Real-time quality control of data from Sea-Wing underwater glider installed with Glider Payload CTD sensor

Zenghong Liu; Jianping Xu; Jiancheng Yu

doi:10.1007/s13131-020-1564-6

Volume 39 Issue 3

Apr. 2020

Turn off MathJax

Article Contents

Abstract

References

Article Navigation > Acta Oceanologica Sinica > 2020 > 39(3): 130-140

Qu Ke, Zhu Fengqin, Song Wenhua. A novel method for internal wave monitoring based on expansion of the sound speed profile[J]. Acta Oceanologica Sinica, 2019, 38(4): 183-189. doi: 10.1007/s13131-019-1422-6

Citation:

Zenghong Liu, Jianping Xu, Jiancheng Yu. Real-time quality control of data from Sea-Wing underwater glider installed with Glider Payload CTD sensor[J]. Acta Oceanologica Sinica, 2020, 39(3): 130-140. doi: 10.1007/s13131-020-1564-6

Citation:

PDF( 946 KB)

Real-time quality control of data from Sea-Wing underwater glider installed with Glider Payload CTD sensor

doi: 10.1007/s13131-020-1564-6

Zenghong Liu^{1, 2
,
,},
Jianping Xu^{1, 2},
Jiancheng Yu³

1.
State Key Laboratory of Satellite Ocean Environment Dynamics, Second Institute of Oceanography, Ministry of Natural Resources, Hangzhou 310012, China
2.
Second Institute of Oceanography, Ministry of Natural Resources, Hangzhou 310012, China
3.
State Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016, China

Funds: The National Natural Science Foundation under contract Nos 41621064, 41606003, U1709202 and U1811464; the National Key R&D Program of China under contract No. 2016YFC0301201; the China Association of Marine Affairs (“Study on the feasibility of establishing an international data sharing application platform for smart ocean”).

More Information

Corresponding author: E-mail: liuzenghong@139.com
Received Date: 2019-02-28
Accepted Date: 2019-06-03

Available Online: 2020-04-21

Publish Date: 2020-03-25

Abstract

Abstract

Profiles observed by Sea-Wing underwater gliders are widely applied in scientific research. However, the quality control (QC) of these data has received little attention. The mismatch between the temperature probe and conductivity cell response times generates erroneous salinities, especially across a strong thermocline. A sensor drift may occur owing to biofouling and biocide leakage into the conductivity cell when a glider has operated for several months. It is therefore critical to design a mature real-time QC procedure and develop a toolbox for the QC of Sea-Wing glider data. On the basis of temperature and salinity profiles observed by several Sea-Wing gliders each installed with a Sea-Bird Glider Payload CTD sensor, a real-time QC method including a thermal lag correction, Argo-equivalent real-time QC tests, and a simple post-processing procedure is proposed. The method can also be adopted for Petrel gliders.
- Sea-Wing underwater glider,
- Glider Payload CTD sensor,
- thermal lag correction,
- quality-control tests

FullText(HTML)

References(35)

References

[1]	Baird M E, Suthers I M, Griffin D A, et al. 2011. The effect of surface flooding on the physical-biogeochemical dynamics of a warm-core eddy off southeast Australia. Deep Sea Research Part II: Topical Studies in Oceanography, 58(5): 592–605. doi: 10.1016/j.dsr2.2010.10.002
[2]	Baltes B, Rudnick D, Crowley M, et al. 2014. Toward a U.S. IOOS^® Underwater glider network plan: part of a comprehensive subsurface observing system. Technical Report U S IOOS
[3]	Böhme L, Send U. 2005. Objective analyses of hydrographic data for referencing profiling float salinities in highly variable environments. Deep Sea Research Part II: Topical Studies in Oceanography, 52(3–4): 651–664. doi: 10.1016/j.dsr2.2004.12.014
[4]	Bouffard J, Pascual A, Ruiz S, et al. 2010. Coastal and mesoscale dynamics characterization using altimetry and gliders: a case study in the Balearic sea. Journal of Geophysical Research: Oceans, 115(C10): C10029. doi: 10.1029/2009JC006087
[5]	Bouffard J, Renault L, Ruiz S, et al. 2012. Sub-surface small-scale eddy dynamics from multi-sensor observations and modeling. Progress in Oceanography, 106: 62–79. doi: 10.1016/j.pocean.2012.06.007
[6]	Dobricic S, Pinardi N, Testor P, et al. 2010. Impact of data assimilation of glider observations in the Ionian Sea (Eastern Mediterranean). Dynamics of Atmospheres and Oceans, 50(1): 78–92. doi: 10.1016/j.dynatmoce.2010.01.001
[7]	Dong J L, Domingues R, Goni G, et al. 2017. Impact of assimilating underwater glider data on Hurricane Gonzalo (2014) forecasts. Weather and Forecasting, 32(3): 1143–1159. doi: 10.1175/WAF-D-16-0182.1
[8]	Gangopadhyay A, Schmidt A, Agel L, et al. 2013. Multiscale forecasting in the western North Atlantic: Sensitivity of model forecast skill to glider data assimilation. Continental Shelf Research, 63 Suppl: S159–S176
[9]	Garau B, Ruiz S, Zhang W G, et al. 2011. Thermal lag correction on Slocum CTD glider data. Journal of Atmospheric and Oceanic Technology, 28(9): 1065–1071. doi: 10.1175/JTECH-D-10-05030.1
[10]	Garcia H E, Boyer T, Baranova O K, et al. 2019. World Ocean Atlas 2018: Product Documentation. Silver Spring, Maryland: National Centers for Environmental Information, USA
[11]	Liu Z H, Chen X R, Yu J C, et al. 2019. Kuroshio intrusion into the South China Sea with an anticyclonic eddy: Evidence from underwater glider observation. Journal of Oceanology and Limnology, doi: 10.1007/s00343-019-8290-y
[12]	Liu F, Wang Y H, Wu Z L, et al. 2017. Motion analysis and trials of the deep sea hybrid underwater glider Petrel-II. China Ocean Engineering, 31(1): 55–62. doi: 10.1007/s13344-017-0007-4
[13]	Liu Y G, Weisberg R H, Lembke C. 2015. Glider salinity correction for unpumped CTD sensors across a sharp thermocline. In: Liu Y G, Kerkering H, Weisberg R H, eds. Coastal Ocean Observing Systems. Amsterdam: Elsevier, 305−325
[14]	Liu Z H, Xu J P, Sun C H. 2007. Discussing on detecting and calibration method of Argo conductivity sensor drift errors. Ocean Technology (in Chinese), 26(4): 72–76
[15]	Lueck R G, Picklo J J. 1990. Thermal inertia of conductivity cells: observations with a sea-bird cell. Journal of Atmospheric and Oceanic Technology, 7(5): 756–768. doi: 10.1175/1520-0426(1990)007<0756:TIOCCO>2.0.CO;2
[16]	Miles T, Seroka G, Kohut J, et al. 2015. Glider observations and modeling of sediment transport in Hurricane Sandy. Journal of Geophysical Research: Oceans, 120(3): 1771–1791. doi: 10.1002/2014JC010474
[17]	Morison J, Andersen R, Larson N, et al. 1994. The correction for thermal-lag effects in sea-bird CTD data. Journal of Atmospheric and Oceanic Technology, 11(4): 1151–1164. doi: 10.1175/1520-0426(1994)011<1151:TCFTLE>2.0.CO;2
[18]	Oka E, Ando K. 2004. Stability of temperature and conductivity sensors of Argo profiling floats. Journal of Oceanography, 60(2): 253–258. doi: 10.1023/B:JOCE.0000038331.10108.79
[19]	Owens W B, Wong A P S. 2009. An improved calibration method for the drift of the conductivity sensor on autonomous CTD profiling floats by θ-S climatology. Deep Sea Research Part I: Oceanographic Research Papers, 56(3): 450–457. doi: 10.1016/j.dsr.2008.09.008
[20]	Pan C D, Yaremchuk M, Nechaev D, et al. 2011. Variational assimilation of glider data in Monterey Bay. Journal of Marine Research, 69(2–3): 331–346
[21]	Pan C D, Zheng L Y, Weisberg R H, et al. 2014. Comparisons of different ensemble schemes for glider data assimilation on West Florida shelf. Ocean Modelling, 81: 13–24. doi: 10.1016/j.ocemod.2014.06.005
[22]	Racape V, Dobler D, Coatanoan C. 2018. Tests RTQC. In: Proceedings of the 19th Meeting of the Argo Data Management Team. San Diego: The 19th Meeting of the Argo Data Managemen Team
[23]	Rudnick D L, Davis R E, Eriksen C C, et al. 2004. Underwater gliders for ocean research. Marine Technology Society Journal, 38(2): 73–84. doi: 10.4031/002533204787522703
[24]	Ruiz S, Pascual A, Garau B, et al. 2009. Mesoscale dynamics of the Balearic Front, integrating glider, ship and satellite data. Journal of Marine Systems, 78 (Suppl): S3–S16
[25]	Shu Y Q, Wang Q, Zu T T. 2018. Progress on shelf and slope circulation in the northern South China Sea. Science China Earth Sciences, 61(5): 560–571. doi: 10.1007/s11430-017-9152-y
[26]	Shu Y Q, Xiu P, Xue H J, et al. 2016. Glider-observed anticyclonic eddy in northern South China Sea. Aquatic Ecosystem Health & Management, 19(3): 233–241
[27]	Shulman I, Rowley C, Anderson S, et al. 2009. Impact of glider data assimilation on the Monterey Bay model. Deep Sea Research Part II: Topical Studies in Oceanography, 56(3–5): 188–198. doi: 10.1016/j.dsr2.2008.08.003
[28]	Stommel H. 1989. The SLOCUM mission. Oceanography, 19(1): 22–25
[29]	Tintoré J, Vizoso G, Casas B, et al. 2013. SOCIB: The Balearic Islands Coastal Ocean Observing and Forecasting System Responding to Science, Technology and Society Needs. Marine Technology Society Journal, 47(1): 101–117. doi: 10.4031/MTSJ.47.1.10
[30]	Troupin C, Beltran J P, Heslop E, et al. 2015. A toolbox for glider data processing and management. Methods in Oceanography, 13–14: 13–23. doi: 10.1016/j.mio.2016.01.001
[31]	UNESCO. 1981. Tenth report of the joint panel on oceanographic tables and standards. UNESCO technical papers in Marine Sciences, No. 36
[32]	U S. Integrated Ocean Observing System. 2016. Manual for quality control of temperature and salinity data observations from gliders Version 1.0. https://cdn.ioos.noaa.gov/media/2017/12/Manual-for-QC-of-Glider-Data_05_09_16.pdf [2017-12-1/2018-8-16]
[33]	Wong A P S, Johnson G C, Owens W B. 2003. Delayed-mode calibration of autonomous CTD profiling float salinity data by θ-S climatology. Journal of Atmospheric and Oceanic Technology, 20(2): 308–318. doi: 10.1175/1520-0426(2003)020<0308:DMCOAC>2.0.CO;2
[34]	Wong A, Keeley R, Carval T, et al. 2019. Argo quality control manual for CTD and trajectory data. http://dx.doi.org/10.13155/33951 [2018-1-16/2018-8-14]
[35]	Yu J C, Zhang A Q, Jin W M, et al. 2011. Development and experiments of the sea-wing underwater glider. China Ocean Engineering, 25(4): 721–736. doi: 10.1007/s13344-011-0058-x

Relative Articles

Relative Articles

Supplements(0)

Cited By

Cited by

Periodical cited type(3)

1.	S. Vasavi, M. Sai Pravallika, B. Naga Varun, et al. Residual network-based ocean wave modelling from satellite images using ensemble Kalman filter. The Visual Computer, 2023. doi:10.1007/s00371-023-03169-2
2.	S. Vasavi, Ch. Divya, A. Shashikant Sarma. Detection of solitary ocean internal waves from SAR images by using U-Net and KDV solver technique. Global Transitions Proceedings, 2021, 2(2): 145. doi:10.1016/j.gltp.2021.08.063
3.	Tongchen Wang, T. C. Yang, Wen Xu. Detection and Parameter Estimation of Solitary Internal Waves Using Distributed Acoustic Sensors. IEEE Access, 2020, 8: 124223. doi:10.1109/ACCESS.2020.3006062