20/04/2021

A Tsunami Space-Based Early Warning System

Tsunami Prevention

Tsunami detection from Space – a nearly real-time system to detect ocean surface altimetric anomalies with satellites

Nuno Silva*, Nuno Catarino*, Nuno Ávila*

Maria Ana Baptista**
Martin Wronna**

Tsunamis are one of the deadliest natural disasters on Earth. Early-warning systems are essential to prevent and minimize their effects, but the current implemented systems have serious limitations in terms of efficiency and operational costs. Elecnor Deimos has been working for many years in new techniques to improve these limitations, using GNSS-Reflectometry to measure sea surface altimetry. The implementation of this innovative tsunami early detection system has the potential to provide invaluable information to save lives and mitigate extreme economic losses throughout the world.

 

Tsunamis – devastating natural disasters

Tsunamis have been responsible for over 500,000 fatalities throughout the world (227,899 were from the 2004 Indian Ocean earthquake and tsunami). Though these events are somewhat rare, earthquakes (including tsunamis) killed more people than all other types of disaster put together, claiming nearly 750,000 lives between 1994 and 2013. Tsunamis were the deadliest sub-type of earthquake, with an average of 79 deaths for every 1,000 people affected, compared to four deaths per 1,000 for ground movements. This makes tsunamis almost twenty times more deadly than ground movements.

Major tsunamis occur in the Pacific Ocean region only about once per decade. The global distribution of these events is 70% Pacific Ocean, 15% Mediterranean Sea, 9% Caribbean Sea and Atlantic Ocean, and 6% Indian Ocean.

 

The limitations of the existing global warning systems

In the wake of the 2004 tsunami in Indonesia which killed 230 000 people there have been calls for a global tsunami warning system. Such a system is based on a network of sensors such as seismographic sensors, cable observations, tidal gauges, GPS and buoys such as DART which are distributed across the world. Unfortunately, such systems are expensive to install, operate and maintain – each DART buoy costs over US$0.5M to install and US$300k to maintain each year (it consumes 28% of the NOAA’s budget) and it can only detect a tsunami at its location. Indonesia’s system, completed in 2008 (US$ 142M), presented key limitations in the September 2018 tsunami (Palu, Sulawesi) connected with damage to communications systems by the earthquake itself. Such limitation is intrinsically present in ground-based systems and would not be present in a space-based sensor.

The waves of the 2004 Sumatra tsunami arrived at the coast within only 20min after the earthquake. Any tsunami early warning system should detect tsunami waves as soon as possible (within 15min from their generation) and with highest certainty which require more and/or better information.

Even though the spatial distribution of DART sensors has been carefully  elected, the number of sensors is limited due to the high costs for development, deployment and maintenance. Tsunamis are a global phenomenon, but a global ground-based tsunami early warning system is economically very challenging.

 

Tsunamis detection from space using satellite navigation signals

Tsunami detection from space could be a valuable complement to ground based systems. To detect a tsunami wave quickly, the sea surface must be monitored with high spatial and temporal coverage.

Satellite radar altimeters do not provide the required spatial and temporal coverage and their data is not transferred immediately as required for tsunami early warning. GNSS-Reflectometry (R) is an appropriate method for sea surface altimetry and therefore tsunami detection from space, especially when using a low Earth orbit (LEO) constellation. This technique uses GNSS signals that are reflected from water or ice surfaces as measurement signals. The travel time of the reflected signal compared to the direct one is a measure of the height of the reflecting surface. It is a low-cost passive technique which allows usage of micro satellites. When arranging them in a LEO constellation, global and nearly permanent altimetric and scatterometry ocean observations are possible.

In combination with the existing network, such a system would contribute with sea surface height observations over areas of several thousand km2 within minutes and would provide the only source of information in those regions where no local sensors exist. Such information, if conveniently ingested into currently tsunami warning systems, would decisively improve the accuracy of the tsunami alert systems (GAO, 2006). Furthermore, the traditional systems have been conceived for tsunamis caused by seismic activity and fall short when the cause is different: landslides and volcanic activity such as the December 2018 Indonesia tsunami (Sunda Straight, Anak Krakatoa volcano collapse) – the GNSS-R based system applies to tsunamis of all causes.

R Stosius et al in 2010 presented a study on the tsunami detection performance of LEO constellations depending on GNSS-R altimetric sensitivity, constellation definition and tsunami magnitude. The analyses show that very strong tsunamis can be detected within 15min with 18 LEO satellites and weak tsunamis prove to be more challenging. With a 48 satellites constellation and from 20cm altimetric sensitivity, strong and medium tsunamis can be detected within 15 to 25min.

Two GNSS-R altimetry techniques have been assessed: the code altimetry and the carrier phase altimetry approaches. Regarding the first 15min after the earthquake both approaches perform similarly. For orbit altitudes up to 900km the carrier phase altimetry performs better; at higher orbits both approaches perform similarly and in some cases the code altimetry performs better. Ideally a tsunami detection system would combine both approaches.

Several GNSS Reflectometry space mission concepts recently considered within ESA include the acquisition of carrier phase observables. Examples of these are: GEROSISS, G-TERN and PRETTY. Other current and future GNSS-R missions are: UK-DMC, TDS-1, CYGNSS, Spire Batch-1 and Cat-5/A. This remains a new technology in the process of maturation presenting both challenges not to be ignored and key opportunities to seize.

The operational concept of such constellations is of major importance. All constellation satellites might have moderate on-board altimetry capability implying the need of permanent downlink of eventually high volumes of data – this is deemed economically challenging. Ideally, a maximum of on-board processing is performed and only an alert would be generated and sent to ground when a tsunami is generated – this is deemed a challenge in terms of processing. Hence, for real-time alert purposes, a maximum of on-board processing is to be performed aiming at minimising the data send to ground for processing. All collected information would be stored, later transmitted to ground and then made available openly.

This initiative is perfectly aligned with the United Nations Decade of Ocean Science for Sustainable Development (2021-2030), contributing to the needs of society for a safe ocean protecting people from ocean hazards. Indeed, it involves the science community, the policy-makers, the private sector and the civil society working together beyond business as usual and aspire for real change. This is the decade for such a system to be developed and deployed.

 

Deimos GNSS-R technology for tsunami detection

Elecnor Deimos has been a key player in the field of GNSS-R working together with the most relevant worldwide players. Examples of key projects led by the company in this field include SARGO – a system for probing water characteristics through the analysis of GNSS signals reflected from the water surface; E-GEM – state-of-the-art GNSS-R methods for the purpose of Earth monitoring (e.g. altimetry); COREGAL – exploring Galileo E5 reflected signals for biomass retrieval and related and relevant applications as carbon mapping and land management; and most recently participated to FFSCAT mission which carried a GNSS-R on board.

Combining its satellite integration and operation capabilities with its GNSS receiver development expertise, Elecnor Deimos will be joining forces with its partners to define the operational concept and the payload for a GNSS-R altimetry mission for tsunami detection.

The Tsunami Space-Based Early Warning mission will be compatible with small satellite platforms. Currently many constellations of small satellites are being designed and deployed, many of them by costal nations with particular interest in effectively protecting their populations from the deadliest natural disaster. For example, in November 2017 Portugal joined France, Italy, Greece and Turkey as a National Tsunami Warning Provider in Europe covering the north-east Atlantic – the source of a devastating earthquake and tsunami which destroyed Lisbon in 1755 killing over 1/3 of its population. Portugal is now planning an Atlantic constellation with other nations and both the payload and the constellation represent mutual opportunities for each other.

The Sendai Framework for Disaster Risk Reduction 2015-2030 was adopted by UN Member States on 18 March 2015. The Framework aims to achieve the substantial reduction of disaster risk and losses in lives, livelihoods and health and in the economic, physical, social, cultural and environmental assets of persons, businesses, communities and countries over the next 15 years. It outlines seven clear targets and four priorities for action to prevent new and reduce existing disaster risks. The Tsunami Space-Based Early Warning System Payload will directly contribute to all of the seven targets.

Today, tsunami early warning preparedness “has never been so important” said Mr. António Guterres in the celebration of the 10th anniversary of Fukushima. To prevent and manage disasters more effectively, “countries need to plan, invest, give early warnings and provide education on what to do”. The technology put forward aims exactly at this, feeding current systems with near real time, permanent ocean altimetric data over vast oceanic areas.

*DEIMOS Engenharia

**Instituto D.Luiz FCUL

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