ScholarGate
Asistent

Compară metode

Examinează metodele selectate una lângă alta; rândurile care diferă sunt evidențiate.

Analiza Covarianței Maxime×Teleconexiunea Ortogonală Empirică×
DomeniuMeteorologieMeteorologie
FamilieProcess / pipelineProcess / pipeline
Anul apariției19921956
Autorul originalBretherton, WallaceLorenz, Wallace
TipCovariance decomposition methodData analysis and pattern identification
Sursa seminalăBretherton, C. S., Widmann, M., Dymnikov, V. P., Wallace, J. M., & Blade, I. (1992). The effective number of spatial degrees of freedom of a time-varying field. Journal of the Atmospheric Sciences, 49(11), 1063-1083. link ↗Wallace, J. M., & Gutzler, D. S. (1981). Teleconnections in the geopotential height field during the Northern Hemisphere winter. Monthly Weather Review, 109(4), 784-812. DOI ↗
Denumiri alternativeMCA, Singular value decomposition, SVD analysis, Covariance analysisEOF analysis, Empirical orthogonal function, Teleconnection patterns, PCA meteorology
Înrudite22
RezumatMaximum covariance analysis (MCA) is a statistical technique that identifies coupled patterns of variability between two spatially distributed fields (e.g., sea surface temperature and precipitation). Unlike EOF analysis which focuses on variance in a single field, MCA identifies spatial patterns that are maximally correlated between two different fields.Empirical orthogonal function (EOF) analysis is a statistical technique that identifies dominant spatial patterns and temporal variability in atmospheric or oceanic data. When applied to geographically distant locations, EOF analysis reveals teleconnection patterns—coherent patterns of variability that link weather systems across ocean basins and continents.
ScholarGateSet de date
  1. v1
  2. 2 Surse
  3. PUBLISHED
  1. v1
  2. 2 Surse
  3. PUBLISHED

Mergi la căutare Descarcă prezentarea

ScholarGateCompară metode: Maximum Covariance Analysis · Empirical Orthogonal Teleconnection. Preluat la 2026-06-19 de pe https://scholargate.app/ro/compare