Abstract
The El Niño Southern Oscillation (ENSO) is a natural phenomenon that relates to the fluctuation of temperatures over the Pacific Ocean. The ENSO significantly affects the ocean dynamics including upwelling event and coastal front. A recent study discovered the seasonal upwelling in the east coast of Peninsular Malaysia (ECPM), which is significant to the fishery industry in this region. Thus, it is vital to have a better understanding of the influence of ENSO towards the coastal upwelling and thermal front in the ECPM. The sea surface temperature (SST) data achieved from moderate resolution imaging spectroradiometer (MODIS) aboard Aqua satellite are used in this study to observe the SST changes from 2005 to 2015. However, due to cloud cover issue, a reconstruction of data set is applied to MODIS data using the data interpolating empirical orthogonal function (DINEOF) to fill in the missing gap in the dataset based on spatial and temporal available data. Besides, a wavelet transformation analysis is done to determine the temperature fluctuation throughout the time series. The DINEOF results show the coastal upwelling in the ECPM develops in July and reaches its peak in August with a clear cold water patch off the coast. There is also a significant change of SST distribution during the El Niño years which weaken the coastal upwelling event along the ECPM. The wavelet transformation analysis shows the highest temperature fluctuation is in 2009–2010 which indicates the strongest El Niño throughout the time period. It is suggested that the El Niño is favourable for the stratification in water column thus it is weakening the upwelling and thermal frontal zone formation in ECPM waters.
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Akhir M F, Daryabor F, Husain M L, et al. 2015. Evidence of upwelling along peninsular malaysia during southwest monsoon. Open Journal of Marine Science, 5(3): 273–279, doi: 10.4236/ojms. 2015.53022
Alvera–Azcárate A, Barth A, Parard G, et al. 2016. Analysis of SMOS sea surface salinity data using DINEOF. Remote Sensing of Environment, 180: 137–145, doi: 10.1016/j.rse.2016.02.044
Alvera–Azcárate A, Barth A, Rixen M, et al. 2005. Reconstruction of incomplete oceanographic data sets using empirical orthogonal functions: Application to the Adriatic Sea surface temperature. Ocean Modelling, 9(4): 325–346, doi: 10.1016/j.ocemod. 2004.08.001
Alvera–Azcárate A, Sirjacobs D, Barth A, et al. 2012. Outlier detection in satellite data using spatial coherence. Remote Sensing of Environment, 119: 84–91, doi: 10.1016/j.rse.2011.12.009
Beckers J M, Rixen M. 2003. EOF calculations and data filling from incomplete oceanographic datasets. Journal of Atmospheric and Oceanic Technology, 20(12): 1839–1856, doi: 10.1175/1520–0426(2003)020<1839:ECADFF>2.0.CO;2
Chao S Y, Shaw P T, Wu S Y. 1997. El Niño modulation of the South China Sea circulation. Progress in Oceanography, 38(1): 51–93
Dahlman L. 2009. NOAA Climate Variability: Oceanic Niño Index. https://www.climate.gov/news–features/understandingclimate/climate–variability–oceanic–niño–index [2016–07–21]
He Shuangyan, Huang Daji, Zeng Dingyong. 2016. Double SST fronts observed from MODIS data in the East China Sea off the Zhejiang–Fujian coast, China. Journal of Marine Systems, 154: 93–102, doi: 10.1016/j.jmarsys.2015.02.009
Hong Huasheng, Zhang Caiyun, Shang Shaoling, et al. 2009. Interannual variability of summer coastal upwelling in the Taiwan Strait. Continental Shelf Research, 29(2): 479–484, doi: 10.1016/j.csr.2008.11.007
Jing Zhiyou, Qi Yiquan, Du Yan. 2011. Upwelling in the continental shelf of northern South China Sea associated with 1997–1998 El Niño. Journal of Geophysical Research: Oceans, 116(C2): C02033
Khalil I, Atkinson P M, Challenor P. 2016. Looking back and looking forwards: Historical and future trends in sea surface temperature (SST) in the Indo–Pacific region from 1982 to 2100. International Journal of Applied Earth Observation and Geoinformation, 45: 14–26, doi: 10.1016/j.jag.2015.10.005
Kim W, Yeh S W, Kim J H, et al. 2011. The unique 2009–2010 El Niño event: A fast phase transition of warm pool El Niño to La Niña. Geophysical Research Letters, 38(15): L15809
Kok P H, Akhir M F M, Tangang F, et al. 2017. Spatiotemporal trends in the southwest monsoon wind–driven upwelling in the southwestern part of the South China Sea. PLoS One, 12(2): e0171979, doi: 10.1371/journal.pone.0171979
Kok P H, Akhir M F M, Tangang F T. 2015. Thermal frontal zone along the east coast of Peninsular Malaysia. Continental Shelf Research, 110: 1–15, doi: 10.1016/j.csr.2015.09.010
Liu Yingchun, Santos A, Wang S M, et al. 2007. Tsunami hazards along Chinese coast from potential earthquakes in South China Sea. Physics of the Earth and Planetary Interiors, 163(1–4): 233–244
Liu Dongyan, Wang Yueqi. 2013. Trends of satellite derived chlorophyll–a (1997–2011) in the Bohai and Yellow Seas, China: Effects of bathymetry on seasonal and inter–annual patterns. Progress in Oceanography, 116: 154–166, doi: 10.1016/j.pocean. 2013.07.003
Montes I, Dewitte B, Gutknecht E. 2014. High–resolution modeling of the Eastern Tropical Pacific oxygen minimum zone: Sensitivity to the tropical oceanic circulation. Journal of Geophysical Research: Oceans, 119(8): 5515–5532, doi: 10.1002/2014JC009858
Moradi M, Kabiri K. 2015. Spatio–temporal variability of SST and Chlorophyll–a from MODIS data in the Persian Gulf. Marine Pollution Bulletin, 98(1–2): 14–25
Phuoc T, van Lanh V, Long B H, et al. 2002. Main Structures of Sea Surface Temperature (SST) in South China Sea from Satellite Data. In: Asian Conference on Remote Sensing (ACRS). Hanoi: Asian Association on Remote Sensing
Reynolds R W, Rayner N A, Smith T M, et al. 2002. An improved in situ and satellite SST analysis for climate. Journal of Climate, 1 5 ( 1 3 ): 1 6 0 9–1 6 2 5, d o i: 1 0. 1 1 7 5 /1 5 2 0–0 4 4 2 ( 2 0 0 2 ) 0 1 5 <1609:AIISAS>2.0.CO;2
Riegl B, Glynn P W, Wieters E, et al. 2015. Water column productivity and temperature predict coral reef regeneration across the Indo–Pacific. Scientific Reports, 5: 8273. doi: 10.1038/srep08273
Waite J N, Mueter F J. 2013. Spatial and temporal variability of chlorophyll–a concentrations in the coastal Gulf of Alaska, 1998–2011, using cloud–free reconstructions of SeaWiFS and MODIS–Aqua data. Progress in Oceanography, 116: 179–192, doi: 10.1016/j.pocean.2013.07.006
Wang Bin, Huang Fei, Wu Zhiwei, et al. 2009. Multi–scale climate variability of the South China Sea monsoon: A review. Dynamics of Atmospheres and Oceans, 47(1–3): 15–37
Acknowledgements
We acknowledge the Institute of Oceanography and Environment, Universiti Malaysia Terengganu for high specification of computer and good facilities for retrieved data, storage and run the analyses for this study. The MODIS data was obtained from NASA Ocean Color website and AVHRR-OI data was from NOAA website. The DINEOF technique was from the geohydrodynamics and environment research website. This work was supported by the UMT (INOS-HICoE).
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Daud, N.R., Akhir, M.F. & Muslim, A.M. Dynamic of ENSO towards upwelling and thermal front zone in the east coast of Peninsular Malaysia. Acta Oceanol. Sin. 38, 48–60 (2019). https://doi.org/10.1007/s13131-019-1369-7
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DOI: https://doi.org/10.1007/s13131-019-1369-7