Preprints
https://doi.org/10.5194/essd-2024-338
https://doi.org/10.5194/essd-2024-338
09 Sep 2024
 | 09 Sep 2024
Status: this preprint is currently under review for the journal ESSD.

A High Dense Temperature-Salinity Dataset Observed by Automatic Underwater Vehicles toward Mesoscale eddies’ Evolutions and Associated Submesoscale Processes in South China Sea

Chunhua Qiu, Zhenyang Du, Jiancheng Yu, Huabin Mao, Haibo Tang, Zhenhui Yi, Jiawei Qiao, Dongxiao Wang, Xiaoming Zhai, and Yeqiang Shu

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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Chunhua Qiu, Zhenyang Du, Jiancheng Yu, Huabin Mao, Haibo Tang, Zhenhui Yi, Jiawei Qiao, Dongxiao Wang, Xiaoming Zhai, and Yeqiang Shu

Status: open (until 07 Nov 2024)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • CC1: 'Comment on essd-2024-338', Luo Yao, 16 Sep 2024 reply
  • RC1: 'Comment on essd-2024-338', Anonymous Referee #1, 08 Oct 2024 reply
  • 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
Chunhua Qiu, Zhenyang Du, Jiancheng Yu, Huabin Mao, Haibo Tang, Zhenhui Yi, Jiawei Qiao, Dongxiao Wang, Xiaoming Zhai, and Yeqiang Shu
Chunhua Qiu, Zhenyang Du, Jiancheng Yu, Huabin Mao, Haibo Tang, Zhenhui Yi, Jiawei Qiao, Dongxiao Wang, Xiaoming Zhai, and Yeqiang Shu

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Short summary
The high dense AUVs’ dataset in SCS provides 24498 temperature and salinity profiles and covers 463 days’ experiments, including 83 AUGs’ and 2 AUVs’ experiments. To our knowledge, the resolution and length of this dataset is enough in detecting the asymmetry, vertical tilt, temporal evolution of MEs, and the submesoscale processes. The dataset is expected to improve the accuracy of current and biogeochemistry numerical model. More projects gathering AUVs network will be promoted in future.
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