Detection of Storm Surge-Induced Non-Tidal Ocean Loading Deformation in Hong Kong Using Sub-Daily GNSS Observations

Abstract

Storm surges occurring over short periods can cause abrupt changes in ocean mass near the coast, leading to transient crustal subsidence known as Non-Tidal Ocean Loading (NTOL). Existing NTOL products provided by various institutions are typically derived from oceanic gravity or fluid dynamic models combined with Earth’s elastic response theory. However, these model-based products lack validation against in-situ observations, raising concerns about their reliability under extreme conditions. In contrast, geodetic Global Navigation Satellite Systems (GNSS) observations offer high accuracy, high spatiotemporal resolution, and near real-time availability. In this study, we analyze sub-daily GNSS vertical displacements from 12 stations in Hong Kong during a storm surge in October 2021 and compare them with NTOL predictions from three global models (GFZ, IMLS, and GGFC) to assess their consistency in a complex coastal environment. Results show that the IMLS and GGFC NTOL products are more reliable than the GFZ product for detecting sub-daily loading deformations in a small region. The GFZ product suffers from spurious NTOL displacement signals (max ≈ 15 mm) during the peak storm surge period. Among the correlation coefficients between 3-h GNSS vertical displacements and the three NTOL products, the IMLS product achieves the highest correlation (max = 0.67), followed by the GGFC product, while the GFZ product exhibits the lowest correlation. Extending the GNSS solution time span (from 3-h to 6-h or 9-h) improves its correlation with NTOL. However, since storm surge effects typically last only tens of minutes to a few hours, a 6-h or 9-h GNSS solution may not capture the full details of the storm surge-induced deformation. Our work demonstrates that sub-daily GNSS observations can detect the transient NTOL-induced subsidence caused by storm surges, thereby validating the accuracy and applicability of these NTOL models and filling the gap left by the lack of observational support in previous model-based studies.

Keywords

GNSS / time series analysis / storm surge / surface load deformation / Hong Kong / marine geology

References

[1] Boy J P, Longuevergne L, Boudin F, et al.. Modelling Atmospheric and Induced Non-Tidal Oceanic Loading Contributions to Surface Gravity and Tilt Measurements. Journal of Geodynamics, 2009, 48(3/4/5): 182-188.

[2] Boy J P, Lyard F. High-Frequency Non-Tidal Ocean Loading Effects on Surface Gravity Measurements. Geophysical Journal International, 2008, 175(1): 35-45.

[3] Dobslaw H, Bergmann-Wolf I, Dill R, et al.. A New High-Resolution Model of Non-Tidal Atmosphere and Ocean Mass Variability for De-Aliasing of Satellite Gravity Observations: AOD1B RL06. Geophysical Journal International, 2017, 211(1): 263-269.

[4] Dong D, Wang M, Chen W, et al.. Mitigation of Multipath Effect in GNSS Short Baseline Positioning by the Multipath Hemispherical Map. Journal of Geodesy, 2016, 90(3): 255-262.

[5] Fenoglio-Marc L, Scharroo R, Annunziato A, et al.. Cyclone Xaver Seen by Geodetic Observations. Geophysical Research Letters, 2015, 42(22): 9925-9932.

[6] Flather R A. Existing Operational Oceanography. Coastal Engineering, 2000, 41(1/2/3): 13-40.

[7] Fratepietro F, Baker T F, Williams S D P, et al.. Ocean Loading Deformations Caused by Storm Surges on the Northwest European Shelf. Geophysical Research Letters, 2006, 33(6): 2005GL025475.

[8] Geng J H, Williams S D P, Teferle F N, et al.. Detecting Storm Surge Loading Deformations around the Southern North Sea Using Subdaily GPS: Storm Surge Loading. Geophysical Journal International, 2012, 191(2): 569-578.

[9] Geng J H, Xin S M, Williams S D P, et al.. Comparing Non-Tidal Ocean Loading around the Southern North Sea with Subdaily GPS/GLONASS Data. Journal of Geophysical Research: Solid Earth, 2021, 126(3): e2020JB020685.

[10] Haigh I D, MacPherson L R, Mason M S, et al.. Estimating Present Day Extreme Water Level Exceedance Probabilities around the Coastline of Australia: Tropical Cyclone-Induced Storm Surges. Climate Dynamics, 2014, 42(1): 139-157.

[11] Haigh I D, Wijeratne E M S, MacPherson L R, et al.. Estimating Present Day Extreme Water Level Exceedance Probabilities around the Coastline of Australia: Tides, Extra-Tropical Storm Surges and Mean Sea Level. Climate Dynamics, 2014, 42(1): 121-138.

[12] Hammond W C, Blewitt G, Kreemer C. GPS Imaging of Vertical Land Motion in California and Nevada: Implications for Sierra Nevada Uplift. Journal of Geophysical Research: Solid Earth, 2016, 121(10): 7681-7703.

[13] Haritonova D. The Impact of the Baltic Sea Non-Tidal Loading on GNSS Station Coordinate Time Series: The Case of Latvia. Baltic Journal of Modern Computing, 2019, 7(4): 541-549.

[14] Heki K, Jin S G. Geodetic Study on Earth Surface Loading with GNSS and GRACE. Satellite Navigation, 2023, 4(1): 24.

[15] Jin S G, Zhang T Y. Terrestrial Water Storage Anomalies Associated with Drought in Southwestern USA from GPS Observations. Surveys in Geophysics, 2016, 37(6): 1139-1156.

[16] Johnson C W, Fu Y N, Bürgmann R. Seasonal Water Storage, Stress Modulation, and California Seismicity. Science, 2017, 356(6343): 1161-1164.

[17] Jungclaus J H, Fischer N, Haak H, et al.. Characteristics of the Ocean Simulations in the Max Planck Institute Ocean Model (MPIOM) the Ocean Component of the MPI-Earth System Model. Journal of Advances in Modeling Earth Systems, 2013, 5(2): 422-446.

[18] Li Z, Lu R, Jiang W P, et al.. A Refined Full-Spectrum Temperature-Induced Subsurface Thermal Expansion Model and Its Contribution to the Vertical Displacement of Global GNSS Reference Stations. Journal of Geodesy, 2024, 98(4): 25.

[19] Lu R, Chen W, Dong D N, et al.. Multipath Mitigation in GNSS Precise Point Positioning Based on Trend-Surface Analysis and Multipath Hemispherical Map. GPS Solutions, 2021, 25(3): 119.

[20] Lu R, Chen W, Li Z, et al.. An Improved Joint Modeling Method for Multipath Mitigation of GPS, BDS-3, and Galileo Overlapping Frequency Signals in Typical Environments. Journal of Geodesy, 2023, 97(10): 95.

[21] Lu R, Chen W, Zhang C L, et al.. Characteristics of the BDS-3 Multipath Effect and Mitigation Methods Using Precise Point Positioning. GPS Solutions, 2022, 26(2): 41.

[22] Lu R, Li Z, Chen Q S, et al.. On the Contributions of Refined Thermal Expansion Model to Nonlinear Variations in Different GNSS Height Time Series Products. GPS Solutions, 2025, 28(2): 80.

[23] Lu R, Zhang M Y, Yuan P, et al.. Enhancing Multi-GNSS Positioning Performances in Harsh Environments via a Refined Joint Troposphere-Multipath Hemispherical Map. GPS Solutions, 2024, 29(1): 1.

[24] Lyard F, Lefevre F, Letellier T, et al.. Modelling the Global Ocean Tides: Modern Insights from FES2004. Ocean Dynamics, 2006, 56(5): 394-415.

[25] Ma M, Tao T, Xie G, et al.. Surface Vertical Deformation in Hong Kong by Combining CORS and Environmental Load Deformation Data. Journal of Geodesy and Geodynamics, 2023, 43(3): 246-249

[26] Malys S, Jensen P A. Geodetic Point Positioning with GPS Carrier Beat Phase Data from the CASA UNO Experiment. Geophysical Research Letters, 1990, 17(5): 651-654.

[27] Mémin A, Watson C, Haigh I D, et al.. Non-Linear Motions of Australian Geodetic Stations Induced by Non-Tidal Ocean Loading and the Passage of Tropical Cyclones. Journal of Geodesy, 2014, 88(10): 927-940.

[28] Ming F, Yang Y X, Zeng A M, et al.. Spatiotemporal Filtering for Regional GPS Network in China Using Independent Component Analysis. Journal of Geodesy, 2017, 91(4): 419-440.

[29] Munekane H, Matsuzaka S. Nontidal Ocean Mass Loading Detected by GPS Observations in the Tropical Pacific Region. Geophysical Research Letters, 2004, 31(8): 2004GL019773.

[30] Nordman M, Mäkinen J, Virtanen H, et al.. Crustal Loading in Vertical GPS Time Series in Fennoscandia. Journal of Geodynamics, 2009, 48(3/4/5): 144-150.

[31] Pintori F, Serpelloni E, Gualandi A. Common-Mode Signals and Vertical Velocities in the Greater Alpine Area from GNSS Data. Solid Earth, 2022, 13(10): 1541-1567.

[32] Ray R D, Ponte R M. Barometric Tides from ECMWF Operational Analyses. Annales Geophysicae, 2003, 21(8): 1897-1910.

[33] Saastamoinen J. Contributions to the Theory of Atmospheric Refraction: Part II. Refraction Corrections in Satellite Geodesy. Bulletin Géodésique, 1973, 107(1): 13-34.

[34] Teunissen P J G. The Least-Squares Ambiguity Decorrelation Adjustment: A Method for Fast GPS Integer Ambiguity Estimation. Journal of Geodesy, 1995, 70(1): 65-82.

[35] Twardzik C, Vergnolle M, Sladen A, et al.. Unravelling the Contribution of Early Postseismic Deformation Using Sub-Daily GNSS Positioning. Scientific Reports, 2019, 9: 1775.

[36] van Dam T M, Wahr J M. Displacements of the Earth’s Surface due to Atmospheric Loading: Effects on Gravity and Baseline Measurements. Journal of Geophysical Research: Solid Earth, 1987, 92(B2): 1281-1286.

[37] van Dam T, Francis O, Wahr J, et al.. Using GPS and Absolute Gravity Observations to Separate the Effects of Present-Day and Pleistocene Ice-Mass Changes in South East Greenland. Earth and Planetary Science Letters, 2017, 459: 127-135.

[38] Voigt C, Sulzbach R, Dobslaw H, et al.. Non-Tidal Ocean Loading Signals of the North and Baltic Sea from Terrestrial Gravimetry, GNSS, and High-Resolution Modeling. Geophysical Research Letters, 2024, 51(13): e2024GL109262.

[39] Wessel P, Smith W H F, Scharroo R, et al.. Generic Mapping Tools: Improved Version Released. Eos, Transactions American Geophysical Union, 2013, 94(45): 409-410.

[40] Williams S D P, Penna N T. Non-Tidal Ocean Loading Effects on Geodetic GPS Heights. Geophysical Research Letters, 2011, 38(9): 2011GL046940.

[41] Yan J, Dong D N, Bürgmann R, et al.. Separation of Sources of Seasonal Uplift in China Using Independent Component Analysis of GNSS Time Series. Journal of Geophysical Research: Solid Earth, 2019, 124(11): 11951-11971.

[42] Zerbini S, Matonti F, Raicich F, et al.. Observing and Assessing Nontidal Ocean Loading Using Ocean, Continuous GPS and Gravity Data in the Adriatic Area. Geophysical Research Letters, 2004, 31(23): 2004GL021185.

[43] Zumberge J F, Heflin M B, Jefferson D C, et al.. Precise Point Positioning for the Efficient and Robust Analysis of GPS Data from Large Networks. Journal of Geophysical Research: Solid Earth, 1997, 102(B3): 5005-5017.

RIGHTS & PERMISSIONS

China University of Geosciences (Wuhan) and Springer-Verlag GmbH Germany, Part of Springer Nature