Principal Component Analysis on Temporal-spatial Variations of Sea Level Anomalies from T/P Satellite Altimeter Data over the Northwest Pacific

Principal Component Analysis, which can reveal maximum temporal-spatial signal structure with a minimum amount of Principal Components (PCs), is used to investigate the temporal-spatial variations of sea level anomalies over the northwest Pacific. Either in S-mode or in T-mode, the sum of the variances contributed by the first 9 PCs in S-mode and by the first 3 PCs in T-mode exceeds 50% of the total amount of variation, respectively. Therefore, these PCs can reveal most of temporal-spatial pattern of sea level variations. There is a strong relationship between the El Nino and the temporal variations of the first PC either in S-mode or in T-mode, which explains the secular and inter-annual changes over the northwest Pacific. The rate of sea level change over the northwest Pacific, for the period October 1992-December 1999, is found to be negative: -0.55±0.30mm/year while in the Yellow Sea, the East China Sea and the South China Sea it is +3.4410.61 mm/year, +3.12±0.47 mm/year and -1.41±0.48 mm/year, respectively.

[1]  F. Bretherton,et al.  A technique for objective analysis and design of oceanographic experiments applied to MODE-73 , 1976 .

[2]  R. Preisendorfer,et al.  A Significance Test for Principal Components Applied to a Cyclone Climatology , 1982 .

[3]  Françoise Ogor,et al.  ERS‐1/2 orbit improvement using TOPEX/POSEIDON: The 2 cm challenge , 1998 .

[4]  D. Chelton,et al.  Geosat altimeter observations of the surface circulation of the Southern Ocean , 1990 .

[5]  Mark R. Abbott,et al.  Tidal and atmospheric forcing of the upper ocean in the Gulf of California: 1. Sea surface temperature variability , 1991 .

[6]  William W. Hsieh,et al.  Summer Sea Surface Temperature Variability off Vancouver Island From Satellite Data , 1993 .

[7]  D. Chelton,et al.  Observing large‐scale temporal variability of ocean currents by satellite altimetry: With application to the Antarctic Circumpolar Current , 1985 .

[8]  M. E. Parke,et al.  Seasonal variability of the Gulf Stream from satellite altimetry , 1987 .

[9]  R. J. Reed,et al.  Structure and Properties of Synoptic-Scale Wave Disturbances in the Equatorial Western Pacific , 1971 .

[10]  Gary S. E. Lagerloef,et al.  Empirical orthogonal function analysis of advanced very high resolution radiometer surface temperature patterns in Santa Barbara Channel , 1988 .

[11]  Chester J. Koblinsky,et al.  Empirical orthogonal function analysis of global TOPEX/POSEIDON altimeter data and implications for detection of global sea level rise , 1996 .

[12]  T. Barnett The estimation of «global» sea level change: a problem of uniqueness , 1984 .

[13]  Kathryn A. Kelly,et al.  The influence of winds and topography on the sea surface temperature patterns over the northern California slope , 1985 .

[14]  Philippe Gaspar,et al.  Using Topex/Poseidon Data to Enhance ERS-1 Data , 1995 .

[15]  J. Font,et al.  Complex empirical orthogonal functions analysis of ERS‐1 and TOPEX/POSEIDON combined altimetric data in the region of the Algerian current , 1998 .

[16]  J. Marsh,et al.  Global mean sea surface computation using GEOS 3 altimeter data , 1982 .

[17]  T. P. Barnett,et al.  The Principal Time and Space Scales of the Pacific Trade Wind Fields. , 1977 .

[18]  J. Wallace,et al.  Empirical Orthogonal Representation of Time Series in the Frequency Domain. Part I: Theoretical Considerations , 1972 .

[19]  Russ E. Davis,et al.  Predictability of Sea Surface Temperature and Sea Level Pressure Anomalies over the North Pacific Ocean , 1976 .