Application of GNSS interferometric reflectometry for detecting storm surges

A single geodetic GNSS station placed at the coast has the capability of a traditional tide gauge for sea-level measurements, with the additional advantage of simultaneously obtaining vertical land motions. The sea-level measurements are obtained using GNSS signals that have reflected off the water, using analysis of the signal-to-noise ratio (SNR) data. For the first time, we apply this technique to detect extreme weather-induced sea-level fluctuations, i.e., storm surges. We first derive 1-year sea-level measurements under normal weather conditions, for a GNSS station located in Hong Kong, and compare them with traditional tide-gauge data to validate its performance. Our results show that the RMS difference between the individual GNSS sea-level measurements and tide-gauge records is about 12.6 cm. Second, we focus on the two recent extreme events, Typhoon Hato of 2017 and Typhoon Mangkhut of 2018, that are ranked the third and second most powerful typhoons hitting Hong Kong since 1954 in terms of maximum sea level. We use GNSS SNR data from two coastal stations to produce sea-level measurements during the two typhoon events. Referenced to predicted astronomical tides, the storm surges caused by the two events are evident in the sea-level time series generated from the SNR data, and the results also agree with tide-gauge records. Our results demonstrate that this technique has the potential to provide a new approach to monitor storm surges that complement existing tide-gauge networks.

[1]  Vasily V. Titov,et al.  Real-Time Tsunami Forecasting: Challenges and Solutions , 2003 .

[2]  H. Fritz,et al.  The 15 August 2007 Peru tsunami runup observations and modeling , 2008 .

[3]  Frédéric Frappart,et al.  Sea level monitoring and sea state estimate using a single geodetic receiver , 2015 .

[4]  Guy Wöppelmann,et al.  The Van de Casteele Test Revisited: An Efficient Approach to Tide Gauge Error Characterization , 2008 .

[5]  I. Haigh,et al.  A century of sea level data and the UK's 2013/14 storm surges: an assessment of extremes and clustering using the Newlyn tide gauge record , 2014 .

[6]  Jon Derek Loftis,et al.  The Storm Surge and Sub-Grid Inundation Modeling in New York City during Hurricane Sandy , 2014 .

[7]  R. Ray,et al.  A 10-Year Comparison of Water Levels Measured with a Geodetic GPS Receiver versus a Conventional Tide Gauge , 2017 .

[8]  P. K. Taylor,et al.  Parameterizing the Sea Surface Roughness , 2005 .

[9]  Stefano Lorito,et al.  Source process of the September 12, 2007, MW 8.4 southern Sumatra earthquake from tsunami tide gauge record inversion , 2008 .

[10]  S. Atzori,et al.  Optimal time alignment of tide‐gauge tsunami waveforms in nonlinear inversions: Application to the 2015 Illapel (Chile) earthquake , 2016 .

[11]  Louise Willemen,et al.  Machine Learning Using Hyperspectral Data Inaccurately Predicts Plant Traits Under Spatial Dependency , 2018, Remote. Sens..

[12]  S. Williams,et al.  Tropospheric delays in ground‐based GNSS multipath reflectometry—Experimental evidence from coastal sites , 2017 .

[13]  Jeffrey T. Freymueller,et al.  The Accidental Tide Gauge: A GPS Reflection Case Study From Kachemak Bay, Alaska , 2013, IEEE Geoscience and Remote Sensing Letters.

[14]  Iris Möller,et al.  Southern North Sea storm surge event of 5 December 2013: Water levels, waves and coastal impacts , 2015 .

[15]  Walter H. F. Smith,et al.  New, improved version of generic mapping tools released , 1998 .

[16]  Jocene Vallack,et al.  Storm Surge , 2015 .

[17]  O. Montenbruck,et al.  Springer Handbook of Global Navigation Satellite Systems , 2017 .

[18]  Nobuhito Mori,et al.  Survey of 2011 Tohoku earthquake tsunami inundation and run‐up , 2011 .

[19]  P. Woodworth,et al.  Sea-Level Science: Understanding Tides, Surges, Tsunamis and Mean Sea-Level Changes , 2014 .

[20]  Robert Weber,et al.  Development of an improved empirical model for slant delays in the troposphere (GPT2w) , 2015, GPS Solutions.

[21]  Hermann M. Fritz,et al.  Hurricane katrina storm surge distribution and field observations on the Mississippi Barrier Islands , 2007 .

[22]  Remko Scharroo,et al.  Satellite altimetry and the intensification of Hurricane Katrina , 2005 .

[23]  Anny Cazenave,et al.  Contemporary sea level changes from satellite altimetry: What have we learned? What are the new challenges? , 2018, Advances in Space Research.

[24]  C. Donlon,et al.  Blending of satellite and tide gauge sea level observations and its assimilation in a storm surge model of the North Sea and Baltic Sea , 2015 .

[25]  H. Fritz,et al.  Repeat Storm Surge Disasters of Typhoon Haiyan and Its 1897 Predecessor in the Philippines , 2016 .

[26]  Hermann M. Fritz,et al.  Hurricane Katrina Storm Surge Reconnaissance , 2008 .

[27]  H. Fritz,et al.  Cyclone Gonu storm surge in Oman , 2010 .

[28]  Nan Chen,et al.  Using Satellite Altimetry to Calibrate the Simulation of Typhoon Seth Storm Surge off Southeast China , 2018, Remote. Sens..

[29]  G. G. Bennett The Calculation of Astronomical Refraction in Marine Navigation , 1982, Journal of Navigation.

[30]  Junjie Wu,et al.  An Optimal 2-D Spectrum Matching Method for SAR Ground Moving Target Imaging , 2018, IEEE Transactions on Geoscience and Remote Sensing.

[31]  Kristine M. Larson,et al.  Software tools for GNSS interferometric reflectometry (GNSS-IR) , 2018, GPS Solutions.

[32]  R. Haas,et al.  Coastal sea level measurements using a single geodetic GPS receiver , 2013 .

[33]  Dake Chen,et al.  Hurricane Sandy storm surges observed by HY‐2A satellite altimetry and tide gauges , 2014 .

[34]  Chuan-Yao Lin,et al.  Field survey of Typhoon Hato (2017) and a comparison with storm surge modeling in Macau , 2018, Natural Hazards and Earth System Sciences.

[35]  R. Haas,et al.  Sea level time series and ocean tide analysis from multipath signals at five GPS sites in different parts of the world , 2014 .