On the consistency in variations of the South China Sea Warm Pool as revealed by three sea surface temperature datasets

• Published in: Remote sensing of environment Vol. 109; no. 1; pp. 118 - 125
• Main Authors: Li, N., Shang, S.P., Shang, S.L., Zhang, C.Y.
• Format: Journal Article
• Language: English
• Published: New York, NY Elsevier Inc 12.07.2007; Elsevier Science
• Subjects: Animal, plant and microbial ecology; Applied geophysics; AVHRR; Biological and medical sciences; Earth sciences; Earth, ocean, space; ENSO; Exact sciences and technology; Fundamental and applied biological sciences. Psychology; General aspects. Techniques; Index; Internal geophysics; Marine; OI.v2; Remote sensing; Sea surface temperature; South China Sea Warm Pool; Teledetection and vegetation maps; TMI; Variation; West Pacific; South China Sea; ISEW, South China Sea; TMI; ENSO; South China Sea Warm Pool; Index; OI.v2; Sea surface temperature; Variation; Remote sensing; AVHRR; microwaves; data; tropical zone; clouds; Capture; El Nino; fluctuations; Southern oscillation; Example; Season; high resolution; Addition; rainfall; Time series; 1990; Imager; remote sensing; contamination; Optimum; interpolation; signals; Pacific Ocean; Deviation; seasonal variations
• ISSN: 0034-4257; 1879-0704
• DOI: 10.1016/j.rse.2006.12.012

The areal and intensity indices of the South China Sea Warm Pool (SCSWP) derived from three datasets, the Advanced Very High Resolution Radiometer (AVHRR), Tropical Rainfall Measuring Mission's Microwave Imager (TMI) and Optimum Interpolation Version 2 (OI.v2) sea surface temperature (SST), are generally consistent with each other at monthly, seasonal and interannual scales. However, the three records are different in some cases. First, minor differences among the monthly records of intensity index are observed in the period July to September. Secondly, the interannual records of SCSWP intensity derived from AVHRR and OI.v2 are different in autumn during the period 1990–1996. The reason is not yet clear and nor is it clear which record best represents fluctuations in SCSWP intensity. These suggest that various drawbacks of the three datasets, such as low resolution of OI.v2, and cloud and rain contamination on AVHRR and TMI data, would be serious enough to allow deviation from each other to appear. Merging AVHRR and TMI SST data might be the way leading to a more convincing time series of SCSWP. In addition, changes of areal and intensity indices are not always consistent with each other, for example, they have different monthly patterns. Although the three interannual records of intensity index in three seasons all capture the main Multivariate ENSO Index (MEI) signals at a half-year lag, only those which are in the summer significantly correlated with MEI.