[vc_empty_space][vc_empty_space]
Spatial-temporal variation of anomaly chlorophyll-a in Southern Java and Nusa Tenggara using empirical orthogonal functionanalysis
a Oceanography Research Group, Faculty of Earth Sciences and Technology, Institut Teknologi Bandung, Jawa Barat, 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.Data from Global Ocean Biogeochemistry models were used to study the spatial and temporal variation of sea surface chlorophyll-a in southern Java and Nusa Tenggara. Empirical Orthogonal Function (EOF) analysis was applied to decompose spatial and temporal mode of the anomaly chlorophyll-a. The first mode (58.7%) revealed strong interannual variation that had a significant correlation with the Indian Ocean Dipole (IOD) event. The Second mode (7.2%) of the temporal pattern showed seasonal periods while the spatial pattern showed the opposite phase between southern Java and Nusa Tenggara. The spatial pattern of mode 3 (5.2%) and 4 (2.7%) showed an interesting pattern where it showed strong variance in the exit way of Indonesian Trough Flow. However, it needs more study to conclude the phenomena that were revealed by mode 3 and 4.[/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]Empirical orthogonal function analysis,Indian ocean dipoles,Interannual variation,Seasonal periods,Spatial and temporal variation,Spatial patterns,Spatial temporals,Temporal pattern[/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][/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/10.1088/1742-6596/1277/1/012042[/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]