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Interannual variability of sea surface height anomaly in the South China Sea
Radjawane I.M.a, Karmel M.E.R.a, Prijatna K.a
a Oceanography Department, Faculty of Earth Sciences and Technology, Institut Teknologi Bandung, Indonesia
[vc_row][vc_column][vc_row_inner][vc_column_inner][vc_separator css=”.vc_custom_1624529070653{padding-top: 30px !important;padding-bottom: 30px !important;}”][/vc_column_inner][/vc_row_inner][vc_row_inner layout=”boxed”][vc_column_inner width=”3/4″ css=”.vc_custom_1624695412187{border-right-width: 1px !important;border-right-color: #dddddd !important;border-right-style: solid !important;border-radius: 1px !important;}”][vc_empty_space][megatron_heading title=”Abstract” size=”size-sm” text_align=”text-left”][vc_column_text]© 2019 IOP Publishing Ltd. All rights reserved.Spatial variability of Sea Surface Height Anomaly (herein after SSHA) in the South China Sea was investigated through the response of sea surface to interannual phenomenon. In this research, satellite altimetry data were used which covered periods from 1992 to 2015. Signal analysis was performed to separate dominant spectrum for each stations. From the analysis, it is found that the dominant feature for South China Sea is high period signal i.e annual and decadal signals. This research will focus the analysis only on interannual variability response of SSHA. During northeast monsoon, SSHA in South China Sea region is increased due to the accumulation of water mass over southern basin. Highest increase of SSHA occurs during strong La Niña, while the highest decrease of SSHA takes place during El Niño. The distribution of change in SSHA varies with strong influence of latitude and longitude to the response of upper layer. During El Niño, increasing SSHA was detected in several locations; likewise, during La Niña the decrease was also found.[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Author keywords” size=”size-sm” text_align=”text-left”][vc_column_text]Interannual,Interannual variability,Northeast monsoon,Satellite altimetry data,Sea surfaces,Sea-surface height anomalies,South China sea,Spatial variability[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Indexed keywords” size=”size-sm” text_align=”text-left”][vc_column_text][/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Funding details” size=”size-sm” text_align=”text-left”][vc_column_text]Part of this research was supported by the P3MI Research Grant ITB 2017. We would like to thank to Aditya Rachmat Kartadikaria for assisting the English manuscript.[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”DOI” size=”size-sm” text_align=”text-left”][vc_column_text]https://doi.org/10.1088/1742-6596/1277/1/012043[/vc_column_text][/vc_column_inner][vc_column_inner width=”1/4″][vc_column_text]Widget Plumx[/vc_column_text][/vc_column_inner][/vc_row_inner][/vc_column][/vc_row][vc_row][vc_column][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][/vc_column][/vc_row]