Interannual SST Variability in the Japan/East Sea and Relationship with Environmental Variables
SUNGHYEA PARK* and PETER C. CHU
Domain
Complex EOF Analysis
– Sn(x,y): spatial amplitude and phase – PCn(x,y): temporal amplitude and phase
• Fourier Transform• Hilbert Transform • Complex data field• Singular value decomposition• Real / Imaginary
Spatial amplitude and phase
• Spatial amplitude An(x, y) distributions (a) and Spatial phase θn(x, y) distributions (b) of each mode. The contour interval of the amplitude is 0.01°C. Signals propagate toward decreasing phase, and contour interval of the phase is 10° (30°) for the first (second) mode.
Spatial and temporal analysis
(Left) Spatial amplitude An(x, y) distributions using NOAA Optimum Interpolation Sea Surface Temperature dataset with a horizontal grid of 1° × 1° (contour interval is 0.01°C).
(Right) Temporal amplitude Bn(t) variations (a) and temporal phase φn(t) variations (b) of each mode.
Seasonal CEOF
Seasonal CEOF. (a) Spatial amplitude (contour interval is 0.01°C), and (b) temporal variation at the grid with a maximum spatial amplitude: (137.5°E, 39.7°N) for the winter first mode, (134.3°E, 41.5°N) for the summer first mode, (128.8°E, 39.4°N) for the winter second mode, and (139.9°E, 46.3°N) for the summer second mode.
Propagation
Evolutions of the second mode SSTA over mid-1987~mid-1993 with an interval of 80 days. Phase changes from 360° to 0°. Time instance is recorded as the fraction of a year; e.g., the fraction 1987.5 indicates mid-1987. Contour interval is 0.2°C. Black (white) contours indicate negative (zero and positive) anomaly.
Comparisons to the climate indices
• Lag correlation coefficients between the climate indices and the n-th mode JES SSTA, where negative lag indicates that the climate indices lead JES SSTA. (a) First mode, and (b) second mode.
Regression to other variations
Regression to other variations
Top Related