the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Eddy-induced chlorophyll profile characteristics and underlying dynamic mechanisms in the South Pacific Ocean
Meng Hou
Jie Yang
Ge Chen
Guiyan Han
Yan Wang
Kai Wu
Abstract. Many studies have consistently demonstrated that the near-surface phytoplankton chlorophyll (Chl) levels in anticyclonic eddies (AEs) are higher than in cyclonic eddies (CEs) in the South Pacific Ocean (SPO) using remote sensing data, which is attributed to higher phytoplankton biomass or physiological adjustments in AEs. However, the characteristics of the Chl profile induced by mesoscale eddies and their underlying dynamic mechanism have not been comprehensively studied by means of field measurement. In this study, we mainly utilized BGC-Argo data to investigate the relationships between Chl levels and environmental factors (CPhyto, Nitrate, Temperature and Light) and the underlying dynamic mechanisms of mesoscale eddies in SPO. Our findings showed that, the elevated Chl levels in AEs primarily result from increased phytoplankton biomass within the Mixed Layer Depth (MLD), which is induced by enhanced nutrient availability due to the deepening MLD in AEs. At depths ranging from 50 m to 110 m (the depth between the bottom of the mixed layer and pycnocline), the dominant factor affecting higher Chl levels in CEs is the physiological adaptation of phytoplankton, driven by reduced temperature and light availability. Between 110 m and 150 m (near the depth of pycnocline or bottom of the euphotic zone), both phytoplankton biomass induced by eddy pumping and physiological adjustments for lower light and temperature contributed to higher Chl levels in CEs. At depths exceeding 150 m (beyond the euphotic zone), higher Chl in AEs is primarily influenced by phytoplankton biomass as a result of the downwelling by eddy pumping. To a certain extent, this work would advance our comprehensive understanding of the physical-biological interactions of mesoscale eddies and their impacts on primary productivity throughout the water column, which has important implications for accurately assessing the biogeochemical processes and ocean carbon cycle.
- Preprint
(1615 KB) - Metadata XML
- BibTeX
- EndNote
Meng Hou et al.
Status: open (until 26 Oct 2023)
-
RC1: 'Comment on egusphere-2023-1735', Anonymous Referee #1, 04 Oct 2023
reply
General comments :
In part 2.3 the authors mentioned that they are using BGC-Argo delayed mode data for their study. Presently, the chlorophyll-A has not been qualified in delayed mode in the South Pacific area (https://biogeochemical-argo.org/cloud/document/implementation-status/BGC_summary.pdf) . So a very important comment, the authors should really improve the description of the dataset first.
The BGC-Argo chlorophyll-A qualification is very heterogeneous presently from a float to another and it is not mentioned in the manuscript. Moreover, there is no mention in the manuscript of the major feature of the Chlorophyll-A measurements, based on fluorescence. According to me it requires careful use of this Chlorophyll-A dataset without ignoring this feature.Â
I think that dealing with this issue is a prerequisite before trying to compare BGC-Argo Chlorophyll-A profiles with satellite data. The chlorophyll-A BGC-Argo, based on fluorescence data, are affected by the non photochemical quenching and this can have a huge impact on the Chlorophyll-A estimation mainly at the surface. Â
It is not clear in the manuscript whether the authors are using raw data from the BGC-Argo dataset or the adjusted fields (corrected in real-time of the quenching); this should be mentioned as a first step. Then, depending on the option chosen (raw vs. adjusted), the authors must describe their treatment of the data and explain in details the quality control that they are applying on the data (it is mentioned, but there is no details).Â
Comments on the Figures :Â Â
Considering that the MLD is close to 50m, it is hard to see that the figure 2 highlights any difference between AES and CES in CHL concentration as mentioned in the text, a zoom of the figure could be added.Â
Still on the BGC-Argo dataset, the figure 4c. is not obviously illustrating an increase of nutrients in the area of 50m to 110m as mentioned by the authors, from AES to CES. If the BGC-Argo data nitrate profiles are qualified in delayed mode as mentioned by the authors, they are provided with uncertainties and these uncertainties are within +-1 micromol per kg. I think that the authors should also consider carefully the uncertainties of the dataset before concluding.  Â
Based on these different remarks, to further evaluate whether this study is relevant, as it is presently difficult to check exactly what data are used, how they are qualified and whether the data are used correctly, the authors should consider revisiting deeply their "data" part (http://www.argodatamgt.org/) . It could be also useful to mention the Argo WMO of the floats that they are using in their study. These are the reasons why I think that this manuscript needs major revision before being reconsidered. Â
Citation: https://doi.org/10.5194/egusphere-2023-1735-RC1
Meng Hou et al.
Meng Hou et al.
Viewed
HTML | XML | Total | BibTeX | EndNote | |
---|---|---|---|---|---|
158 | 41 | 7 | 206 | 4 | 6 |
- HTML: 158
- PDF: 41
- XML: 7
- Total: 206
- BibTeX: 4
- EndNote: 6
Viewed (geographical distribution)
Country | # | Views | % |
---|
Total: | 0 |
HTML: | 0 |
PDF: | 0 |
XML: | 0 |
- 1