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Scattered Dataset of Global Ocean Temperature and Salinity Profiles from the International Argo Program


LIU Zenghong1LI Zhaoqin1LU Shaolei1WU Xiaofen1SUN Chaohui1XU Jianping1
1Second Institute of Oceanography,Ministry of Natural Resources of P. R. China,Hangzhou 310012,China

DOI:10.3974/geodb.2021.06.05.V1

Published:Jun. 2021

Visitors:1575       Data Files Downloaded:869      
Data Downloaded:356529.70 MB      Citations:

Key Words:

Argo,temperature,salinity,global,ocean

Abstract:

By the end of 2020, the International Argo Program has collected more than 2.3 million temperature and salinity (TS) profiles over the global oceans. Although the Argo Data Assembly Centers (DACs) from various countries conduct a quality control to each TS profile, Argo dataset are becoming more and more complicated which brings difficulties when users read and make use of them. In order to facilitate the usage of Argo dataset, China Argo Real-time Data Center (CARDC) has started to reconstructed the TS dataset after a post-quality-control. The dataset is archived in .dat format, and consists of 2,244,712 data files with data size of 41.1 GB (compressed to 18 files with 7.56 GB). The analysis paper related to the dataset was published at IOP Conference Series: Earth and Environmental Science, 502, 2020.

Foundation Item:

Ministry of Science and Technology of P. R. China (2012FY112300) Scientific Research Fund of the Second Institute of Oceanography, MNR (JG1709, JG1812); Zhejiang Natural Science Foundation (LQY18D060001); National Natural Science Foundation of China (U1811464)

Data Citation:

LIU Zenghong, LI Zhaoqin, LU Shaolei, WU Xiaofen, SUN Chaohui, XU Jianping. Scattered Dataset of Global Ocean Temperature and Salinity Profiles from the International Argo Program[J/DB/OL]. Digital Journal of Global Change Data Repository, 2021. https://doi.org/10.3974/geodb.2021.06.05.V1.

References:

[1] Argo Steering Team. On the design and implementation of Argo – An initial plan for the global array of profiling floats [M]. International CLIVAR Project Office Report, 1998: 32.
     [2] Roemmich, D. H., Davis, R. E., Riser, S. C., et al. The Argo Project: Global ocean observations for understanding and prediction of climate variability [R/OL]. https://www.nopp.org/wp-content/uploads/project-reports-cdrom/reports/02roemmi.pdf
     [3] Xu, J. P. Studies of Global Argo Ocean Observation [M]. Beijng: Ocean Press, 2002: 115.
     [4] Riser, S. C., Freeland, H. J., Roemmich, D., et al. Fifteen years of ocean observations with the global Argo array [J]. Nature Climate Change, 2016, 6(2): 145-153.
     [5] Liu, Z. H., Wu, X. F., Xu J. P., et al. China Argo Project: Progress in China Argo ocean observations and data applications [J]. Acta Oceanologica Sinica, 2017, 36(6): 1-11.
     [6] Oka, E., Ando, K. Stability of temperature and conductivity sensors of Argo Profiling Floats [J]. Journal of Oceanography, 2004, 60(2): 253-258.
     [7] Liu, Z. H., Zhu, B. K., Guo, M., et al. The test and deployment of Argo profiling float [J]. Ocean Technology, 2002(2): 13-24.
     [8] Bushinsky, S. M., Takeshita, Y., Williams, N. L. Observing changes in ocean Carbonate chemistry: Our autonomous future [J]. Current Climate Change Reports, 2019(5): 207-220.
     [9] Wong, A., Keeley, R., Carval, T., et al. Argo quality control manual for CTD and trajectory data [R], V3.3. 2020. DOI:10.13155/33951.
     [10] Kobayashi T., Minato, S. Importance of reference dataset improvements for Argo delayed-mode quality control [J]. Journal of Oceanography, 2005, 61(6): 995-1009.
     [11] Lu, S. L., Liu, Z. H., Sun C. H. Application of improved Argo salinity delayed-mode quality control method [J]. Journal of PLA University of Science and Technology(Natural Science Edition), 2016, 17(02):43-52.
     [12] Wong, A., Wijffels, S. E., Riser, S. C., et al. Argo data 1999–2019: Two million temperature-salinity profiles and subsurface velocity observations from a global array of profiling floats [J]. Frontiers in Marine Science, 2020, 7. DOI: 10.3389/fmars.2020.00700.
     [13] Owens, W. B., Wong, A. P. S. An improved calibration method for the drift of the conductivity sensor on autonomous CTD profiling floats by theta-S climatology [J]. Deep Sea Research Part I: Oceanographic Research Papers, 2009, 56(3): 450-457.
     [14] Bohme, L., Send, U. Objective analyses of hydrographic data for referencing profiling float salinities in highly variable environments [J]. Deep Sea Research, 2005, 52(3/4): 651-664.
     [15] Li, Z. Q., Liu, Z. H., Lu, S. L. Global Argo data fast receiving and post-quality-control-system [C]. IOP Conference Series: Earth and Environmental Science, 2020, 502: 012012. DOI: 10.1088/1755-1315/502/1/012012.
     

Data Product:

ID Data Name Data Size Operation
1 199707_200702.rar 398001.79KB
2 200703_200903.rar 395012.57KB
3 200904_201102.rar 426721.86KB
4 201103_201207.rar 427403.60KB
5 201208_201307.rar 435876.32KB
6 201308_201405.rar 447270.17KB
7 201406_201501.rar 404287.73KB
8 201502_201509.rar 446078.23KB
9 201510_201605.rar 497600.16KB
10 201606_201612.rar 460771.58KB
11 201701_201706.rar 404307.23KB
12 201707_201801.rar 493151.44KB
13 201802_201808.rar 506315.64KB
14 201809_201902.rar 443650.70KB
15 201903_201908.rar 462149.84KB
16 201909_202002.rar 484248.46KB
17 202003_202007.rar 401316.87KB
18 202008_202012.rar 395695.35KB
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