alfred Wegener Institute, Helmholtz Center for Polar and Marine Research, Bremerhaven, Germany 
700 1 |a Müller, Vasco  |u Alfred Wegener Institute, Helmholtz Center for Polar and Marine Research, Bremerhaven, Germany 
700 1 |a Liu, Caili  |u Alfred Wegener Institute, Helmholtz Center for Polar and Marine Research, Bremerhaven, Germany; College of Oceanic and Atmospheric Sciences, Ocean University of China, Qingdao, China 
773 0 |t Geoscientific Model Development  |g vol. 18, no. 18 (2025), p. 6541-6552 
786 0 |d ProQuest  |t Engineering Database 
856 4 1 |3 Citation/Abstract  |u https://www.proquest.com/docview/3255246783/abstract/embedded/6A8EOT78XXH2IG52?source=fedsrch 
856 4 0 |3 Full Text  |u https://www.proquest.com/docview/3255246783/fulltext/embedded/6A8EOT78XXH2IG52?source=fedsrch 
856 4 0 |3 Full Text - PDF  |u https://www.proquest.com/docview/3255246783/fulltextPDF/embedded/6A8EOT78XXH2IG52?source=fedsrch