Reference : Reconstruction and analysis of long-term satellite-derived sea surface temperature fo...
Scientific journals : Article
Physical, chemical, mathematical & earth Sciences : Earth sciences & physical geography
http://hdl.handle.net/2268/195421
Reconstruction and analysis of long-term satellite-derived sea surface temperature for the South China Sea
English
Huynh, Thi Hong Ngu mailto [Université de Liège - ULg > > > Form.doct. sc. (océanographie - Bologne)]
Alvera Azcarate, Aïda mailto [Université de Liège > Département d'astrophys., géophysique et océanographie (AGO) > GeoHydrodynamics and Environment Research (GHER) >]
Barth, Alexander mailto [Université de Liège > Département d'astrophys., géophysique et océanographie (AGO) > GeoHydrodynamics and Environment Research (GHER) >]
Beckers, Jean-Marie mailto [Université de Liège > Département d'astrophys., géophysique et océanographie (AGO) > GeoHydrodynamics and Environment Research (GHER) >]
6-Apr-2016
Journal of Oceanography
Springer Japan
Yes (verified by ORBi)
International
0916-8370
1573-868X
[en] South China Sea ; SST ; Seasonal and interannual variability ; Monsoon ; ENSO ; DINEOF
[en] Sea surface temperature (SST) is one of the key variables often used to investigate ocean dynamics, ocean-atmosphere interaction, and climate change. Unfortunately, the SST data sources in the South China Sea (SCS) are not abundant due to sparse measurements of in situ SST and a high percentage of missing data in the satellite-derived SST. Therefore, SST data sets with low resolution and/or a short-term period have often been used in previous researches. Here we used Data INterpolating Empirical Orthogonal Functions, a self-consistent and parameter-free method for filling in missing data, to reconstruct the daily nighttime 4-km AVHRR Pathfinder SST for the long-term period spanning from 1989 to 2009. In addition to the reconstructed field, we also estimated the local error map for each reconstructed image. Comparisons between the reconstructed and other data sets (satellite-derived microwave and in situ SSTs) show that the results are reliable for use in many different researches, such as validating numerical models, or identifying and tracking meso-scale oceanic features. Moreover, the Empirical Orthogonal Function (EOF) analysis of the reconstructed SST and the reconstructed SST anomalies clearly shows the subseasonal, seasonal, and interannual variability of SST under the influence of monsoon and El Niño-Southern Oscillation (ENSO), as well as reveals some oceanic features that could not be captured well in previous EOF analyses. The SCS SST often lags ENSO by about half a year. However, in this study, we see that the time lag changes with the frequencies of the SST variability, from 1 to 6 months.
GHER
Researchers ; Professionals ; Students
http://hdl.handle.net/2268/195421
10.1007/s10872-016-0365-1
http://link.springer.com/article/10.1007/s10872-016-0365-1

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