The impact on tsunami detection from space using GNSS-reflectometry when combining GPS with GLONASS and Galileo

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Abstract

The devastating Sumatra tsunami in 2004 demonstrated the need for a tsunami early warning system in the Indian Ocean. Such a system has been installed within the German-Indonesian Tsunami Early Warning System (GITEWS) project. Tsunamis are a global phenomenon and for global observations satellites are predestined. Within the GITEWS project a feasibility study on a future tsunami detection system from space has therefore been carried out. The Global Navigation Satellite System Reflectometry (GNSS-R) is an innovative way of using GNSS signals for remote sensing. It uses ocean reflected GNSS signals for sea surface altimetry. With a dedicated Low Earth Orbit (LEO) constellation of satellites equipped with GNSS-R receivers, densely spaced sea surface height measurements could be established to detect tsunamis. Some general considerations on the geometry between LEO and GNSS are made in this simulation study. It exemplary analyzes the detection performance of a GNSS-R constellation at 900 km altitude and 60° inclination angle when applied to the Sumatra tsunami as it occurred in 2004. GPS is assumed as signal source and the combination with GLONASS and Galileo signals is investigated. It can be demonstrated, that the combination of GPS and Galileo is advantageous for constellations with few satellites while the combination with GLONASS is preferable for constellations with many satellites. If all three GNSS are combined, the best detection performance can be expected for all scenarios considered. In this case an 18 satellite constellation will detect the Sumatra tsunami within 17 min with certainty, while it takes 53 min if only GPS is considered.

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

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