Seasonal Variability of Phytoplankton Biomass Revealed by Satellite and BGC‐Argo Data in the Central Tropical Indian Ocean
The variability of phytoplankton biomass related to ocean's biological carbon pump in the central tropical Indian Ocean is not fully understood. Using satellite and biogeochemical Argo data, we found that phytoplankton biomass exhibits significantly different and even opposite changes at the ne...
Gespeichert in:
Veröffentlicht in: | Journal of geophysical research. Oceans 2022-10, Vol.127 (10), p.n/a |
---|---|
Hauptverfasser: | , , , , , , , |
Format: | Artikel |
Sprache: | eng |
Schlagworte: | |
Online-Zugang: | Volltext |
Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
container_end_page | n/a |
---|---|
container_issue | 10 |
container_start_page | |
container_title | Journal of geophysical research. Oceans |
container_volume | 127 |
creator | Hu, Qiwei Chen, Xiaoyan He, Xianqiang Bai, Yan Zhong, Qingwen Gong, Fang Zhu, Qiankun Pan, Delu |
description | The variability of phytoplankton biomass related to ocean's biological carbon pump in the central tropical Indian Ocean is not fully understood. Using satellite and biogeochemical Argo data, we found that phytoplankton biomass exhibits significantly different and even opposite changes at the near‐surface (0–10 m) and subsurface layer (50–100 m). Results showed that the shoaling/deepening of the mixed layer and thermocline dominated the phytoplankton biomass change in different layers. In February–May, the shallow mixed‐layer depth (MLD) exacerbated the oligotrophic environment in the mixed layer, thus resulting in low near‐surface phytoplankton biomass (Chl a 50 m), hence increasing the supply of both nutrients and phytoplankton from the subsurface to maintain the near‐surface phytoplankton blooms (Chl a > 0.2 mg m−3) in June–October. Below the mixed layer, wind‐induced upwelling/downwelling modulated the thermocline, which significantly affects the supply of nutrients for phytoplankton growth in the subsurface layer. The shallower thermocline during February and March provided favorable conditions for the subsurface blooms (Chl a > 0.5 mg m−3) with a prominent subsurface chlorophyll maximum layer (SCML). Conversely, the deeper thermocline in June and July was related to the lowest phytoplankton biomass with the disappearance of the SCML. These results may help explain the response of vertical phytoplankton to changes driven by multiple atmospheric and physical forcing factors in future climate‐change scenarios.
Plain Language Summary
Satellite and biogeochemical float are essential platforms for quantifying phytoplankton biomass in the upper ocean, which is critical for understanding ocean's biological carbon pump that removes carbon dioxide from the atmosphere. Phytoplankton variation in the upper‐water column, however, is not fully understood. We showed that the seasonal variation of phytoplankton in the near‐surface layer differs from that in the subsurface layer in the central tropical Indian Ocean (CIO) using satellite and float data. We demonstrated that various responses of phytoplankton in the upper water column are triggered by seasonal wind bursts, including the deepening of the mixed layer and shoaling of the thermocline. In February–May, weak wind and enhanced stratification resulted in low near‐surface phytoplankton biomass. However, the s |
doi_str_mv | 10.1029/2021JC018227 |
format | Article |
fullrecord | <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_journals_2729009906</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>2729009906</sourcerecordid><originalsourceid>FETCH-LOGICAL-a3738-d804597d8fa7ce9fca82664062543e115f162ea7b3b262b6d1396dd289ac75a33</originalsourceid><addsrcrecordid>eNp90MFKxDAQBuAiCsrqzQcIeHU1mbRpctSq6y4LK7vqtUzbVKM1WZOuUvDgI_iMPomVFfHkXGYOHz_MH0X7jB4xCuoYKLBJRpkESDeiHWBCDRUotvl7p8l2tBfCA-1HMhnHaid6W2gMzmJDbtEbLExj2o64mlzdd61bNmgfW2fJqXFPGAKZ6xeNja5I0ZEFtrrpuSZoK3I6yj7fP078nSNn2CIxlrT3mmTatr5Pv_Zuacr-GNvKoCWzUqPdjbZqbILe-9mD6Obi_Dq7HE5no3F2Mh0iT7kcVpLGiUorWWNaalWXKEGImApIYq4ZS2omQGNa8AIEFKJiXImqAqmwTBPkfBAdrHOX3j2vdGjzB7fy_dMhhxQUpUpR0avDtSq9C8HrOl9684S-yxnNvyvO_1bcc77mr6bR3b82n4zmGSTAJP8C1PN89A</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2729009906</pqid></control><display><type>article</type><title>Seasonal Variability of Phytoplankton Biomass Revealed by Satellite and BGC‐Argo Data in the Central Tropical Indian Ocean</title><source>Wiley Free Content</source><source>Wiley Online Library Journals Frontfile Complete</source><source>Alma/SFX Local Collection</source><creator>Hu, Qiwei ; Chen, Xiaoyan ; He, Xianqiang ; Bai, Yan ; Zhong, Qingwen ; Gong, Fang ; Zhu, Qiankun ; Pan, Delu</creator><creatorcontrib>Hu, Qiwei ; Chen, Xiaoyan ; He, Xianqiang ; Bai, Yan ; Zhong, Qingwen ; Gong, Fang ; Zhu, Qiankun ; Pan, Delu</creatorcontrib><description>The variability of phytoplankton biomass related to ocean's biological carbon pump in the central tropical Indian Ocean is not fully understood. Using satellite and biogeochemical Argo data, we found that phytoplankton biomass exhibits significantly different and even opposite changes at the near‐surface (0–10 m) and subsurface layer (50–100 m). Results showed that the shoaling/deepening of the mixed layer and thermocline dominated the phytoplankton biomass change in different layers. In February–May, the shallow mixed‐layer depth (MLD) exacerbated the oligotrophic environment in the mixed layer, thus resulting in low near‐surface phytoplankton biomass (Chl a < 0.1 mg m−3). However, strengthened wind stress and surface cooling induced deep vertical mixing (MLD > 50 m), hence increasing the supply of both nutrients and phytoplankton from the subsurface to maintain the near‐surface phytoplankton blooms (Chl a > 0.2 mg m−3) in June–October. Below the mixed layer, wind‐induced upwelling/downwelling modulated the thermocline, which significantly affects the supply of nutrients for phytoplankton growth in the subsurface layer. The shallower thermocline during February and March provided favorable conditions for the subsurface blooms (Chl a > 0.5 mg m−3) with a prominent subsurface chlorophyll maximum layer (SCML). Conversely, the deeper thermocline in June and July was related to the lowest phytoplankton biomass with the disappearance of the SCML. These results may help explain the response of vertical phytoplankton to changes driven by multiple atmospheric and physical forcing factors in future climate‐change scenarios.
Plain Language Summary
Satellite and biogeochemical float are essential platforms for quantifying phytoplankton biomass in the upper ocean, which is critical for understanding ocean's biological carbon pump that removes carbon dioxide from the atmosphere. Phytoplankton variation in the upper‐water column, however, is not fully understood. We showed that the seasonal variation of phytoplankton in the near‐surface layer differs from that in the subsurface layer in the central tropical Indian Ocean (CIO) using satellite and float data. We demonstrated that various responses of phytoplankton in the upper water column are triggered by seasonal wind bursts, including the deepening of the mixed layer and shoaling of the thermocline. In February–May, weak wind and enhanced stratification resulted in low near‐surface phytoplankton biomass. However, the strong wind and sea surface cooling induced deep vertical mixing, thus increasing the supply of both nutrients and phytoplankton to support the near‐surface phytoplankton blooms in June–October of the CIO. For the subsurface layer (50–100 m), the wind‐induced upwelling uplifted the nutrients and provided favorable conditions for the strong subsurface phytoplankton blooms in February and March. Conversely, the wind‐induced downwelling led to the lowest phytoplankton biomass in June and July. These results provide new information on the vertical variability of phytoplankton biomass in the tropical marine.
Key Points
The phytoplankton biomass in 0–10 m decreased (increased), while that in 50–100 m increased (decreased) during February–May (June and July)
The deep vertical mixing drove the supply of both nutrients and phytoplankton from the subsurface to support near‐surface blooms
The intensity of subsurface blooms depended on the modulation of the thermocline depth by wind‐induced upwelling</description><identifier>ISSN: 2169-9275</identifier><identifier>EISSN: 2169-9291</identifier><identifier>DOI: 10.1029/2021JC018227</identifier><language>eng</language><publisher>Washington: Blackwell Publishing Ltd</publisher><subject>Biogeochemistry ; Biomass ; Blooms ; Carbon ; Carbon dioxide ; Carbon dioxide removal ; Chlorophyll ; Chlorophylls ; Climate change ; Cooling ; Downwelling ; Future climates ; Geophysics ; Indian spacecraft ; Mixed layer ; Nutrient cycles ; Nutrients ; Ocean circulation ; Oceans ; Phytoplankton ; Plankton ; Satellites ; Sea surface ; Sea surface cooling ; Seasonal variability ; Seasonal variation ; Seasonal variations ; Seasonal winds ; Shoaling ; Stratification ; Strong winds ; Surface boundary layer ; Surface cooling ; Surface layers ; Thermocline ; Upper ocean ; Upwelling ; Vertical mixing ; Water circulation ; Water column ; Wind ; Wind stress ; Work platforms</subject><ispartof>Journal of geophysical research. Oceans, 2022-10, Vol.127 (10), p.n/a</ispartof><rights>2022. American Geophysical Union. All Rights Reserved.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-a3738-d804597d8fa7ce9fca82664062543e115f162ea7b3b262b6d1396dd289ac75a33</citedby><cites>FETCH-LOGICAL-a3738-d804597d8fa7ce9fca82664062543e115f162ea7b3b262b6d1396dd289ac75a33</cites><orcidid>0000-0001-7474-6778 ; 0000-0002-8438-2848 ; 0000-0002-5212-510X ; 0000-0001-5882-1176 ; 0000-0002-3345-1495</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://onlinelibrary.wiley.com/doi/pdf/10.1029%2F2021JC018227$$EPDF$$P50$$Gwiley$$H</linktopdf><linktohtml>$$Uhttps://onlinelibrary.wiley.com/doi/full/10.1029%2F2021JC018227$$EHTML$$P50$$Gwiley$$H</linktohtml><link.rule.ids>314,776,780,1411,1427,27901,27902,45550,45551,46384,46808</link.rule.ids></links><search><creatorcontrib>Hu, Qiwei</creatorcontrib><creatorcontrib>Chen, Xiaoyan</creatorcontrib><creatorcontrib>He, Xianqiang</creatorcontrib><creatorcontrib>Bai, Yan</creatorcontrib><creatorcontrib>Zhong, Qingwen</creatorcontrib><creatorcontrib>Gong, Fang</creatorcontrib><creatorcontrib>Zhu, Qiankun</creatorcontrib><creatorcontrib>Pan, Delu</creatorcontrib><title>Seasonal Variability of Phytoplankton Biomass Revealed by Satellite and BGC‐Argo Data in the Central Tropical Indian Ocean</title><title>Journal of geophysical research. Oceans</title><description>The variability of phytoplankton biomass related to ocean's biological carbon pump in the central tropical Indian Ocean is not fully understood. Using satellite and biogeochemical Argo data, we found that phytoplankton biomass exhibits significantly different and even opposite changes at the near‐surface (0–10 m) and subsurface layer (50–100 m). Results showed that the shoaling/deepening of the mixed layer and thermocline dominated the phytoplankton biomass change in different layers. In February–May, the shallow mixed‐layer depth (MLD) exacerbated the oligotrophic environment in the mixed layer, thus resulting in low near‐surface phytoplankton biomass (Chl a < 0.1 mg m−3). However, strengthened wind stress and surface cooling induced deep vertical mixing (MLD > 50 m), hence increasing the supply of both nutrients and phytoplankton from the subsurface to maintain the near‐surface phytoplankton blooms (Chl a > 0.2 mg m−3) in June–October. Below the mixed layer, wind‐induced upwelling/downwelling modulated the thermocline, which significantly affects the supply of nutrients for phytoplankton growth in the subsurface layer. The shallower thermocline during February and March provided favorable conditions for the subsurface blooms (Chl a > 0.5 mg m−3) with a prominent subsurface chlorophyll maximum layer (SCML). Conversely, the deeper thermocline in June and July was related to the lowest phytoplankton biomass with the disappearance of the SCML. These results may help explain the response of vertical phytoplankton to changes driven by multiple atmospheric and physical forcing factors in future climate‐change scenarios.
Plain Language Summary
Satellite and biogeochemical float are essential platforms for quantifying phytoplankton biomass in the upper ocean, which is critical for understanding ocean's biological carbon pump that removes carbon dioxide from the atmosphere. Phytoplankton variation in the upper‐water column, however, is not fully understood. We showed that the seasonal variation of phytoplankton in the near‐surface layer differs from that in the subsurface layer in the central tropical Indian Ocean (CIO) using satellite and float data. We demonstrated that various responses of phytoplankton in the upper water column are triggered by seasonal wind bursts, including the deepening of the mixed layer and shoaling of the thermocline. In February–May, weak wind and enhanced stratification resulted in low near‐surface phytoplankton biomass. However, the strong wind and sea surface cooling induced deep vertical mixing, thus increasing the supply of both nutrients and phytoplankton to support the near‐surface phytoplankton blooms in June–October of the CIO. For the subsurface layer (50–100 m), the wind‐induced upwelling uplifted the nutrients and provided favorable conditions for the strong subsurface phytoplankton blooms in February and March. Conversely, the wind‐induced downwelling led to the lowest phytoplankton biomass in June and July. These results provide new information on the vertical variability of phytoplankton biomass in the tropical marine.
Key Points
The phytoplankton biomass in 0–10 m decreased (increased), while that in 50–100 m increased (decreased) during February–May (June and July)
The deep vertical mixing drove the supply of both nutrients and phytoplankton from the subsurface to support near‐surface blooms
The intensity of subsurface blooms depended on the modulation of the thermocline depth by wind‐induced upwelling</description><subject>Biogeochemistry</subject><subject>Biomass</subject><subject>Blooms</subject><subject>Carbon</subject><subject>Carbon dioxide</subject><subject>Carbon dioxide removal</subject><subject>Chlorophyll</subject><subject>Chlorophylls</subject><subject>Climate change</subject><subject>Cooling</subject><subject>Downwelling</subject><subject>Future climates</subject><subject>Geophysics</subject><subject>Indian spacecraft</subject><subject>Mixed layer</subject><subject>Nutrient cycles</subject><subject>Nutrients</subject><subject>Ocean circulation</subject><subject>Oceans</subject><subject>Phytoplankton</subject><subject>Plankton</subject><subject>Satellites</subject><subject>Sea surface</subject><subject>Sea surface cooling</subject><subject>Seasonal variability</subject><subject>Seasonal variation</subject><subject>Seasonal variations</subject><subject>Seasonal winds</subject><subject>Shoaling</subject><subject>Stratification</subject><subject>Strong winds</subject><subject>Surface boundary layer</subject><subject>Surface cooling</subject><subject>Surface layers</subject><subject>Thermocline</subject><subject>Upper ocean</subject><subject>Upwelling</subject><subject>Vertical mixing</subject><subject>Water circulation</subject><subject>Water column</subject><subject>Wind</subject><subject>Wind stress</subject><subject>Work platforms</subject><issn>2169-9275</issn><issn>2169-9291</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2022</creationdate><recordtype>article</recordtype><recordid>eNp90MFKxDAQBuAiCsrqzQcIeHU1mbRpctSq6y4LK7vqtUzbVKM1WZOuUvDgI_iMPomVFfHkXGYOHz_MH0X7jB4xCuoYKLBJRpkESDeiHWBCDRUotvl7p8l2tBfCA-1HMhnHaid6W2gMzmJDbtEbLExj2o64mlzdd61bNmgfW2fJqXFPGAKZ6xeNja5I0ZEFtrrpuSZoK3I6yj7fP078nSNn2CIxlrT3mmTatr5Pv_Zuacr-GNvKoCWzUqPdjbZqbILe-9mD6Obi_Dq7HE5no3F2Mh0iT7kcVpLGiUorWWNaalWXKEGImApIYq4ZS2omQGNa8AIEFKJiXImqAqmwTBPkfBAdrHOX3j2vdGjzB7fy_dMhhxQUpUpR0avDtSq9C8HrOl9684S-yxnNvyvO_1bcc77mr6bR3b82n4zmGSTAJP8C1PN89A</recordid><startdate>202210</startdate><enddate>202210</enddate><creator>Hu, Qiwei</creator><creator>Chen, Xiaoyan</creator><creator>He, Xianqiang</creator><creator>Bai, Yan</creator><creator>Zhong, Qingwen</creator><creator>Gong, Fang</creator><creator>Zhu, Qiankun</creator><creator>Pan, Delu</creator><general>Blackwell Publishing Ltd</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7TG</scope><scope>7TN</scope><scope>F1W</scope><scope>H96</scope><scope>KL.</scope><scope>L.G</scope><orcidid>https://orcid.org/0000-0001-7474-6778</orcidid><orcidid>https://orcid.org/0000-0002-8438-2848</orcidid><orcidid>https://orcid.org/0000-0002-5212-510X</orcidid><orcidid>https://orcid.org/0000-0001-5882-1176</orcidid><orcidid>https://orcid.org/0000-0002-3345-1495</orcidid></search><sort><creationdate>202210</creationdate><title>Seasonal Variability of Phytoplankton Biomass Revealed by Satellite and BGC‐Argo Data in the Central Tropical Indian Ocean</title><author>Hu, Qiwei ; Chen, Xiaoyan ; He, Xianqiang ; Bai, Yan ; Zhong, Qingwen ; Gong, Fang ; Zhu, Qiankun ; Pan, Delu</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-a3738-d804597d8fa7ce9fca82664062543e115f162ea7b3b262b6d1396dd289ac75a33</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2022</creationdate><topic>Biogeochemistry</topic><topic>Biomass</topic><topic>Blooms</topic><topic>Carbon</topic><topic>Carbon dioxide</topic><topic>Carbon dioxide removal</topic><topic>Chlorophyll</topic><topic>Chlorophylls</topic><topic>Climate change</topic><topic>Cooling</topic><topic>Downwelling</topic><topic>Future climates</topic><topic>Geophysics</topic><topic>Indian spacecraft</topic><topic>Mixed layer</topic><topic>Nutrient cycles</topic><topic>Nutrients</topic><topic>Ocean circulation</topic><topic>Oceans</topic><topic>Phytoplankton</topic><topic>Plankton</topic><topic>Satellites</topic><topic>Sea surface</topic><topic>Sea surface cooling</topic><topic>Seasonal variability</topic><topic>Seasonal variation</topic><topic>Seasonal variations</topic><topic>Seasonal winds</topic><topic>Shoaling</topic><topic>Stratification</topic><topic>Strong winds</topic><topic>Surface boundary layer</topic><topic>Surface cooling</topic><topic>Surface layers</topic><topic>Thermocline</topic><topic>Upper ocean</topic><topic>Upwelling</topic><topic>Vertical mixing</topic><topic>Water circulation</topic><topic>Water column</topic><topic>Wind</topic><topic>Wind stress</topic><topic>Work platforms</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Hu, Qiwei</creatorcontrib><creatorcontrib>Chen, Xiaoyan</creatorcontrib><creatorcontrib>He, Xianqiang</creatorcontrib><creatorcontrib>Bai, Yan</creatorcontrib><creatorcontrib>Zhong, Qingwen</creatorcontrib><creatorcontrib>Gong, Fang</creatorcontrib><creatorcontrib>Zhu, Qiankun</creatorcontrib><creatorcontrib>Pan, Delu</creatorcontrib><collection>CrossRef</collection><collection>Meteorological & Geoastrophysical Abstracts</collection><collection>Oceanic Abstracts</collection><collection>ASFA: Aquatic Sciences and Fisheries Abstracts</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) 2: Ocean Technology, Policy & Non-Living Resources</collection><collection>Meteorological & Geoastrophysical Abstracts - Academic</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) Professional</collection><jtitle>Journal of geophysical research. Oceans</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Hu, Qiwei</au><au>Chen, Xiaoyan</au><au>He, Xianqiang</au><au>Bai, Yan</au><au>Zhong, Qingwen</au><au>Gong, Fang</au><au>Zhu, Qiankun</au><au>Pan, Delu</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Seasonal Variability of Phytoplankton Biomass Revealed by Satellite and BGC‐Argo Data in the Central Tropical Indian Ocean</atitle><jtitle>Journal of geophysical research. Oceans</jtitle><date>2022-10</date><risdate>2022</risdate><volume>127</volume><issue>10</issue><epage>n/a</epage><issn>2169-9275</issn><eissn>2169-9291</eissn><abstract>The variability of phytoplankton biomass related to ocean's biological carbon pump in the central tropical Indian Ocean is not fully understood. Using satellite and biogeochemical Argo data, we found that phytoplankton biomass exhibits significantly different and even opposite changes at the near‐surface (0–10 m) and subsurface layer (50–100 m). Results showed that the shoaling/deepening of the mixed layer and thermocline dominated the phytoplankton biomass change in different layers. In February–May, the shallow mixed‐layer depth (MLD) exacerbated the oligotrophic environment in the mixed layer, thus resulting in low near‐surface phytoplankton biomass (Chl a < 0.1 mg m−3). However, strengthened wind stress and surface cooling induced deep vertical mixing (MLD > 50 m), hence increasing the supply of both nutrients and phytoplankton from the subsurface to maintain the near‐surface phytoplankton blooms (Chl a > 0.2 mg m−3) in June–October. Below the mixed layer, wind‐induced upwelling/downwelling modulated the thermocline, which significantly affects the supply of nutrients for phytoplankton growth in the subsurface layer. The shallower thermocline during February and March provided favorable conditions for the subsurface blooms (Chl a > 0.5 mg m−3) with a prominent subsurface chlorophyll maximum layer (SCML). Conversely, the deeper thermocline in June and July was related to the lowest phytoplankton biomass with the disappearance of the SCML. These results may help explain the response of vertical phytoplankton to changes driven by multiple atmospheric and physical forcing factors in future climate‐change scenarios.
Plain Language Summary
Satellite and biogeochemical float are essential platforms for quantifying phytoplankton biomass in the upper ocean, which is critical for understanding ocean's biological carbon pump that removes carbon dioxide from the atmosphere. Phytoplankton variation in the upper‐water column, however, is not fully understood. We showed that the seasonal variation of phytoplankton in the near‐surface layer differs from that in the subsurface layer in the central tropical Indian Ocean (CIO) using satellite and float data. We demonstrated that various responses of phytoplankton in the upper water column are triggered by seasonal wind bursts, including the deepening of the mixed layer and shoaling of the thermocline. In February–May, weak wind and enhanced stratification resulted in low near‐surface phytoplankton biomass. However, the strong wind and sea surface cooling induced deep vertical mixing, thus increasing the supply of both nutrients and phytoplankton to support the near‐surface phytoplankton blooms in June–October of the CIO. For the subsurface layer (50–100 m), the wind‐induced upwelling uplifted the nutrients and provided favorable conditions for the strong subsurface phytoplankton blooms in February and March. Conversely, the wind‐induced downwelling led to the lowest phytoplankton biomass in June and July. These results provide new information on the vertical variability of phytoplankton biomass in the tropical marine.
Key Points
The phytoplankton biomass in 0–10 m decreased (increased), while that in 50–100 m increased (decreased) during February–May (June and July)
The deep vertical mixing drove the supply of both nutrients and phytoplankton from the subsurface to support near‐surface blooms
The intensity of subsurface blooms depended on the modulation of the thermocline depth by wind‐induced upwelling</abstract><cop>Washington</cop><pub>Blackwell Publishing Ltd</pub><doi>10.1029/2021JC018227</doi><tpages>19</tpages><orcidid>https://orcid.org/0000-0001-7474-6778</orcidid><orcidid>https://orcid.org/0000-0002-8438-2848</orcidid><orcidid>https://orcid.org/0000-0002-5212-510X</orcidid><orcidid>https://orcid.org/0000-0001-5882-1176</orcidid><orcidid>https://orcid.org/0000-0002-3345-1495</orcidid></addata></record> |
fulltext | fulltext |
identifier | ISSN: 2169-9275 |
ispartof | Journal of geophysical research. Oceans, 2022-10, Vol.127 (10), p.n/a |
issn | 2169-9275 2169-9291 |
language | eng |
recordid | cdi_proquest_journals_2729009906 |
source | Wiley Free Content; Wiley Online Library Journals Frontfile Complete; Alma/SFX Local Collection |
subjects | Biogeochemistry Biomass Blooms Carbon Carbon dioxide Carbon dioxide removal Chlorophyll Chlorophylls Climate change Cooling Downwelling Future climates Geophysics Indian spacecraft Mixed layer Nutrient cycles Nutrients Ocean circulation Oceans Phytoplankton Plankton Satellites Sea surface Sea surface cooling Seasonal variability Seasonal variation Seasonal variations Seasonal winds Shoaling Stratification Strong winds Surface boundary layer Surface cooling Surface layers Thermocline Upper ocean Upwelling Vertical mixing Water circulation Water column Wind Wind stress Work platforms |
title | Seasonal Variability of Phytoplankton Biomass Revealed by Satellite and BGC‐Argo Data in the Central Tropical Indian Ocean |
url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-02-05T20%3A03%3A13IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Seasonal%20Variability%20of%20Phytoplankton%20Biomass%20Revealed%20by%20Satellite%20and%20BGC%E2%80%90Argo%20Data%20in%20the%20Central%20Tropical%20Indian%20Ocean&rft.jtitle=Journal%20of%20geophysical%20research.%20Oceans&rft.au=Hu,%20Qiwei&rft.date=2022-10&rft.volume=127&rft.issue=10&rft.epage=n/a&rft.issn=2169-9275&rft.eissn=2169-9291&rft_id=info:doi/10.1029/2021JC018227&rft_dat=%3Cproquest_cross%3E2729009906%3C/proquest_cross%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2729009906&rft_id=info:pmid/&rfr_iscdi=true |