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| 最大共分散解析× | 経験的直交テレコネクション× | WRFモデル× | |
|---|---|---|---|
| 分野 | 気象学 | 気象学 | 気象学 |
| 系統 | Process / pipeline | Process / pipeline | Process / pipeline |
| 提唱年≠ | 1992 | 1956 | 2000 |
| 提唱者≠ | Bretherton, Wallace | Lorenz, Wallace | Skamarock and Klemp |
| 種類≠ | Covariance decomposition method | Data analysis and pattern identification | Atmospheric simulation system |
| 原典≠ | Bretherton, 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 ↗ | Skamarock, W. C., Klemp, J. B., Dudhia, J., et al. (2008). A Description of the Advanced Research WRF Version 3. NCAR Technical Note NCAR/TN-475+STR. link ↗ |
| 別名 | MCA, Singular value decomposition, SVD analysis, Covariance analysis | EOF analysis, Empirical orthogonal function, Teleconnection patterns, PCA meteorology | Weather Research and Forecasting, WRF, ARW, NMM |
| 関連≠ | 2 | 2 | 4 |
| 概要≠ | Maximum 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. | The Weather Research and Forecasting (WRF) model is a mesoscale atmospheric simulation system used for weather forecasting, research, and climate applications. Developed cooperatively by NCAR, NOAA, and academic institutions, WRF became operational in 2004 and has become one of the most widely used atmospheric models worldwide. |
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