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

Tianhao Wang Yu Sun Hua Su Wenfang Lu

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
Citation: 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

doi: 10.1007/s13131-022-2097-y

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

Funds: The National Natural Science Foundation of China under contract No. 41906019.
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  • Figure  1.  The cross-validation errors of SCSDCT. a. The spatial distribution of RMSE for ln[CHLrec (mg/m3)]; b. the density plot between OC-CCI and SCSDCT. The black dots and solid lines in a represent observation sites from Xiao et al. (2018) and the 50-m isobath. The black line in b is the 1:1 line, and the green one is the linear least-squared fit of scatters. MAPE: Mean Absolute Percentage Error. N is the number of points. The subscript rec represents reconstruction; sat, cross-validation set from satellite data set.

    Figure  2.  Scatter plots of in-situ observation versus CHLobs reconstruction (a) and observation versus original OC-CCI (b). The solid black lines represent x=y lines, and the red lines represent the regression lines. The subscript rec represents reconstruction; sat, cross-validation set from satellite data set; obs, in situ observations. N is the number of points.

    Figure  3.  Yearly- (a), winter- (b), and summer- (c) mean chlorophyll a concentration (CHL) in the South China Sea. The two red boxes represent the region of Vietnam Upwelling Systems (SV) (left) and Luzon Strait (LZ) (right). The black bold line is the 50-m isobath.

    Figure  4.  Trends of chlorophyll a concentration (CHL) in the whole year for linear trend (a) of the classic least squares model (LSM), 75th quantile (b), 50th quantile (c), and 25th quantile (d). Points that fail the significance test (p>0.05) are covered by white points.

    Figure  5.  The chlorophyll a concentration (CHL) trends in all quantiles range from 5th to 95th percentages every 5%. The vertical bars are standard errors in each regression.

    Figure  6.  The chlorophyll a concentration (CHL) trend of monthly standard deviation at each point (N=180) (a); points that failed the significance test (p>0.05) are covered by white points. Time series of spatial standard deviations (STD) of CHL (light blue, N=219552) (b), corresponding 30-days moving mean (thick blue), and the linear fit (dashed red).

    Figure  7.  Trends of chlorophyll a concentration (CHL) in winter (November to March of next year) for linear trend of the dassic least squares modle (LSM) (a), 75th quantile (b), 50th quantile (c), and 25th quantile (d). Points that fail the significance test (p>0.05) are covered by white points.

    Figure  8.  For the winter South China Sea (SCS) (black), Luzon Strait (LZ) (blue), and Vietnam Upwelling System (SV) (red), the corresponding trends in all quantiles range from 5th to 95th percentages with an interval of 5%. The vertical bars are standard errors in each regression. CHL: chlorophyll a concentration.

    Figure  9.  Trends of chlorophyll a concentration (CHL) in summer (May to September) for linear trend of the classic least squares model (LSM) (a), 75th quantile (b), 50th quantile (c), and 25th quantile (d). Points that fail the significance test (p>0.05) are covered by white points.

    Figure  10.  For the summer South China Sea (SCS) (black), Luzon Strait (LZ) (blue), and Vietnam Upwelling System (SV) (red), the corresponding trends in all quantiles range from 5th to 95th percentages with an interval of 5%. The vertical bars are standard errors in each regression. CHL: chlorophyll a concentration.

    Figure  11.  Sea surface water temperature (SST) trends for 75th quantile in whole year (a), winter (November to March of next year) (b), and summer (May to September) (c). All trends for SST can be found in Fig. S1.

    Figure  12.  For yearly sea surface temperature (SST) of the South China Sea (SCS) (black), winter SST (blue), and summer SST (red), the corresponding trends of all quantiles range from 5th to 95th percentages with an interval of 5%. The vertical bars are standard errors in each regression.

    Figure  13.  Wind speed trends for 75th quantile in whole year (a), winter (November to March of next year) (b), and summer (May to September) (c). All trends for the wind can be found in Fig. S2.

    Figure  14.  The mixed layer depth (MLD) trends for 75th quantile in whole year (a), winter (November to March of next year) (b), and summer (May to September) (c). All trends for MLD can be found in Fig. S3.

    Figure  15.  Gridded absolute dynamic height (ADT) trends for 75th quantile in whole year (a), winter (November to March of next year) (b), and summer (May to September) (c). The colored lines are along-track Sea Level Anomaly, with the same color bar. All trends for ADT can be found in Fig. S4.

    Figure  16.  Steric height (SH) trends for 75th quantile in whole year (a), winter (November to March of next year) (b), and summer (May to September) (c). All trends for SH can be found in Fig. S5.

    Figure  17.  Sea surface temperature front (SSTF) trends for 75th in whole year (a), winter (November to March of next year) (b), and summer (May to September) (c). All trends for SSTF can be found in Fig. S6.

    Figure  18.  The relative importance of each factor to Chlorophyll a concentration trends by repeating the Randon Forest analysis 100 times and taking the averaged importance. SST: sea surface temperature; MLD: mixed layer depth; ADT: gridded absolute dynamic height; SSTF: sea surface temperature front; SH: steric height.

    Table  1.   Correlation coefficients between trends of CHL and other factors*

    SSTWind speedMLDADTSSTFSH
    Whole year SCS (N=183393)−0.220.04−0.09−0.180.01−0.06
    Winter LZ (N=6281)−0.640.24−0.39−0.640.03−0.58
    Summer SV (N=13495)−0.380.420.100.060.28−0.14
    Note: * The p<0.01 for all correlations. SST: sea surface temperature; MLD: mixed layer depth; ADT: gridded absolute dynamic height; SSTF: sea surface temperature front; SH: steric height.
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  • 收稿日期:  2022-01-27
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