the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
A High Dense Temperature-Salinity Dataset Observed by Automatic Underwater Vehicles toward Mesoscale eddies’ Evolutions and Associated Submesoscale Processes in South China Sea
Abstract. Marginal seas are usually fulfilled with strongly varying mesoscale eddies (MEs), which evolutions plays vital roles in regulating global oceanic energy equilibrium, triggering subemesoscale processes with strong vertical velocity, and inducing high biogeochemistry transport. But the temporal evolutions of MEs and submesoscale processes with several kilometers’ resolutions are difficult to be measured by traditional observations with passive working mode. The automatic underwater gliders (AUGs) and vehicles (AUVs) positively observe oceanic motion, and could provide us spatiotemporal synchronization information for strongly varying MEs. Here, we present a 9-year high dense dataset of AUVs/AUGs observations in 2014–2022 in the South China Sea (SCS) can be downloaded from https://doi.org/10.57760/sciencedb.11996 (Qiu et al., 2024b). Totally, 9 AUG and 2 AUV cruise experiments were conducted, and 83 AUGs (2 AUVs) equipment were deployed with zonal and temporal resolutions of < 7 km and <6 hour. It covers the area of eddy’s birth, propagation, and dissipation, presenting us the most complete data to investigate the evolution of MEs at different life stages. 40 % of them reach resolutions < 1 km and < 1 hour, which provides us the dynamic characteristics of submesoscale instabilities across and along front at the eddy edge. This dataset has potential in improving the forecast accuracy in physical and biogeochemistry numerical model. Much more aggressive field investigation programs will be promoted by the NSFC in future.
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Status: open (until 07 Nov 2024)
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CC1: 'Comment on essd-2024-338', Luo Yao, 16 Sep 2024
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The article highlights the crucial role of mesoscale eddy (ME) evolution in regulating the global ocean energy balance, triggering sub-mesoscale processes with strong vertical velocities, and inducing significant biogeochemical transport. It presents a remarkable dataset collected from the South China Sea (SCS) over nine years (2014-2022), using 83 AUG (2 AUV) devices, providing high-resolution observations with spatial resolution under 7 km and temporal resolution of less than 6 hours.
The cost of acquiring such high-quality, long-duration data is extremely high, making it inaccessible for many researchers. However, the availability of this dataset offers a valuable resource for the scientific community, serving as foundational data for numerous studies. It also has the potential to enhance the accuracy of both physical and biogeochemical numerical models, significantly advancing research in these areas.
Citation: https://doi.org/10.5194/essd-2024-338-CC1 -
RC1: 'Comment on essd-2024-338', Anonymous Referee #1, 08 Oct 2024
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Hello,
The Authors certainly have the promise of a very exciting data set that I would like to see published. Unfortunately, there are some major issues with this paper that mean it should be rejected, although if corrected could be resubmitted to this journal possibly. My notes are below:
- The data itself as found at the link in the abstract are unusable and seem to be incomplete. The data set spoken about in this paper needs to be completely detailed and metadata provided. There are international best practices for what to include as glider data metadata e.g. oceangliders.org. The data provided here are not even close to that and so are not really usable by the scientific community.
- The journal’s aims specifically exclude the interpretation of the dataset which I believe the authors begin to do. While it is exciting to see what can be learned from such a data set it is best left for another paper (which I hope the authors write).
- The paper needs a restructure so that the motivations of the data collection are in the introduction. These need to be properly referenced.
- The colouring of all figures should be reviewed with colourblind folks in mind. E.g. Figure 1 could have the SLA in grey scale.
- QA/QC of this data set should be undertaken as per international standard where it exists – e.g. IOOS. That could be taken further and local knowledge applied as per 3.1, but choices of acceptable salinity ranges etc should be justified (referenced).
- The vehicles themselves can be referenced – other works have previously described them.
- Important detail about collection of the data are missing, these could include:
- Vehicle name/serial number
- Deployment location and recovery
- Waypoints
- Any challenges during missions e.g. malfunctioning sensors, bad/false bottom hits, requirements or challenges for vehicle course
- Accumulation of biofouling
- Power management strategies that may affect any of the data
- Any other notes from the piloting team
- All oceanographic data need a matching time, latitude, and longitude. How the location underwater was determined needs to be noted, and any interpolation needs to be explained fully. Any derived values (e.g. density) also need to be described. All units must be provided.
- Sampling intervals should be noted.
- Very importantly these are AUTONOMOUS underwater vehicles and AUTONOMOUS underwater gliders not “automatic”. This must be corrected throughout. The authors need to take care to use the correct words so that their work fits appropriately within the greater body of knowledge and can be searched.
- Table 3 indicates that there are data channels (chlorophyll, dissolved oxygen etc) that are not evident in the downloadable data files, those data should be made available or mention of them removed.
I look forward to seeing this data set published in a useable way.
Citation: https://doi.org/10.5194/essd-2024-338-RC1
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