The impact on tsunami detection from space using GNSS-reflectometry when combining GPS with GLONASS and Galileo
Introduction
The Sumatra earthquake in 2004 and the following tsunami took more than 225.000 lives. By 2008, a tsunami early warning system had been installed in Indonesia by the German-Indonesian Tsunami Early Warning System (GITEWS) project (Rudloff et al., 2009). It consists of a network of sensors like seismometers, GPS sensors for surface displacement measurements, ocean bottom pressure sensors, buoys, and tide gauges that are transmitting their data in near-realtime to the warning center at Jakarta via satellite communication. There the incoming sensor signals are matched with tsunami models calculated in advance for various epicenter locations and magnitudes to predict the tsunami wave propagation in order to retrieve an accurate situation awareness map essential for early warning mitigation. Even though the seismic and GPS sensor networks localize the epicenter very quickly, they are insensitive for tsunami waves. The justification whether a tsunami has been triggered or not is essential for the certainty of the tsunami warning. Buoys, pressure sensors and tide gauges are monitoring the sea surface to notify the warning center in case they are sensing a tsunami wave. However, the number of sea surface sensors is limited, and depending on the epicenter location it may take several tens of minutes until the waves reach the nearest sensor. In order to increase the time available for tsunami warning, the tsunami wave must be detected as soon as possible, but raising the number of sea surface sensors is very expensive.
To detect a tsunami wave quickly, the sea surface must be monitored with high spatial and temporal coverage. For this kind of observations, satellite systems are predestined. Satellite radar altimeters (RA) have already demonstrated that they can observe tsunami waves from space (Ablain et al., 2006). But they offer high altimetric accuracy only along track and do not suffice to guarantee the required spatial and temporal coverage. Furthermore, their data is not transferred immediately as required for tsunami early warning. According to Martín-Neira (1993) GNSS-R is an appropriate method for sea surface height measurements and therefore tsunami detection from space, especially when using a LEO constellation (Martín-Neira et al., 2005, Soulat et al., 2005).
In a simulation study for GNSS-R tsunami detection with Walker (Walker, 1984) constellations, Stosius et al. (2010) analyzed the detection performance of such a system for various historical tsunamis in the Indian Ocean. The authors have varied different parameters like orbit altitude, orbit inclination, number of satellites and orbit planes as well as the altimetric sensitivity of the system and they compared two different GNSS-R altimetric approaches. Their study has shown that a 48/8 Walker constellation (48 satellites distributed on 8 orbit planes, refer to next section for explanation of this terminology) is able to detect strong and medium tsunamis in the Indian Ocean within 15–25 min assuming GPS, GLONASS and Galileo signals being available. In their study, effects like GNSS clock errors, ionospheric and tropospheric delays, scattering, antenna orientation or multipath are neglected because their influences on the technical feasibility and altimetric accuracy are very complex and beyond the scope of their simulations. Within this contribution the same basic assumptions are made but the impact of GLONASS and Galileo on the detection performance is analyzed to investigate if GPS as single signal source is sufficient. First, GPS is considered as the only signal source and the detection performances of five different constellations are compared. Second, GLONASS and Galileo signals are added to investigate their impact on the detection performance. Additionally, principal geometrical relations influencing the detection probability are discussed.
Section snippets
GNSS-R as tsunami detection system
The feasibility of GNSS-R (Fig. 1) has been demonstrated in ground based, airplane and balloon experiments (Garrison and Katzberg, 1997, Treuhaft et al., 2001, Cardellach et al., 2003, Helm, 2008). Sea level heights with accuracies at cm level were determined using dedicated delay mapping GNSS receivers (Lowe et al., 2002). The observation of signal reflections from space was first described by Pavelyev et al. (1996). Later, signatures of coherent GPS reflections at low elevation angles were
General geometric considerations
Depending on antenna configuration, the LEO satellites can observe areas on ground within their footprints. In GNSS-R direct and reflected GNSS signals are measured. In a PARIS-like antenna configuration only those reflections can be considered for which also the direct signals can be received and these are limited by the local horizon of the uplooking antenna. According to the calculations of Martín-Neira (1993) the distance s between the reflection point and the nadir point of the satellite
Tsunami detection simulation
The tsunami detection simulation used here is described in more detail in Stosius et al. (2010). The Sumatra tsunami is modeled using the TUNAMI-N2 wave propagation model (Imamura et al., 1997). It implements nonlinear shallow water equations and computes the sea surface height anomalies for the area from 70° to 110° longitude and −15° to 25° latitude with 5 arcmin spacing and 1 min temporal resolution over a period of 3 h after the earthquake. Initial condition is vertical sea floor displacement
Detection performance analyzes
In our simulations we assume that a LEO GNSS-R constellation had been operational on 26 December 2004 when the Sumatra tsunami occurred. On this day GPS was working regularly but GLONASS was not fully established; only 14 GLONASS satellites were in orbit. Additionally, the Galileo constellation is assumed to be operational as intended. The detection performance for five different GNSS-R constellation scenarios (Table 3) at 900 km altitude and 60° inclination angle is calculated. Each of the
Summary
GNSS-R is a promising technique for global tsunami detection from space. A detection performance analysis for the Sumatra event of 26 December 2004 has been carried out assuming GPS, GLONASS and Galileo as signal sources and various LEO GNSS-R Walker constellations as detection system. Considerations are made that discuss the effects that footprint distribution, GNSS visibility and tsunami expansion would have on the detection probability in general. The reflection points in this simulation are
Acknowledgement
This is publication no. 125 of the GITEWS project (German-Indonesian Tsunami Early Warning System). The GITEWS project is carried out through a large group of scientists and engineers from GFZ and its partners from German Aerospace Center (DLR), Alfred-Wegener-Institute for Polar and Marine Research (AWI), GKSS Research Centre, Leibniz-Institute for Marine Sciences (IFM-GEOMAR), United Nations University (UNU), Federal Institute for Geosciences and Natural Resources (BGR), German Agency for
References (35)
- et al.
A new technique to sense non-gaussian features of the sea surface from L-Band bi-static GNSS reflections
Remote Sens. Environ.
(2008) - et al.
Mediterranean balloon experiment: Ocean wind speed sensing from the stratosphere, using GPS reflections
Remote Sens. Environ.
(2003) - et al.
The international GPS service: celebrating the 10th anniversary and looking to the next decade
Adv. Space Res.
(2005) - et al.
Bistatic radar as a tool for Earth investigation using small satellites
Acta Astronaut.
(1996) - et al.
High resolution altimetry reveals new characteristics of the December 2004 Indian Ocean tsunami
Geophys. Res. Lett.
(2006) - et al.
Bistatic scattering of GPS signals off Arctic sea ice
IEEE T. Geosci. Remote Sens.
(2009) - et al.
Observation and simulation of direct and reflected GPS signals in radio occultation experiments
Geophys. Res. Lett.
(2001) - et al.
GPS radio occultations with CHAMP: a radio holographic analysis of GPS signal propagation in the troposphere and surface reflections
J. Geophys. Res.
(2002) - Cardellach, E., Ao, C.O., de la Torre Juárez, M., et al. Carrier phase delay altimetry with GPS-reflection/occultation...
- Cardellach, E., Fabra, F., Nogués-Correig, O., et al. From Greenland to Antarctica: CSIC/IEEC results on sea-ice,...
Wind speed measurement using forward scattered GPS signals
IEEE T. Geosci. Remote Sens.
CHAMP and SAC-C atmospheric occultation results and intercomparisons
J. Geophys. Res.
Enhanced GPS inversion technique applied to the 2004 Sumatra earthquake and tsunami
Geophys. Res. Lett.
Cited by (20)
Evaluation of SNR-based GNSS-reflectometry altimetric precision by a height displacement tool
2022, Advances in Space ResearchCitation Excerpt :Multipath has an effect of reducing accuracy as a source of error in positioning studies with GNSS (Chen, 2018; Wang and El-Mowafy, 2021). However, recently, an enhanced technique is called GNSS Reflectometry is widely used to retrieve information about the physical characteristics of the Earth's surface based on terrestrial and satellite based observations (Ferrazzoli et al., 2011; Geremia-Nievinski et al., 2020; Gerlein-Safdi and Ruf, 2019; Germain et al., 2004; Jia and Savi, 2017; Larson et al., 2013; Lee et al., 2019; Li et al., 2021; Löfgren et al., 2011; Martin-Neira, 1993; Shum et al., 2011; Small et al., 2010; Stosius et al., 2011; Wang et al., 2020; Watzak et al., 2019; Yang et al., 2019). The Global Navigation Satellite System (GNSS) reflected signal provide important parameters to sense the Earth’s surface physical components since early 1990s.
Determination of GNSS receiver elevation-dependent clock bias accuracy
2021, Measurement: Journal of the International Measurement ConfederationCitation Excerpt :After precise synchronisation using, for example, a reference station, phase observations might also be used. The altitude of each GNSS system satellite is near to 20,000 km (GPS – 20,200 km, GLONASS – 19,100 km and Galileo – 23, 222 km) [9]. Adopting the speed of light as 3·105 km, the GNSS signal propagation time is around 0.064–0.077 s. Satellite clock bias is determined with 1 ms error level which triggers a 300 km error on the satellite-receiver distance, 1 μs level leads to a 300 m error and so on.
GNSS monitoring natural and anthropogenic phenomena
2021, GPS and GNSS Technology in GeosciencesRadio occultation and ground-based GNSS products for observing, understanding and predicting extreme events: A review
2019, Atmospheric ResearchCitation Excerpt :Transmitted navigation signals are forward scattered off the surface, and dedicated GNSS-R receivers on land, airborne, or spaceborne platforms detect and correlate the reflected signals with direct ones to retrieve geophysical information about the reflecting surface (Zavorotny et al., 2014). Typical detected surface properties include ocean roughness and sea surface height, tsunami detection (Stosius et al., 2010), storm surges (Peng et al., 2019), soil moisture, vegetation, snow depth, sea ice extent, and ocean surface wind speed (Foti et al., 2015). The latter property can be used to improve the tropical cyclones intensity forecast.
Advanced technologies for satellite navigation and geodesy
2019, Advances in Space ResearchCitation Excerpt :Reflectometry means, in this respect, that satellites of the system establish pairwise reflection links in bistatic radar configuration, see Martín-Neira et al. (2011). Earlier impact studies on GNSS reflectometry already indicated an improved detection of sub-mesoscale ocean phenomena such as oceanic eddies or tsunamis (Stosius et al., 2011). Altimetric measurements, based on the reflection links, will particularly benefit from reduced orbit uncertainties of the transmitting and receiving satellites (Semmling et al., 2016).
Tide variation monitoring based improved GNSS-MR by empirical mode decomposition
2019, Advances in Space ResearchCitation Excerpt :The single and double-difference GNSS-R algorithms, which are used for water level retrieval, can reduce the effects of clock errors and of ionospheric and tropospheric errors substantially (Wang et al., 2016). GNSS-R can also be used for monitoring and providing early warning of tsunamis (Stosius et al., 2011; Yu et al., 2016a, b). In the study using GNSS-MR based on SNR observations, Larson et al. (2013a) performed experiments to monitor the tide at two stations and they achieved the RMSE tide level precision of 5–10 cm.