Declined trends of chlorophyll <i>a</i> in the South China Sea over 2005−2019 from remote sensing reconstruction

Tianhao Wang; Yu Sun; Hua Su; Wenfang Lu

doi:10.1007/s13131-022-2097-y

Volume 42 Issue 1

Jan. 2023

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Tianhao Wang, Yu Sun, Hua Su, Wenfang Lu. Declined trends of chlorophyll a in the South China Sea over 2005−2019 from remote sensing reconstruction[J]. Acta Oceanologica Sinica, 2023, 42(1): 12-24. doi: 10.1007/s13131-022-2097-y

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Tianhao Wang, Yu Sun, Hua Su, Wenfang Lu. Declined trends of chlorophyll a in the South China Sea over 2005−2019 from remote sensing reconstruction[J]. Acta Oceanologica Sinica, 2023, 42(1): 12-24. doi: 10.1007/s13131-022-2097-y

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Declined trends of chlorophyll a in the South China Sea over 2005−2019 from remote sensing reconstruction

doi: 10.1007/s13131-022-2097-y

Tianhao Wang^{3, 4},
Yu Sun^{5, 6},
Hua Su^{5, 6},
Wenfang Lu^{1, 2
,
,}

1.
School of Marine Sciences, Sun Yat-Sen University, Zhuhai 519000, China
2.
Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai 519000, China
3.
College of Ocean and Earth Sciences, Xiamen University, Xiamen 361102, China
4.
State Key Laboratory of Marine Environmental Science, Xiamen University, Xiamen 361102, China
5.
Key Laboratory of Spatial Data Mining and Information Sharing of Ministry of Education, Fuzhou University, Fuzhou 350108, China
6.
National & Local Joint Engineering Research Center of Satellite Geospatial Information Technology, Fuzhou University, Fuzhou 350108, China

Funds: The National Natural Science Foundation of China under contract No. 41906019.

More Information

Corresponding author: E-mail: luwf6@sysu.edu.cn
Received Date: 2022-01-27
Accepted Date: 2022-08-15

Available Online: 2022-10-28

Publish Date: 2023-01-25

Abstract

Abstract

Chlorophyll a concentration (CHL) is an important proxy of the marine ecological environment and phytoplankton production. Long-term trends in CHL of the South China Sea (SCS) reflect the changes in the ecosystem’s productivity and functionality in the regional carbon cycle. In this study, we applied a previously reconstructed 15-a (2005−2019) CHL product, which has a complete coverage at 4 km and daily resolutions, to analyze the long-term trends of CHL in the SCS. Quantile regression was used to elaborate on the long-term trends of high, median, and low CHL values, as an extended method of conventional linear regression. The results showed downward trends of the SCS CHL for the 75th, 50th, and 25th quantile in the past 15 a, which were −0.004 0 mg/(m³·a) (−1.62% per year), −0.002 3 mg/(m³·a) (−1.10% per year), and −0.001 9 mg/(m³·a) (−1.01% per year). The negative trends in winter (November to March) were more prominent than those in summer (May to September). In terms of spatial distribution, the downward trend was more significant in regions with higher CHL. These led to a reduced standard deviation of CHL over time and space. We further explored the influence of various dynamic factors on CHL trends for the entire SCS and two typical systems (winter Luzon Strait (LZ) and summer Vietnam Upwelling System (SV)) with single-variate linear regression and multivariate Random Forest analysis. The multivariate analysis suggested the CHL trend pattern can be best explained by the trends of wind speed and mixed-layer depth. The divergent importance of controlling factors for LZ and SV can explain the different CHL trends for the two systems. This study expanded our understanding of the long-term changes of CHL in the SCS and provided a reference for investigating changes in the marine ecosystem.
- chlorophyll a concentration,
- quantile trends,
- remote sensing reconstruction,
- South China Sea

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References

Aumont O, Belviso S, Monfray P. 2002. Dimethylsulfoniopropionate (DMSP) and dimethylsulfide (DMS) sea surface distributions simulated from a global three-dimensional ocean carbon cycle model. Journal of Geophysical Research: Oceans, 107(C4): 3029. doi: 10.1029/1999JC000111

Barbosa S M. 2008. Quantile trends in Baltic sea level. Geophysical Research Letters, 35(22): L22704. doi: 10.1029/2008GL035182

Bassett Jr G, Koenker R. 1978. Regression quantiles. Econometrica, 46(1): 33–50. doi: 10.2307/1913643

Behrenfeld M J, Falkowski P G. 1997. Photosynthetic rates derived from satellite-based chlorophyll concentration. Limnology and Oceanography, 42(1): 1–20. doi: 10.4319/lo.1997.42.1.0001

Belkin I M, O’Reilly J E. 2009. An algorithm for oceanic front detection in chlorophyll and SST satellite imagery. Journal of Marine Systems, 78(3): 319–326. doi: 10.1016/j.jmarsys.2008.11.018

Beniston M. 2009. Trends in joint quantiles of temperature and precipitation in Europe since 1901 and projected for 2100. Geophysical Research Letters, 36(7): L07707

Birol F, Fuller N, Lyard F, et al. 2017. Coastal applications from nadir altimetry: example of the X-TRACK regional products. Advances in Space Research, 59(4): 936–953. doi: 10.1016/j.asr.2016.11.005

Boon A R, Duineveld G C A. 1998. Chlorophyll a as a marker for bioturbation and carbon flux in southern and central North Sea sediments. Marine Ecology Progress Series, 162: 33–43. doi: 10.3354/meps162033

Boyce D G, Lewis M R, Worm B. 2010. Global phytoplankton decline over the past century. Nature, 466(7306): 591–596. doi: 10.1038/nature09268

Breiman L. 2001. Random forests. Machine Learning, 45(1): 5–32. doi: 10.1023/A:1010933404324

Carder K L, Chen F R, Lee Z P, et al. 1999. Semianalytic Moderate-Resolution Imaging Spectrometer algorithms for chlorophyll a and absorption with bio-optical domains based on nitrate-depletion temperatures. Journal of Geophysical Research: Oceans, 104(C3): 5403–5421. doi: 10.1029/1998JC900082

Casella D, Meloni M, Petrenko A A, et al. 2020. Coastal current intrusions from satellite altimetry. Remote Sensing, 12(22): 3686. doi: 10.3390/rs12223686

Chen Yuh-ling Lee, Chen Houng-Yung, Karl D M, et al. 2004. Nitrogen modulates phytoplankton growth in spring in the South China Sea. Continental Shelf Research, 24(4–5): 527–541

Chen Liqi, Xu Suqing, Gao Zhongyong, et al. 2011. Estimation of monthly air-sea CO₂ flux in the southern Atlantic and Indian Ocean using in-situ and remotely sensed data. Remote Sensing of Environment, 115(8): 1935–1941. doi: 10.1016/j.rse.2011.03.016

Chen Chen-Tung Arthur, Yu Shujie, Huang Ting-Hsuan, et al. 2020. Changing biogeochemistry in the South China Sea. In: Chen Chen-Tung Arthur, Guo Xinyu, eds. Changing Asia-Pacific Marginal Seas. Singapore: Springer, 203–216

Dai Minhan, Cao Zhimian, Guo Xianghui, et al. 2013. Why are some marginal seas sources of atmospheric CO₂?. Geophysical Research Letters, 40(10): 2154–2158. doi: 10.1002/grl.50390

Dai Minhan, Su Jianzhong, Zhao Yangyang, et al. 2022. Carbon fluxes in the coastal ocean: synthesis, boundary processes, and future trends. Annual Review of Earth and Planetary Sciences, 50: 593–626. doi: 10.1146/annurev-earth-032320-090746

Doney S C, Lima I, Moore J K, et al. 2009. Skill metrics for confronting global upper ocean ecosystem-biogeochemistry models against field and remote sensing data. Journal of Marine Systems, 76(1–2): 95–112

Duan Rui, Yang Kunde, Ma Yuanliang, et al. 2012. A study of the mixed layer of the South China Sea based on the multiple linear regression. Acta Oceanologica Sinica, 31(6): 19–31. doi: 10.1007/s13131-012-0250-8

Dunstan P K, Foster S D, King E, et al. 2018. Global patterns of change and variation in sea surface temperature and chlorophyll a. Scientific Reports, 8(1): 14624. doi: 10.1038/s41598-018-33057-y

Fan Lijun, Chen Deliang. 2016. Trends in extreme precipitation indices across China detected using quantile regression. Atmospheric Science Letters, 17(7): 400–406. doi: 10.1002/asl.671

Feng Wei, Zhong Min, Xu Houze. 2012. Sea level variations in the South China Sea inferred from satellite gravity, altimetry, and oceanographic data. Science China: Earth Sciences, 55(10): 1696–1701. doi: 10.1007/s11430-012-4394-3

Feng Jianfeng, Zhu Lin. 2012. Changing trends and relationship between global ocean chlorophyll and sea surface temperature. Procedia Environmental Sciences, 13: 626–631. doi: 10.1016/j.proenv.2012.01.054

Gan Jianping, Lu Zhongming, Dai Minhan, et al. 2010. Biological response to intensified upwelling and to a river plume in the northeastern South China Sea: a modeling study. Journal of Geophysical Research: Oceans, 115(C9): C09001

Gao Meng, Franzke C L E. 2017. Quantile regression–based spatiotemporal analysis of extreme temperature change in China. Journal of Climate, 30(24): 9897–9914. doi: 10.1175/JCLI-D-17-0356.1

Gao Na, Ma Yi, Zhao Mingli, et al. 2020. Quantile analysis of long-term trends of near-surface chlorophyll-a in the Pearl River plume. Water, 12(6): 1662. doi: 10.3390/w12061662

Gao Shan, Wang Hui. 2008. Seasonal and spatial distributions of phytoplankton biomass associated with monsoon and oceanic environments in the South China Sea. Acta Oceanologica Sinica, 27(6): 17–32

Gao Shan, Wang Hui, Liu Guimei, et al. 2013. Spatio-temporal variability of chlorophyll a and its responses to sea surface temperature, winds and height anomaly in the western South China Sea. Acta Oceanologica Sinica, 32(1): 48–58. doi: 10.1007/s13131-013-0266-8

Goh S C, Knight K. 2009. Nonstandard quantile-regression inference. Econometric Theory, 25(5): 1415–1432. doi: 10.1017/S0266466609090719

Grémillet D, Lewis S, Drapeau L, et al. 2008. Spatial match-mismatch in the Benguela upwelling zone: should we expect chlorophyll and sea-surface temperature to predict marine predator distributions?. Journal of Applied Ecology, 45(2): 610–621. doi: 10.1111/j.1365-2664.2007.01447.x

Guo Lin, Xiu Peng, Chai Fei, et al. 2017. Enhanced chlorophyll concentrations induced by Kuroshio intrusion fronts in the northern South China Sea. Geophysical Research Letters, 44(22): 11565–11572. doi: 10.1002/2017GL075336

Hersbach H, Bell B, Berrisford P, et al. 2020. The ERA5 global reanalysis. Quarterly Journal of the Royal Meteorological Society, 146(730): 1999–2049. doi: 10.1002/qj.3803

Huynh H N T, Alvera-Azcárate A, Beckers J M. 2020. Analysis of surface chlorophyll a associated with sea surface temperature and surface wind in the South China Sea. Ocean Dynamics, 70(1): 139–161. doi: 10.1007/s10236-019-01308-9

Jang P G, Lee T S, Kang J H, et al. 2013. The influence of thermohaline fronts on chlorophyll a concentrations during spring and summer in the southeastern Yellow Sea. Acta Oceanologica Sinica, 32(9): 82–90. doi: 10.1007/s13131-013-0355-8

Keiner L E, Yan X H. 1998. A neural network model for estimating sea surface chlorophyll and sediments from thematic mapper imagery. Remote Sensing of Environment, 66(2): 153–165. doi: 10.1016/S0034-4257(98)00054-6

Koenker R, Hallock K F. 2001. Quantile regression. Journal of Economic Perspectives, 15(4): 143–156. doi: 10.1257/jep.15.4.143

Kosaka Y, Xie Shangping. 2013. Recent global-warming hiatus tied to equatorial Pacific surface cooling. Nature, 501(7467): 403–407. doi: 10.1038/nature12534

Kouketsu S, Kaneko H, Okunishi T, et al. 2016. Mesoscale eddy effects on temporal variability of surface chlorophyll a in the Kuroshio Extension. Journal of Oceanography, 72(3): 439–451. doi: 10.1007/s10872-015-0286-4

Landerer F W, Flechtner F M, Save H, et al. 2020. Extending the global mass change data record: GRACE Follow-On instrument and science data performance. Geophysical Research Letters, 47(12): e2020GL088306

Lee K, Baek H J, Cho C H. 2013. Analysis of changes in extreme temperatures using quantile regression. Asia-Pacific Journal of Atmospheric Sciences, 49(3): 313–323. doi: 10.1007/s13143-013-0030-1

Lévy M, Franks P J S, Smith K S. 2018. The role of submesoscale currents in structuring marine ecosystems. Nature Communications, 9(1): 4758. doi: 10.1038/s41467-018-07059-3

Li Yuanlong, Han Weiqing, Wilkin J L, et al. 2014. Interannual variability of the surface summertime eastward jet in the South China Sea. Journal of Geophysical Research: Oceans, 119(10): 7205–7228. doi: 10.1002/2014JC010206

Li Yan, Wang Qingyuan, Li Qingquan, et al. 2021. An asymmetric variation of hot and cold SST extremes in the China Seas during the recent warming hiatus period. Scientific Reports, 11(1): 2014. doi: 10.1038/s41598-020-79854-2

Liao Enhui, Lu Wenfang, Yan Xiaohai, et al. 2015. The coastal ocean response to the global warming acceleration and hiatus. Scientific Reports, 5(1): 16630. doi: 10.1038/srep16630

Liu K K, Chao S Y, Shaw P T, et al. 2002. Monsoon-forced Chlorophyll distribution and primary production in the South China Sea: Observations and a numerical study. Deep-Sea Research Part I: Oceanographic Research Papers, 49(8): 1387–1412. doi: 10.1016/S0967-0637(02)00035-3

Liu Jianguo, Chen Muhong, Chen Zhong, et al. 2010. Clay mineral distribution in surface sediments of the South China Sea and its significance for in sediment sources and transport. Chinese Journal of Oceanology and Limnology, 28(2): 407–415. doi: 10.1007/s00343-010-9057-7

Liu Fenfen, Chen Chuqun, Zhan Haigang. 2012. Decadal variability of chlorophyll a in the South China Sea: a possible mechanism. Chinese Journal of Oceanology and Limnology, 30(6): 1054–1062. doi: 10.1007/s00343-012-1282-9

Liu Xiao, Levine N M. 2016. Enhancement of phytoplankton chlorophyll by submesoscale frontal dynamics in the North Pacific Subtropical Gyre. Geophysical Research Letters, 43(4): 1651–1659. doi: 10.1002/2015GL066996

Liu Fenfen, Tang Shilin. 2022. A Double-peak intraseasonal pattern in the chlorophyll concentration associated with summer upwelling and mesoscale eddies in the western South China Sea. Journal of Geophysical Research: Oceans, 127(1): e2021JC017402

Liu Jianguo, Xiang Rong, Chen Zhong, et al. 2013. Sources, transport and deposition of surface sediments from the South China Sea. Deep-Sea Research Part I: Oceanographic Research Papers, 71: 92–102. doi: 10.1016/j.dsr.2012.09.006

Longhurst A, Sathyendranath S, Platt T, et al. 1995. An estimate of global primary production in the ocean from satellite radiometer data. Journal of Plankton Research, 17(6): 1245–1271. doi: 10.1093/plankt/17.6.1245

Lu Wenfang, Luo Yawei, Yan Xiaohai, et al. 2018a. Modeling the contribution of the microbial carbon pump to carbon sequestration in the South China Sea. Science China: Earth Sciences, 61(11): 1594–1604. doi: 10.1007/s11430-017-9180-y

Lu Wenfang, Oey L Y, Liao Enhui, et al. 2018b. Physical modulation to the biological productivity in the summer Vietnam upwelling system. Ocean Science, 14(5): 1303–1320. doi: 10.5194/os-14-1303-2018

Lu Wenfang, Su Hua, Yang Xin, et al. 2019. Subsurface temperature estimation from remote sensing data using a clustering-neural network method. Remote Sensing of Environment, 229: 213–222. doi: 10.1016/j.rse.2019.04.009

Lu Wenfang, Yan Xiaohai, Jiang Yuwu. 2015. Winter bloom and associated upwelling northwest of the Luzon Island: a coupled physical-biological modeling approach. Journal of Geophysical Research: Oceans, 120(1): 533–546. doi: 10.1002/2014JC010218

Ma Jinfeng, Liu Hailong, Zhan Haigang, et al. 2012. Effects of chlorophyll on upper ocean temperature and circulation in the upwelling regions of the South China Sea. Aquatic Ecosystem Health & Management, 15(2): 127–134

Martinez E, Gorgues T, Lengaigne M, et al. 2020. Reconstructing global chlorophyll-a variations using a non-linear statistical approach. Frontiers in Marine Science, 7: 464. doi: 10.3389/fmars.2020.00464

Ni Qinbiao, Zhai Xiaoming, Wilson C, et al. 2021. Submesoscale eddies in the South China Sea. Geophysical Research Letters, 48(6): e2020GL091555

Palacz A P, Xue Huijie, Armbrecht C, et al. 2011. Seasonal and inter-annual changes in the surface chlorophyll of the South China Sea. Journal of Geophysical Research: Oceans, 116(C9): C09015

Shen Chunyan, Zhao Hui, Chen Fajin, et al. 2020. The distribution of aerosols and their impacts on chlorophyll-a distribution in the South China Sea. Journal of Geophysical Research: Biogeosciences, 125(6): e2019JG005490

Su Hua, Wu Xiangbai, Lu Wenfang, et al. 2017. Inconsistent subsurface and deeper ocean warming signals during recent global warming and hiatus. Journal of Geophysical Research: Oceans, 122(10): 8182–8195. doi: 10.1002/2016JC012481

Tang Shilin, Liu Fenfen. 2020. Remote sensing of phytoplankton decline during the late 1980s and early 1990s in the South China Sea. International Journal of Remote Sensing, 41(15): 6010–6021. doi: 10.1080/01431161.2020.1718241

Wahr J, Molenaar M, Bryan F. 1998. Time variability of the Earth’s gravity field: hydrological and oceanic effects and their possible detection using GRACE. Journal of Geophysical Research: Solid Earth, 103(B12): 30205–30229. doi: 10.1029/98JB02844

Wang Guizhi, Shen S S P, Chen Yao, et al. 2021a. Feasibility of reconstructing the summer basin-scale sea surface partial pressure of carbon dioxide from sparse in situ observations over the South China Sea. Earth System Science Data, 13(3): 1403–1417. doi: 10.5194/essd-13-1403-2021

Wang Tianhao, Yu Peng, Wu Zelun, et al. 2021b. Revisiting the intraseasonal variability of chlorophyll-a in the adjacent Luzon Strait with a new gap-filled remote sensing data set. IEEE Transactions on Geoscience and Remote Sensing, 60: 4201311

Watkins M M, Wiese D N, Yuan Dah-Ning, et al. 2015. Improved methods for observing Earth’s time variable mass distribution with GRACE using spherical cap mascons. Journal of Geophysical Research: Solid Earth, 120(4): 2648–2671. doi: 10.1002/2014JB011547

Wiese D N, Landerer F W, Watkins M M. 2016. Quantifying and reducing leakage errors in the JPL RL05M GRACE mascon solution. Water Resources Research, 52(9): 7490–7502. doi: 10.1002/2016WR019344

Wiese D N, Yuan D N, Boening C, et al. 2018. JPL GRACE Mascon Ocean, Ice, and Hydrology Equivalent Water Height Release 06 Coastal Resolution Improvement (CRI) Filtered Version 1.0. Pasadena: DAAC

Wilson C, Adamec D. 2001. Correlations between surface chlorophyll and sea surface height in the tropical Pacific during the 1997–1999 El Niño-Southern Oscillation event. Journal of Geophysical Research: Oceans, 106(C12): 31175–31188. doi: 10.1029/2000JC000724

Xiao Wupeng, Wang Lei, Laws E, et al. 2018. Realized niches explain spatial gradients in seasonal abundance of phytoplankton groups in the South China Sea. Progress in Oceanography, 162: 223–239. doi: 10.1016/j.pocean.2018.03.008

Xie Shangping, Xie Qiang, Wang Dongxiao, et al. 2003. Summer upwelling in the South China Sea and its role in regional climate variations. Journal of Geophysical Research: Oceans, 108(C8): 3261. doi: 10.1029/2003JC001867

Yan Xiaohai, Boyer T, Trenberth K, et al. 2016. The global warming hiatus: slowdown or redistribution?. Earth’s Future, 4(11): 472–482. doi: 10.1002/2016EF000417

Yang Yuanjian, Xian Tao, Sun Liang, et al. 2012. Summer monsoon impacts on chlorophyll-a concentration in the middle of the South China Sea: climatological mean and annual variability. Atmospheric and Oceanic Science Letters, 5(1): 15–19. doi: 10.1080/16742834.2012.11446961

Ye Haijun, Kalhoro M A, Morozov E, et al. 2018. Increased chlorophyll-a concentration in the South China Sea caused by occasional sea surface temperature fronts at peripheries of eddies. International Journal of Remote Sensing, 39(13): 4360–4375. doi: 10.1080/01431161.2017.1399479

Yu Yi, Wang Yuntao, Cao Lu, et al. 2020. The ocean-atmosphere interaction over a summer upwelling system in the South China Sea. Journal of Marine Systems, 208: 103360. doi: 10.1016/j.jmarsys.2020.103360

Yu Yi, Zhang Haoran, Jin Jiangbo, et al. 2019. Trends of sea surface temperature and sea surface temperature fronts in the South China Sea during 2003–2017. Acta Oceanologica Sinica, 38(4): 106–115. doi: 10.1007/s13131-019-1416-4

Zhao Hui, Tang Danling. 2007. Effect of 1998 El Niño on the distribution of phytoplankton in the South China Sea. Journal of Geophysical Research: Oceans, 112(C2): C02017

Zhao Kaiguang, Wulder M A, Hu Tongxi, et al. 2019. Detecting change-point, trend, and seasonality in satellite time series data to track abrupt changes and nonlinear dynamics: a Bayesian ensemble algorithm. Remote Sensing of Environment, 232: 111181. doi: 10.1016/j.rse.2019.04.034

Zheng Quanan, Xie Lingling, Xiong Xuejun, et al. 2020. Progress in research of submesoscale processes in the South China Sea. Acta Oceanologica Sinica, 39(1): 1–13. doi: 10.1007/s13131-019-1521-4

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