Impact of Earth's curvature on coastal sea level altimetry with ground-based GNSS Reflectometry

Author(s):  
Vitor Hugo Almeida Junior ◽  
Marcelo Tomio Matsuoka ◽  
Felipe Geremia-Nievinski

<p>Global mean sea level is rising at an increasing rate. It is expected to cause more frequent extreme events on coastal sites. The main sea level monitoring systems are conventional tide gauges and satellite altimeters. However, tide gauges are few and satellite altimeters do not work well near the coasts. Ground-based GNSS Reflectometry (GNSS-R) is a promising alternative for coastal sea level measurements. GNSS-R works as a bistatic radar, based on the use of radio waves continuously emitted by GNSS satellites, such as GPS and Galileo, that are reflected on the Earth’s surface. The delay between reflected and direct signals, known as interferometric delay, can be used to retrieve geophysical parameters, such as sea level. One advantage of ground-based GNSS-R is the slant sensing direction, which implies the reflection points can occur at long distances from the receiving antenna. The higher is the receiving antenna and the lower is the satellite elevation angle, the longer will be the distance to the reflection point. The geometrical modeling of interferometric delay, in general, adopts a planar and horizontal model to represent the reflector surface. This assumption may be not valid for far away reflection points due to Earth’s curvature. It must be emphasized that ground-based GNSS-R sensors can be located at high altitudes, such in lighthouses and cliffs, and GNSS satellites are often tracked near grazing incidence and even at negative elevation angles. Eventually, Earth’s curvature would have a significant impact on altimetry retrievals. The osculating spherical model is more adequate to represent the Earth’s surface since its mathematical complexity is in between a plane and an ellipsoid. The present work aims to quantify the effect of Earth’s curvature on ground-based GNSS-R altimetry. Firstly, we modeled the interferometric delay for each plane and sphere and we calculated the differences across the two surface models, for varying satellite elevation and antenna altitude. Then, we developed an altimetry correction in terms of half of the rate of change of the delay correction with respect to the sine of elevation. We simulated observation scenarios with satellite elevation angles from zenith down to the minimum observable elevation on the spherical horizon (negative) and antenna altitudes from 10 m to 500 m. We noted that due to Earth’s curvature, the reflection point is displaced, brought closer in the x-axis and bent downward in the y-axis. The displacement of the reflection point increases the interferometric delay. Near the planar horizon, at zero elevation, the difference increases quickly and so does the altimetry correction. Finally, considering a 1-cm altimetry precision threshold to sea-level measurements, we observed that the altimetry correction for Earth’s curvature is needed at 10°, 20°, and 30° satellite elevation, for an antenna altitude of 60 m, 120 m, and 160 m, respectively.</p>

2021 ◽  
Author(s):  
Thalia Nikolaidou ◽  
Marcelo Santos ◽  
Simon D. P. Williams ◽  
Felipe Geremia-Nievinski

<p>GNSS reflectometry (GNSS-R) ability to remote sense the Earth’s surface is affected by an atmospheric bias, as pointed out by several recent studies. In particular, sea level altimetry retrievals are biased in proportion to the reflector height, while by-products, such as tidal amplitudes, are underestimated. Previously, we developed an atmospheric ray-tracing procedure to solve rigorously the three-point boundary value problem of ground-based GNSS-R observations. We defined the reflection-minus-direct or interferometric delay in terms of vacuum distance and radio length. We clarified the roles of linear and angular refraction in splitting the total delay in two components, along-path and geometric. We introduced for the first time two subcomponents of the atmospheric geometric delay, the geometry shift and geometric excess. Finally, we defined atmospheric altimetry corrections necessary for unbiased altimetry retrievals based on half of the rate of change of the atmospheric delays with respect to sine of elevation angle. Later, for users without access to ray-tracing software, we developed closed-form expressions for the atmospheric delay and altimetry correction. The first expression accounts for the angular component of refraction (bending), leading to a displaced specular reflection point. The second one accounts for the linear component (speed retardation) in a homogeneous atmosphere. The expressions are parametrized in terms of refractivity and elevation bending, which can be obtained from empirical models, such as the GPT2 or Bennet’s, or fine-tuned based on in situ pressure and temperature. We also provide a correction for the satellite elevation angle such that the refraction effect is nullified. We validated these expressions against rigorous ray-tracing results and showed that the discrepancy is caused by assumptions in the derivation of the closed formulas. We found the corrections to be beneficial even for small reflector heights, as approximated half of the atmospheric effect originates above the receiving antenna at low satellite elevation angles.</p>


2014 ◽  
Vol 7 (5) ◽  
pp. 2261-2279 ◽  
Author(s):  
N. Roussel ◽  
F. Frappart ◽  
G. Ramillien ◽  
J. Darrozes ◽  
C. Desjardins ◽  
...  

Abstract. The detection of Global Navigation Satellite System (GNSS) signals that are reflected off the surface, along with the reception of direct GNSS signals, offers a unique opportunity to monitor water level variations over land and ocean. The time delay between the reception of the direct and reflected signals gives access to the altitude of the receiver over the reflecting surface. The field of view of the receiver is highly dependent on both the orbits of the GNSS satellites and the configuration of the study site geometries. A simulator has been developed to determine the location of the reflection points on the surface accurately by modeling the trajectories of GNSS electromagnetic waves that are reflected by the surface of the Earth. Only the geometric problem was considered using a specular reflection assumption. The orbit of the GNSS constellation satellites (mainly GPS, GLONASS and Galileo), and the position of a fixed receiver, are used as inputs. Four different simulation modes are proposed, depending on the choice of the Earth surface model (local plane, osculating sphere or ellipsoid) and the consideration of topography likely to cause masking effects. Angular refraction effects derived from adaptive mapping functions are also taken into account. This simulator was developed to determine where the GNSS-R receivers should be located to monitor a given study area efficiently. In this study, two test sites were considered: the first one at the top of the 65 m Cordouan lighthouse in the Gironde estuary, France, and the second one on the shore of Lake Geneva (50 m above the reflecting surface), at the border between France and Switzerland. This site is hidden by mountains in the south (orthometric altitude up to 2000 m), and overlooking the lake in the north (orthometric altitude of 370 m). For this second test site configuration, reflections occur until 560 m from the receiver. The planimetric (arc length) differences (or altimetric difference as WGS84 ellipsoid height) between the positions of the specular reflection points obtained considering the Earth's surface as an osculating sphere or as an ellipsoid were found to be on average 9 cm (or less than 1 mm) for satellite elevation angles greater than 10°, and 13.9 cm (or less than 1 mm) for satellite elevation angles between 5 and 10°. The altimetric and planimetric differences between the plane and sphere approximations are on average below 1.4 cm (or less than 1 mm) for satellite elevation angles greater than 10° and below 6.2 cm (or 2.4 mm) for satellite elevation angles between 5 and 10°. These results are the means of the differences obtained during a 24 h simulation with a complete GPS and GLONASS constellation, and thus depend on how the satellite elevation angle is sampled over the day of simulation. The simulations highlight the importance of the digital elevation model (DEM) integration: average planimetric differences (or altimetric) with and without integrating the DEM (with respect to the ellipsoid approximation) were found to be about 6.3 m (or 1.74 m), with the minimum elevation angle equal to 5°. The correction of the angular refraction due to troposphere on the signal leads to planimetric (or altimetric) differences of an approximately 18 m (or 6 cm) maximum for a 50 m receiver height above the reflecting surface, whereas the maximum is 2.9 m (or 7 mm) for a 5 m receiver height above the reflecting surface. These errors increase deeply with the receiver height above the reflecting surface. By setting it to 300 m, the planimetric errors reach 116 m, and the altimetric errors reach 32 cm for satellite elevation angles lower than 10°. The tests performed with the simulator presented in this paper highlight the importance of the choice of the Earth's representation and also the non-negligible effect of angular refraction due to the troposphere on the specular reflection point positions. Various outputs (time-varying reflection point coordinates, satellite positions and ground paths, wave trajectories, first Fresnel zones, etc.) are provided either as text or KML files for visualization with Google Earth.


2012 ◽  
Vol 50 (8) ◽  
pp. 1099-1106 ◽  
Author(s):  
Yongcun Cheng ◽  
Ole Baltazar Andersen ◽  
Per Knudsen
Keyword(s):  

2021 ◽  
Author(s):  
Thalia Nikolaidou ◽  
Marcelo Santos ◽  
Simon Williams ◽  
Felipe Geremia-Nievinski

Radio waves used in Global Navigation Satellite System Reflectometry (GNSS-R) are subject to atmospheric refraction, even for ground-based tracking stations in applications such as coastal sea-level altimetry. Although atmospheric delays are best investigated via ray-tracing, its modification for reflections is not trivial. We have developed closed-form expressions for atmospheric refraction in ground-based GNSS-R and validated them against raytracing. We provide specific expressions for the linear and angular components of the atmospheric interferometric delay and corresponding altimetry correction, parameterized in terms of refractivity and bending angle. Assessment results showed excellent agreement for the angular component and good for the linear one. About half of the delay was found to originate above the receiving antenna at low satellite elevation angles. We define the interferometric slant factor used to map interferometric zenithal delays to individual satellites. We also provide an equivalent correction for the effective satellite elevation angle such that the refraction effect is nullified. Lastly, we present the limiting conditions for negligible atmospheric altimetry correction (sub-cm), over domain of satellite elevation angle and reflector height. For example, for 5-meter reflector height, observations below 20° elevation angle have more than 1-centimeter atmospheric altimetry error.


2021 ◽  
Author(s):  
Fabio Mangini ◽  
Antonio Bonaduce ◽  
Léon Chafik ◽  
Laurent Bertino

<p>Satellite altimetry measurements, complemented by in-situ records, have made a fundamental contribution to the understanding of global sea level variability for almost 30 years. Due to land contamination, it performs best over the open ocean. However, over the years, there has been a significant effort to improve the altimetry products in coastal regions. Indeed, altimetry observations could be fruitfully used in the coastal zone to complement the existing tide gauge network which, despite its relevance, does not represent the entire coast. Given the important role of coastal altimetry in oceanography, we have recently decided to check the quality of a new coastal altimetry dataset, ALES, along the coast of Norway. The Norwegian coast is well covered by tide gauges and, therefore, particularly suitable to validate a coastal altimetry dataset. Preliminary results show a good agreement between in-situ and remote sensing sea-level signals in terms of linear trend, seasonal cycle and inter-annual variability. For example, the linear correlation coefficient between the inter-annual sea level variability from altimetry and tide gauges exceeds 0.8. Likewise, the root mean square difference between the two is less than 2 cm at most tide gauge locations. A comparison with Breili et al. (2017) shows that ALES performs better than the standard satellite altimetry products at estimating sea level trends along the coast of Norway. Notably, in the Lofoten region, the difference between the sea level trends computed using ALES and the tide gauges range between 0.0 to 0.7 mm/year, compared to circa 1 to 3 mm/year found by Breili et al. (2017). These preliminary results go in the direction of obtaining an accurate characterization of coastal sea-level at the high latitudes based on coastal altimetry records, which can represent a valuable source of information to reconstruct coastal sea-level signals in areas where in-situ data are missing or inaccurate.</p>


Measurements of currents, wind, and coastal sea level from off Oregon, northwest Africa and Peru are used to examine characteristics of the depth-integrated momentum balance at mid-shelf locations. Attention is focused on determining the nature of the balance, as a function of frequency, of time-dependent terms in the alongshore momentum equation. Decomposition of the estimated terms into empirical orthogonal functions, and regression of terms on the wind stress to obtain the wind-forced component, are methods used in an attempt to assess objectively the type of balance present. It is found, for Oregon, that there is a relatively large amount of variance in the depth-integrated cross-shelf velocity which is not balanced by other estimated terms. In addition, a substantial component of the flow is wind-forced, with bottom friction insignificant for periods less than 11 days. For northwest Africa, the motion is strongly wind-driven, with bottom friction playing an important role for periods greater than 6 days and with a quasi-steady response evident for periods longer than 10 days. For Peru, the motion is dominated by an inviscid, unforced balance which, for the 5- to 11-day frequency band, is primarily between the alongshore pressure gradient and the rate of change with time of the alongshore velocity.


2021 ◽  
Author(s):  
Stefano Vignudelli ◽  
Francesco De Biasio

For the last century, tide gauges have been used to measure sea level change along the world’s coastline. However, tide gauges are heterogeneously distributed and sparse in coverage. The measured sea level changes are also affected by solid-Earth geophysics. Since 1992, satellite radar altimetry technique made possible to measure heights at sea independent of land changes. Recently various efforts started to improve the sea level record reprocessing past altimetry missions to create an almost 30 year-long combined record for sea level research studies. Moreover, coastal altimetry, i.e. the extension of altimetry into the oceanic coastal zone and its exploitation for looking at climate-scale variations of sea level, has had a steady progress in recent years and has become a recognized mission target for present and future satellite altimeters. Global sea level rise is today well acknowledged. On the opposite, the regional and local patterns are much more complicated to observe and explain. Sea level falls in some places and rises in others, as a consequence of natural cycles and anthropogenic causes. As relative sea level height continues to increase, many coastal cities can have the local elevation closer to the flooding line. It is evident that at land-sea interface a single technique is not enough to de-couple land and sea level changes. Satellite radar altimetry and tide gauges would coincide at coast if land had no vertical motion. By noting this fact, the difference of the two independent measurements is a proxy of land motion. In this chapter, we review recent advances in open ocean and coastal altimetry to measure sea level changes close to the coasts over the satellite radar altimetry era. The various methods to measure sea level trends are discussed, with focus on a more robust inverse method that has been tested in the Northern Adriatic Sea, where Global Positioning System (GPS) data are available to conduct a realistic assessment of uncertainties. The results show that the classical approach of estimating Vertical Land Motion (VLM) provides values that are almost half of those provided by the new Linear Inverse Problem With Constraints (LIPWC) method, in a new formulation which makes use of a change of variable (LIPWCCOV). Moreover, the accuracy of the new VLM estimates is lower when compared to the VLM estimated from GPS measurements. The experimental Sea Level Climate Change Initiative (SLCCI) data set (high resolution along track) coastal sea level product (developed within Climate Change Initiative (CCI project) that has been also assessed in the Gulf of Trieste show that the trends calculated with the gridded and along track datasets exhibit some differences, probably due to the different methodologies used in the generation of the products.


Proceedings ◽  
2019 ◽  
Vol 19 (1) ◽  
pp. 11 ◽  
Author(s):  
Puente ◽  
Valdés

GNSS reflectometry (GNSS-R) a technique for the study of variations in the height of sea level and inland waters, and for the study of soil moisture, based on the comparison of the direct and reflected noise signal. The main advantage of this method is that allows the connection between sea level measurements and the global reference frame. The purpose of this contribution is to present the GNSS-R analysis service at the Geodesy department of the National Geographic Institute of Spain and to compare the sea level time series determined by means of GNSS-R with tide gauge measurements. Two different GNSS-R methods using multi-constellation and multi-frequency data are compared: Lomb-Scargle Periodogram and Inverse Modelling. This analysis is performed for 3 GNSS antennas collocated to tide gauges along the Spanish coast. Eventually, advantages and disadvantages of this method are discussed.


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