Influence of mixed layer depth on chlorophyll-a concentration in the Southern Ocean
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Abstract: The element iron limitation is one of the crucial factors contributing to high nutrient low chlorophyll in the Southern Ocean (SO). Mixed layer dynamics regulate the availability of iron to phytoplankton. In this paper, we investigate the influence of surface iron supplementation triggered by the mixed layer depth (MLD) variation on chlorophyll-a (Chl-a) concentration in the SO on seasonal and interannual timescales. This analysis is based on the Biogeochemical Southern Ocean State Estimate for the period from 2013 to 2021. We provide a comprehensive and systematic mapping of the regions within the SO, where Chl-a is affected by iron input related to MLD deepening. The relationship between the MLD and the Chl-a varies with the latitude on the seasonal time scale. Both the MLD and sea ice melting affect the distribution of Chl-a. On the interannual scale, iron supply due to MLD deepening occurs primarily north of 60°S. Horizontal advection-induced entrainment enhances the surface iron input during the austral summer, which favors Chl-a increase. In addition to the MLD, the melting of sea ice and cooling of the sea surface can also alter iron input and subsequently affect Chl-a distribution in the austral summer. During the austral winter, entrainment can boost iron stocks, stimulating a subsequent spring increase of Chl-a in the SO. Furthermore, sea surface temperature declines during the austral winter, promoting an increased iron supply and creating favorable conditions for the subsequent spring Chl-a increase in the SO.
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Key words:
- mixed layer depth /
- entrainment /
- chlorophyll-a concentration /
- Southern Ocean
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Figure 1. Seasonal cycle of MLD from B-SOSE (a–d) and WOD18 (e–h). The values represent the climatological mean over the period during 2013 to 2018. A region within the deep MLD band is randomly selected to test the credibility of B-SOSE (black box in Fig. 1). The seasons are defined as spring including March, April, and May (MAM), summer including June, July, and August (JJA), autumn including September, October, and November (SON) and winter including December, January, and February (DJF).
Figure 3. Time series of monthly MLD anomaly from B-SOSE and WOD18. The values are calculated by the black box depicted in Fig. 1. The asterisk (*) represents that the results are statistically significant at the 95% confidence level.
Figure 4. Time series of monthly Chl-a anomaly derived from B-SOSE and VIIRS sensor. The values are calculated by the black box depicted in Fig. 2. The asterisk (*) represents that the results are statistically significant at the 95% confidence level.
Figure 5. Maximum values of MLD (a) and Chl-a (d) and the occurrence time of maximum MLD (b, c) and Chl-a (e, f) from B-SOSE. b and e show the months when the maximum value occurs, c and f show the seasons when the maximum value occurs. The colored contours represent the edges of sea ice in four seasons. The black, cyan, blue, and pink contours represent austral spring, summer, autumn, and winter, respectively.
Figure 6. Strongest positive (a) and negative (d) correlation coefficients between the MLD and Chl-a and the time that Chl-a lags the MLD when the strongest correlation coefficient occurs (b, c, e, f). Figures 6a and d are statistically significant, and the statistically insignificant points have been removed. The colored contours represent the edges of sea ice in four seasons. The black, cyan, blue, and pink contours represent austral spring, summer, autumn, and winter, respectively.
Figure 12. Correlation coefficients between MLD anomaly and Chl-a anomaly in the austral spring (a), summer (b), autumn (c), and winter (d) MLD and spring Chl-a. The black, cyan, and pink contours represent the edges of sea ice in the austral spring, summer, and winter, respectively. White regions represent correlations with p > 0.05.
Figure 15. Time series and connections of the three terms in Eq. (2) (
$ {\partial {h}}/{\partial {t}} $ , the rate of MLD deepening;$ {{w}}_{{b}} $ , the vertical velocity at the ML base$ ; $ $ \overrightarrow{{V}}\cdot \nabla {h} $ , the horizontal advection (adv) of water in the ML) and iron anomalies in annual summer. The magnitudes are calculated by domain-averaged over Fig. 14a, where the MLD works in the austral summer.Figure 18. Time series and connections of three terms in Eq. (2) (
$ {\partial {h}}/{\partial {t}} $ , the rate of MLD deepening;$ {{w}}_{{b}} $ , the vertical velocity at the ML base$ ; $ $ \overrightarrow{{V}}\cdot \nabla {h} $ , the horizontal advection (adv) of water in the ML) and iron in annual winter. The magnitudes are calculated by domain-averaged over Fig. 17a, where the MLD works in winter.Figure 19. A schematic summarizing the response of phytoplankton biomass to various primary physical variables in the SO on seasonal (a, b) and interannual (c, d) time scales. a. Positively correlated regions, regions in pink (P1) and red (P2) represent regions of deep MLD with high Chl-a (positively correlated). b. Negatively correlated regions, regions in light blue (N1) and blue (N2) represent regions of deep MLD with low Chl-a (negatively correlated). Regions P1 and N1 exhibit synchronous responses of Chl-a to the MLD, while Regions P2 and N2 show a one-season lagged responses of Chl-a to the MLD. c. Synchronous influence regions, regions showing positive anomalies in summer Chl-a are associated with negative anomalies in summer SST (purple), positive anomalies in summer MLD (blue), and positive anomalies in summer SIC (red). d. Delayed influence regions, regions showing positive anomalies in spring Chl-a are associated with negative anomalies in winter SST (purple), positive anomalies in winter MLD (blue), and negative anomalies in winter SIC (red).
Table 1. Correlation coefficients for each term in Eq. (2) and the MLD and iron over Region P1 in summer
$ w $ $ \dfrac{\partial h}{\partial t} $ $ {w}_{b} $ $ \overrightarrow{V}\cdot \nabla h $ $ w $ – –0.07 0.26 0.40 MLD 0.29 –0.53 0.06 0.49 Fe 0.84* –0.16 0.24 0.39 Note: The asterisk (*) represents that the results are statistically significant at the 95% confidence level. – denotes no data. -
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