Estimating Surface Current from HIMAWARI-8 SST Data using Particle Image Velocimetry Method (Case Study in The Flores Sea)

Kadek Setiya Wati, Takahiro Osawa, I Wayan Gede Astawa Karang

Abstract

Four High-Frequency radar systems (HF) have been installed in Indonesia to monitor surface currents. In-situ ocean current observations are relatively expensive and limited by spatial and temporal resolution. Satellite remote sensing enables the estimate of surface current data generally from surface tracer data, including sea surface temperature (SST). Various methodologies have been developed to obtain surface currents. With Himawari-8 SST data, this study examines the accuracy of the resulting estimation. The cross-correlation fields of two identical-sized interrogation windows obtained from sequential images are employed in Particle Image Velocimetry (PIV). The HF radar in Labuan Bajo was used to validate surface current velocity estimates. RMSE, bias, and the Willmott index determined the accuracy. According to the estimates of surface currents made on July 29, 2022, the results follow a monsoon characteristic wind pattern in the Flores Sea. HF radar observations better validate the V component current estimation than the U component current estimation. A study of sea surface currents from SST data is lacking in Indonesian seas, and more repetition is required. As a result, This method has the potential can be employed to observe aquatic environments in other Indonesian areas.

Keywords

PIV, HF radar, current velocity, ocean current, remote sensing

Full Text:

PDF

References

1. Röhrs J, Sutherland G, Jeans G, Bedington M, Sperrevik AK, Dagestad KF, et al. Surface currents in operational oceanography: Key applications, mechanisms, and methods. Journal of Operational Oceanography. 2021;

2. Choi JM, Kim W, Hong TTM, Park YG. Derivation and Evaluation of Satellite-Based Surface Current. Front Mar Sci. 2021 Nov 15;8.

3. Ghalenoei E, Hasanlou M. Monitoring of sea surface currents by using sea surface temperature and satellite altimetry data in the Caspian Sea Av photogrammetry View project SAR Polarimetry Information Extraction View project Monitoring of sea surface currents by using sea surface temperature and satellite altimetry data in the Caspian Sea. Earth Observation and Geomatics Engineering [Internet]. 2017;1(1):36–46. Available from: https://www.researchgate.net/publication/321292343

4. Klemas V. Remote sensing of coastal and ocean currents: An overview. Vol. 28, Journal of Coastal Research. 2012. p. 576–86.

5. Taniguchi N, Kida S, Sakuno Y, Mutsuda H, Syamsudin F. Short-term variation of the surface flow pattern south of Lombok Strait observed from the Himawari-8 sea surface temperature. Remote Sens (Basel). 2019 Jun 1;11(12).

6. González-Haro C, Isern-Fontanet J, Tandeo P, Garello R. Ocean Surface Currents Reconstruction: Spectral Characterization of the Transfer Function Between SST and SSH. J Geophys Res Oceans. 2020 Oct 1;125(10).

7. Chen W, Mied RP, Shen CY. Near-surface ocean velocity from infrared images: Global Optimal Solution to an inverse model. J Geophys Res [Internet]. 2008 Oct 7;113(C10):C10003. Available from: http://doi.wiley.com/10.1029/2008JC004747

8. Ciani D, Rio MH, Nardelli BB, Etienne H, Santoleri R. Improving the Altimeter-Derived Surface Currents Using Sea Surface Temperature (SST) Data: A Sensitivity Study to SST Products. Remote Sens (Basel) [Internet]. 2020 May 17;12(10):1601. Available from: https://www.mdpi.com/2072-4292/12/10/1601

9. Kelly KA. An Inverse Model for Near-Surface Velocity from Infrared Images. J Phys Oceanogr [Internet]. 1989 Dec;19(12):1845–64. Available from: http://journals.ametsoc.org/doi/10.1175/1520-0485(1989)019%3C1845:AIMFNS%3E2.0.CO;2

10. Vigan X, Provost C, Bleck R, Courtier P. Sea surface velocities from sea surface temperature images sequence. 1. Method and validation using primitive equation model output. J Geophys Res. 2000;105(AUGUST 15, 2000):19.499-19.514.

11. Cote S, Tatnall ARL. The Use of the Hopfield Neural Network to Measure Sea-Surface Velocities From Satellite Images. IEEE Geoscience and Remote Sensing Letters [Internet]. 2007 Oct;4(4):624–8. Available from: http://ieeexplore.ieee.org/document/4317525/

12. Marghany M, Hashim M, Cracknell AP. Hopfield Neural Network for Sea Surface Current Tracking from Tiungsat-1 Data. In: Computational Science and Its Applications – ICCSA 2008 [Internet]. Berlin, Heidelberg: Springer Berlin Heidelberg; 2008. p. 950–8. Available from: http://link.springer.com/10.1007/978-3-540-69848-7_75

13. Kusnanti EA, Novitasari DCR, Setiawan F, Fanani A, Hafiyusholeh M, Permata Sari GI. Predicting Velocity and Direction of Ocean Surface Currents using Elman Recurrent Neural Network Method. Journal of Information Systems Engineering and Business Intelligence [Internet]. 2022 Apr 26;8(1):21–30. Available from: https://e-journal.unair.ac.id/JISEBI/article/view/30682

14. Kim HY, Park KA, Kim HA, Chung SR, Cheong SH. Retrievals of Sea Surface Current Vectors from Geostationary Satellite Data (Himawari-8/AHI). Asia Pac J Atmos Sci. 2020 May 1;56(2):249–63.

15. Zhu Z, Geng X, Li S, Xie T, Yan XH. Ocean surface current retrieval at Hangzhou Bay from Himawari-8 sequential satellite images. Sci China Earth Sci. 2020 Jul 1;63(7):1026–38.

16. Perkovic D, Lippmann TC, Frasier SJ. Longshore Surface Currents Measured by Doppler Radar and Video PIV Techniques. IEEE Transactions on Geoscience and Remote Sensing [Internet]. 2009 Aug;47(8):2787–800. Available from: http://ieeexplore.ieee.org/document/4967973/

17. Russmeier N, Hahn A, Zielinski O. Ocean surface water currents by large-scale particle image velocimetry technique. In: OCEANS 2017 - Aberdeen. Institute of Electrical and Electronics Engineers Inc.; 2017. p. 1–10.

18. Supriyadi E, Hidayat R, Santikayasa P, Ramdhani A. An Analysis of Surface Ocean Currents from HF Radar Measurements in the Bali Strait and the Flores Sea, Indonesia. Int J Adv Sci Eng Inf Technol. 2021;11(4).

19. Atmadipoera AS, Hasanah P. Characteristics And Variability of the Flores ITF And Its Coherence with the South Java Coastal Current. Jurnal Ilmu dan Teknologi Kelautan Tropis [Internet]. 2018 Jan 2;9(2):537–56. Available from: https://jagb.journal.ipb.ac.id/index.php/jurnalikt/article/view/19289

20. Yang M, Guan L, Beggs H, Morgan N, Kurihara Y, Kachi M. Comparison of Himawari-8 AHI SST with Shipboard Skin SST Measurements in the Australian Region. Remote Sens (Basel) [Internet]. 2020 Apr 13;12(8):1237. Available from: https://www.mdpi.com/2072-4292/12/8/1237

21. Hsu TW, Shin CY, Ou SH, Li YT. Multi-Cross-Correlation Method in Particle Image Velocimetry. Journal of Mechanics [Internet]. 2011 Sep 31;27(3):365–77. Available from: https://academic.oup.com/jom/article/27/3/365-377/5943809

22. Fujita I, Muste M, Kruger A. Large-scale particle image velocimetry for flow analysis in hydraulic engineering applications. Journal of Hydraulic Research [Internet]. 1998 May 13;36(3):397–414. Available from: https://www.tandfonline.com/doi/full/10.1080/00221689809498626

23. Balamurugan R, Jeeva B. Micron size particle image velocimetry by fast Fourier transform. In 2019. p. 020156. Available from: http://aip.scitation.org/doi/abs/10.1063/1.5130366

24. Nogueira, J., Lecuona, A., Ruiz-rivas, Rodriguez PA. Analysis and alternatives in two-dimensional multigrid particle image velocimetry methods: application of a dedicated weighting function and symmetric direct correlation. Measurement Science and Technology. 2002;13:963–74.

25. Thielicke W, Stamhuis EJ. PIVlab – Towards User-friendly, Affordable, and Accurate Digital Particle Image Velocimetry in MATLAB. J Open Res Softw [Internet]. 2014 Oct 16;2. Available from: http://openresearchsoftware.metajnl.com/articles/10.5334/jors.bl/

26. Patel A, Dharpure JK, Snehmani, Ganju A. Estimating surface ice velocity on Chhota Shigri glacier from satellite data using Particle Image Velocimetry (PIV) technique. Geocarto Int. 2019 Mar 21;34(4):335–47 http://doi.org/10.1080/10106049.2017.1404142

27. Menditto A, Patriarca M, Magnusson B. Understanding the meaning of accuracy, trueness and precision. Accreditation and Quality Assurance [Internet]. 2007 Jan 9;12(1):45–7. Available from: http://link.springer.com/10.1007/s00769-006-0191-z

28. Willmott CJ, Robeson SM, Matsuura K. A refined index of model performance. International Journal of Climatology [Internet]. 2012 Nov 15;32(13):2088–94. Available from: https://onlinelibrary.wiley.com/doi/10.1002/joc.2419

29. Putriani PY, Atmadipoera AS, Nugroho D. Interannual variability of Indonesian throughflow in the Flores Sea. IOP Conf Ser Earth Environ Sci [Internet]. 2019 May 1;278(1):012064. Available from: https://iopscience.iop.org/article/10.1088/1755-1315/278/1/012064

30. Havis MI, Yunita NF. Surface Currents in Indonesian Sea Based on Ocean Surface Currents Near – Real-time (OSCAR) Data. In: Marine Technology for Sustainable Development. Surabaya: Institut Teknologi Sepuluh November; 2017. p. 27–31.

DOI: https://doi.org/10.13057/ijap.v13i2.76131

Refbacks

  • There are currently no refbacks.