School of Oceanography, Shanghai Jiao Tong University, Shanghai 200240, China
2.
Yunnan Key Laboratory of Meteorological Disasters and Climate Resources in the Greater Mekong Subregion, Yunnan University, Kunming 600650, China
3.
Department of Atmospheric and Oceanic Science, University of Maryland at College Park, College Park 20742, USA
Funds:
The fund from Ministry of Science and Technology of the People’s Republic of China under contract No. 2023YFF0805204; the Natural Science Foundation of Yunnan Province under contract No. 202302AN360006; the National Natural Science Foundation of China under contract No. 41776019.
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 study, we investigate the influence of surface iron supplementation triggered by the mixed layer depth (MLD) variation on chlorophyll-a concentration (Chl-a) 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.
Figure 1. The seasonal cycle of MLD (unit: m) from B-SOSE (a)–(d) and WOD18 (e)–(h). The values represent the climatological mean over the period from 2013 to 2018. The black box in the subplot represents the same region as the black box in Fig. 2. 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 2. The seasonal cycle of Chl-a concentration (unit: mg/m3) from B-SOSE (a)–(d) and VIIRS (e)–(H) sensor. The values represent the climatological mean over the period from 2013 to 2021.
Figure 3. Time series of monthly MLD anomaly (unit: m) 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 (unit: mg/m3) 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. The maximum values of MLD (unit: m) (a) and Chl-a (unit: mg/m3) (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 7. Time series of MLD (a), Chl-a (b), and iron (c) in the selected regions (P1, P2, N1, and N2). The error bars represent the standard deviation.
Figure 8. Time series and connections of MLD, Chl, and iron in annual spring (a), summer (b), autumn (c), and winter (d) in Region P1. The magnitudes are calculated by domain-averaged over Region P1.
Figure 9. Time series and connections of MLD, Chl, and iron in annual spring (a), summer (b), autumn (c), and winter (d) in Region P2. The magnitudes are calculated by domain-averaged over Region P2.
Figure 10. Time series and connections of MLD, Chl, and iron in annual spring (a), summer (b), autumn (c), and winter (d) in Region N1. The magnitudes are calculated by domain-averaged over Region N1.
Figure 11. Time series and connections of MLD, Chl, and iron in annual spring (a), summer (b), autumn (c), and winter (d) in Region N2. The magnitudes are calculated by domain-averaged over Region N2.
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 13. Correlation coefficients between anomaly of iron and Chl-a (a), MLD (b) in the austral summer. White regions represent correlations with p > 0.05.
Figure 14. A schematic summarizing the response of Chl-a anomaly to the physical variables in the austral summer. The regions in blue, purple, and red indicate the areas where the influence of austral summer MLD, SST, and sea ice is significant, respectively.
Figure 15. Time series and connections of the three terms in Eq. (2) ($ \dfrac{\partial \boldsymbol{h}}{\partial \boldsymbol{t}} $, the rate of MLD deepening; $ {\boldsymbol{w}}_{\boldsymbol{b}} $, the vertical velocity at the ML base$ ; $$ \vec{\boldsymbol{V}}\cdot \nabla \boldsymbol{h} $, the horizontal advection of water in the ML) and iron anomalies in annual summer. The magnitudes are calculated by domain-averaged over Fig. 14a, where the MLD works in the austral summer.
Figure 16. Correlation coefficients of winter iron anomaly and spring Chl-a (a) and winter MLD (b). White regions represent correlations with p > 0.05.
Figure 17. A schematic summarizing the response of austral spring Chl-a anomaly to the physical variables in the austral winter. The regions in blue, purple, and red indicate the areas where austral winter MLD, SST, and sea ice influence are significant, respectively.
Figure 18. Time series and connections of three terms in Eq. (2) ($ \dfrac{\partial \boldsymbol{h}}{\partial \boldsymbol{t}} $, the rate of MLD deepening; $ {\boldsymbol{w}}_{\boldsymbol{b}} $, the vertical velocity at the ML base$ ; $$ \vec{\boldsymbol{V}}\cdot \nabla \boldsymbol{h} $, the horizontal advection 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).
DownLoad:
