Indian Ocean wind speed variability and global teleconnection patterns
Summary: The influence of the local sea surface temperature (SST) and remote ENSO (El Niño-Southern Oscillation) indices on the wind speed (WS) data were explored for the Indian Ocean region. Relationships among the parameters were studied using spatial correlation plots and significant correlation...
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ftdoajarticles:oai:doaj.org/article:3d132a326ad04a49941b2ed1537ed1c5 2023-05-15T17:35:29+02:00 Indian Ocean wind speed variability and global teleconnection patterns Mourani Sinha Somnath Jha Paromita Chakraborty 2020-04-01T00:00:00Z https://doi.org/10.1016/j.oceano.2019.10.002 https://doaj.org/article/3d132a326ad04a49941b2ed1537ed1c5 EN eng Elsevier http://www.sciencedirect.com/science/article/pii/S0078323419300776 https://doaj.org/toc/0078-3234 0078-3234 doi:10.1016/j.oceano.2019.10.002 https://doaj.org/article/3d132a326ad04a49941b2ed1537ed1c5 Oceanologia, Vol 62, Iss 2, Pp 126-138 (2020) Oceanography GC1-1581 article 2020 ftdoajarticles https://doi.org/10.1016/j.oceano.2019.10.002 2022-12-31T03:15:50Z Summary: The influence of the local sea surface temperature (SST) and remote ENSO (El Niño-Southern Oscillation) indices on the wind speed (WS) data were explored for the Indian Ocean region. Relationships among the parameters were studied using spatial correlation plots and significant correlation ranges. Two months (July and January) representing opposite monsoon phases were selected for analysis for the period 1950–2016. There was a significant negative correlation between WS and SST over the Bay of Bengal (BOB) during July. Although different ENSO indices correlated differently in different areas of the Indian Ocean, the region off the coast of Sri Lanka was most significantly teleconnected. The southwest monsoon locally impacted the WS and SST relationship and the WS parameter was remotely teleconnected in both the monsoon seasons. Further empirical orthogonal function (EOF) analysis was applied on the 67 years WS data of the BOB region to extract the dominant mode representing maximum variability of the total variance. The temporal pattern of the first principal component (PC1) of WS data was linked to the North Atlantic Oscillations in January and the Atlantic Multidecadal Oscillation in July respectively. The continuous wavelet power spectra of the PC1 of WS showed significant regions in the 2–4-year band resembling the ENSO variability. Wavelet coherence applied between PC1 of WS and the ENSO indices showed greatest values for January in the 8–16-year band and for July in the 0–4-year band. A close relationship was established between the WS variability in BOB and the ENSO indices. Keywords: Wind speed, Sea surface temperature, Monsoon, Wavelet coherence, Indian Ocean, Global teleconnection Article in Journal/Newspaper North Atlantic Directory of Open Access Journals: DOAJ Articles Indian Oceanologia 62 2 126 138 |
institution |
Open Polar |
collection |
Directory of Open Access Journals: DOAJ Articles |
op_collection_id |
ftdoajarticles |
language |
English |
topic |
Oceanography GC1-1581 |
spellingShingle |
Oceanography GC1-1581 Mourani Sinha Somnath Jha Paromita Chakraborty Indian Ocean wind speed variability and global teleconnection patterns |
topic_facet |
Oceanography GC1-1581 |
description |
Summary: The influence of the local sea surface temperature (SST) and remote ENSO (El Niño-Southern Oscillation) indices on the wind speed (WS) data were explored for the Indian Ocean region. Relationships among the parameters were studied using spatial correlation plots and significant correlation ranges. Two months (July and January) representing opposite monsoon phases were selected for analysis for the period 1950–2016. There was a significant negative correlation between WS and SST over the Bay of Bengal (BOB) during July. Although different ENSO indices correlated differently in different areas of the Indian Ocean, the region off the coast of Sri Lanka was most significantly teleconnected. The southwest monsoon locally impacted the WS and SST relationship and the WS parameter was remotely teleconnected in both the monsoon seasons. Further empirical orthogonal function (EOF) analysis was applied on the 67 years WS data of the BOB region to extract the dominant mode representing maximum variability of the total variance. The temporal pattern of the first principal component (PC1) of WS data was linked to the North Atlantic Oscillations in January and the Atlantic Multidecadal Oscillation in July respectively. The continuous wavelet power spectra of the PC1 of WS showed significant regions in the 2–4-year band resembling the ENSO variability. Wavelet coherence applied between PC1 of WS and the ENSO indices showed greatest values for January in the 8–16-year band and for July in the 0–4-year band. A close relationship was established between the WS variability in BOB and the ENSO indices. Keywords: Wind speed, Sea surface temperature, Monsoon, Wavelet coherence, Indian Ocean, Global teleconnection |
format |
Article in Journal/Newspaper |
author |
Mourani Sinha Somnath Jha Paromita Chakraborty |
author_facet |
Mourani Sinha Somnath Jha Paromita Chakraborty |
author_sort |
Mourani Sinha |
title |
Indian Ocean wind speed variability and global teleconnection patterns |
title_short |
Indian Ocean wind speed variability and global teleconnection patterns |
title_full |
Indian Ocean wind speed variability and global teleconnection patterns |
title_fullStr |
Indian Ocean wind speed variability and global teleconnection patterns |
title_full_unstemmed |
Indian Ocean wind speed variability and global teleconnection patterns |
title_sort |
indian ocean wind speed variability and global teleconnection patterns |
publisher |
Elsevier |
publishDate |
2020 |
url |
https://doi.org/10.1016/j.oceano.2019.10.002 https://doaj.org/article/3d132a326ad04a49941b2ed1537ed1c5 |
geographic |
Indian |
geographic_facet |
Indian |
genre |
North Atlantic |
genre_facet |
North Atlantic |
op_source |
Oceanologia, Vol 62, Iss 2, Pp 126-138 (2020) |
op_relation |
http://www.sciencedirect.com/science/article/pii/S0078323419300776 https://doaj.org/toc/0078-3234 0078-3234 doi:10.1016/j.oceano.2019.10.002 https://doaj.org/article/3d132a326ad04a49941b2ed1537ed1c5 |
op_doi |
https://doi.org/10.1016/j.oceano.2019.10.002 |
container_title |
Oceanologia |
container_volume |
62 |
container_issue |
2 |
container_start_page |
126 |
op_container_end_page |
138 |
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1766134666570498048 |