Tag Archives: disaster risk reduction

How to Accelerate the Understanding of Disaster Risk

RMS is delighted in playing an integral role at the United Nations’ Global Platform for Disaster Risk Reduction in Cancun next week.  This is the first time that government stakeholders from all 193 member countries have come together on this subject since the Sendai Framework for Disaster Risk Reduction was adopted in March 2015.  Cancun looks forward to welcoming some 5,000 participants.

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EXPOSURE Magazine Snapshots: Water Security – Managing the Next Financial Shock

This is a taster of an article published by RMS in the second edition of EXPOSURE magazine.  Click here and download your full copy now.

18 Apr 2017 Exposure Drought image


EXPOSURE magazine reported on how a pilot project to stress test banks’ exposure to drought could hold the key to future economic resilience, as recognition grows that environmental stress testing is a crucial instrument to ensure a sustainable financial system.

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Closing the Resilience Gap: A Tale of Two Countries, Nepal and Chile

Nepal house smallOn April 25, 2015, a magnitude 7.8 earthquake struck nearly 50 miles (80 km) northwest of Kathmandu, the capital of Nepal.  This resulted in more than 8,600 fatalities, the destruction of around half a million homes, and left 2.8 million people displaced.

Some two years on and rebuilding efforts have barely started, as US$4.1 billion of pledged international aid is reportedly stalled within Nepal’s National Reconstruction Authority.

As of February 2017, 14,000 homes have been rebuilt and some 30,000 homes are in construction – less than a tenth of the total number of homes destroyed.

Contrast this with the situation in Chile. Since a magnitude 9.4 earthquake in 1960, the country has focused on adequate seismic design requirements within its building code, with both government and the public willing to follow the principles of earthquake-resistant building design. And it’s paying off.

After a magnitude 8.8 quake in 2010, structures in areas that experienced strong shaking had less damage than would have been seen if building codes were weaker. Of 370,000 housing units affected by the earthquake, nearly half experienced only minor damage, and just 22 percent were destroyed.  Where commercial buildings were designed with the help of structural engineers, only five were destroyed, according to the U.S. Geological Survey.

This wide inequity in resilience between two countries facing major seismic hazard brings into sharp focus the urgent need for better quantification, mitigation, and post-event protection for all people, regardless of their location.

Bridging the Divide

Communities around the world can become more resilient both before an event strikes, through practices such as construction education and the implementation of building codes, or post-event by providing insurance and other appropriate risk transfer solutions for individuals and governments. By empowering these stakeholders, our industry can play a vital role in helping to ensure a safer world for all.

Social enterprises such as Build Change, who work on the ground in countries like Nepal, Columbia, and Haiti, are helping to bridge some of this ‘resilience gap’ by working with local governments to institute building codes and train their construction sectors in locally attainable and safe building practices. Over the past 10 years, Build Change has trained over 25,000 people in the basics of safe construction, created over 12,000 local jobs, and enabled 245,000 people to live and learn in safer homes and schools within some of the most catastrophe-prone regions of the planet.

Nepal builder smallThis week, during the annual RMS Impact Trek, both our employees and our clients representing major insurance and reinsurance firms are working together on the ground in Nepal with Build Change, exploring solutions to bring greater synergy and resilience capacity-building to the forefront of our market. We are proud to partner with Build Change by also providing grants to jumpstart and enhance its country programs, and allowing the organization to use our products for free in order to better quantify the risk landscape of the countries in which they operate.

All of us within the insurance industry have an opportunity to reshape the future for communities around the globe by allowing them to better measure and understand their risk, so that responsible mitigation efforts can take shape. We can create tools to help ensure that those who are struck by catastrophe can recover quickly and completely.

At RMS, we remain focused on contributing to this mission by strengthening resilience from the ground up, and continuing our work alongside impactful organizations like Build Change.

Friday 13th and the Long-Term Cost of False Alarms

If the prospect of flooding along the East Coast of England earlier this month was hard to forecast, the newspaper headlines the next day were predictable enough:

Floods? What floods? Families’ fury at evacuation order over storm surge … that never happened (Daily Mail)

East coast residents have derided the severe storm warnings as a ‘load of rubbish’ (The Guardian)

Villagers shrug off storm danger (The Times)

The police had attempted an evacuation of some communities and the army was on standby. This was because of warnings of a ‘catastrophic’ North Sea storm surge on January 13 for which the UK Environment Agency applied the highest level flood warnings along parts of the East Coast: ‘severe’ which represents a danger to life. And yet the flooding did not materialize.

Environment Agency flood warnings: January 13 2017

Water levels were 1.2m lower along the Lincolnshire coast than those experienced in the last big storm surge flood in December 2013, and 0.9m lower around the Norfolk towns of Great Yarmouth and Lowestoft. Predicting the future in such complex situations, even very near-term, always has the potential to make fools of the experts. But there’s a pressure on public agencies, knowing the political fallout of missing a catastrophe, to adopt the precautionary principle and take action. Imagine the set of headlines, and ministerial responses, if there had been no warnings followed by loss of life.

Interestingly, most of those who had been told to evacuate as this storm approached chose to stay in their homes. One police force in Essex, knocked on 2,000 doors yet only 140 of those people registered at an evacuation centre. Why did the others ignore the warnings and stay put? Media reports suggest that many felt this was another false alarm.

The precautionary principal might seem prudent, but a false alarm forecast can encourage people to ignore future warnings. Recent years offer numerous examples of the consequences.

The Lessons of History

Following a 2006 Mw8.3 earthquake offshore from the Kurile Islands, tsunami evacuation warnings were issued all along the Pacific coast of northern Japan, where the tsunami that did arrive was harmless. For many people that experience weakened the imperative to evacuate after feeling the three-minute shaking of the March 2011 Mw9 earthquake, following which 20,000 people were drowned by the tsunami. Based on the fear of what happened in 2004 and 2011, today tsunami warnings are being ‘over-issued’ in many countries around the Pacific and Indian Oceans.

For the inhabitants of New Orleans, the evacuation order issued in advance of Hurricane Ivan in December 2004 (when one third of the city’s population moved out, while the storm veered away), left many sceptical about the mandatory evacuation issued in advance of Hurricane Katrina in August 2005 (after which around 1500 drowned).

Agencies whose job it is to forecast disaster know only too well what happens if they don’t issue a warning as any risk looms. However, the long-term consequences from false alarms are perhaps not made explicit enough. While risk models to calculate the consequence are not yet available, a simple hypothetical calculation illustrates the basic principles of how such a model might work:

  • the chance of a dangerous storm surge in the next 20 years is 10 percent, for a given community;
  • if this happens, then let’s say 5,000 people would be at grave risk;
  • because of a recent ‘false’ alarm, one percent of those residents will ignore evacuation orders;
  • thus the potential loss of life attributed to the false alarm is five people.

Now repeat with real data.

Forecasting agencies need a false alarm forecast risk model to be able to help balance their decisions about when to issue severe warnings. There is an understandable instinct to be over cautious in the short-term, but when measured in terms of future lives lost, disaster warnings need to be carefully rationed. And that rationing requires political support, as well as public education.

[Note: RMS models storm surge in the U.K. where the risk is highest along England’s East Coast – the area affected by flood warnings on January 13. Surge risk is complex, and the RMS Europe Windstorm Model™ calculates surge losses caused by extra-tropical cyclones considering factors such as tidal state, coastal defenses, and saltwater contamination.]

Earthquake Hazard: What Has New Zealand’s Kaikoura Earthquake Taught Us So Far?

The northeastern end of the South Island is a tectonically complex region with the plate motion primarily accommodated through a series of crustal faults. On November 14, as the Kaikoura earthquake shaking began, multiple faults ruptured at the same time culminating in a Mw 7.8 event (as reported by GNS Science).

The last two weeks have been busy for earthquake modelers. The paradox of our trade is that while we exist to help avoid the damage this natural phenomenon causes, the only way we can fully understand this hazard is to see it in action so that we can refine our understanding and check that our science provides the best view of risk. Since November 14 we have been looking at what Kaikoura tells us about our latest, high-definition New Zealand Earthquake model, which was designed to handle such complex events.

Multiple-Segment Ruptures

With the Kaikoura earthquake’s epicenter at the southern end of the faults identified, the rupture process moved from south to north along this series of interlinked faults (see graphic below). Multi-fault rupture is not unique to this event as the same process occurred during the 2010 Mw 7.2 Darfield Earthquake. Such ruptures are important to consider in risk modeling as they produce events of larger magnitude, and therefore affect a larger area, than individual faults would on their own.

Map showing the faults identified by GNS Sciences as experiencing surface fault rupture in the Kaikoura Earthquake.
Source: http://info.geonet.org.nz/display/quake/2016/11/16/Ruptured +land%3A+observations+from+the+air

In keeping with the latest scientific thinking, the New Zealand Earthquake HD Model provides an expanded suite of events that represent complex ruptures along multiple faults. For now, these are included only for areas of high slip fault segments in regions with exposure concentrations, but their addition increases the robustness of the tail of the Exceedance Probability curve, meaning clients get a better view of the risk of the most damaging, but lower probability events.

Landsliding and Liquefaction

While most property damage has been caused directly by shaking, infrastructure has been heavily impacted by landsliding and, to a lesser extent, liquefaction. Landslides and slumps have occurred across the region, most notably over Highway 1, an arterial route. The infrastructure impacts of the Kaikoura earthquake are a likely dress rehearsal for the expected event on the Alpine Fault. This major fault runs 600 km along the western coast of the South Island and is expected to produce an Mw 8+ event with a probability of 30% in the next 50 years, according to GNS Science.

As many as 80 – 100,000 landslides have been reported in the upper South Island, with some creating temporary dams over rivers and in some cases temporary lakes (see below). These dams can fail catastrophically, sending a sudden increase of water flow down the river.



Examples of rivers blocked by landslides photographed by GNS Science researchers.

Source: http://info.geonet.org.nz/display/quake/2016/11/18/ Landslides+and+Landslide+dams+caused +by+the+Kaikoura+Earthquake









Liquefaction occurred in discrete areas across the region impacted by the Kaikoura earthquake. The Port of Wellington experienced both lateral and vertical deformation likely due to liquefaction processes in reclaimed land. There have been reports of liquefaction near the upper South Island towns (Blenheim, Seddon, Ward), but liquefaction will not be a driver of loss in the Kaikoura event to the extent it was in the Christchurch earthquake sequence.

RMS’ New Zealand Earthquake HD Model includes a new liquefaction component that was derived using the immense amount of new borehole data collected after the Canterbury Earthquake Sequence in 2010-2011. This new methodology considers additional parameters, such as depth to the groundwater table and soil-strength characteristics, that lead to better estimates of lateral and vertical displacement. The HD model is the first probabilistic model with a landslide susceptibility component for New Zealand.


The Kaikoura Earthquake generated tsunami waves that were observed in Kaikoura at 2.5m, Christchurch at 1m, and Wellington at 0.5m. The tsunami waves arrived in Kaikoura significantly earlier than in Christchurch and Wellington indicating that the tsunami was generated near Kaikoura. The waves were likely generated by offshore faulting, but also may be associated with submarine landsliding. Fortunately, the scale of the tsunami waves did not produce significant damage. RMS’ latest New Zealand Earthquake HD Model captures tsunami risk due to local ocean bottom deformation caused by fault rupture, and is the first model in the New Zealand market to do this, that is built from a fully hydrodynamic model.

Next Generation Earthquake Modeling at RMS

Thankfully the Kaikoura earthquake seems to have produced damage that is lower than we might have seen had it hit a more heavily populated area of New Zealand with greater exposures – for detail on damage please see my other blog on this event.

But what Kaikoura has told us is that our latest HD model offers an advanced view of risk. Released only in September 2016, it was designed to handle such a complex event as the Kaikoura earthquake, featuring multiple-segment ruptures, a new liquefaction model at very high resolution, and the first landslide susceptibility model for New Zealand.

New Zealand’s Kaikoura Earthquake: What Have We Learned So Far About Damage?

The Kaikoura Earthquake of November 14 occurred in a relatively low population region of New Zealand, situated between Christchurch and Wellington. The largest town close to the epicentral region is Blenheim, with a population near 30,000.

Early damage reports indicate there has been structural damage in the northern part of the South Island as well as to numerous buildings in Wellington. While most of this has been caused directly by shaking, infrastructure and ports across the affected region have been heavily impacted by landsliding and, to a lesser extent, liquefaction. Landslides and slumps have occurred across the northeastern area of the South Island, most notably over Highway 1, severing land routes to Kaikoura – a popular tourist destination.

The picture of damage is still unfolding as access to badly affected areas improves. At RMS we have been comparing what we have learned from this earthquake to the view of risk provided by our new, high-definition New Zealand Earthquake model, which is designed to improve damage assessment and loss quantification at location-level resolution.

No Damage to Full Damage

The earthquake shook a relatively low population area of the South Island and, while it was felt keenly in Christchurch, there have been no reports of significant damage in the city. The earthquake ruptured approximately 150 km along the coast, propagating north towards Wellington. The capital experienced ground shaking intensities at the threshold for damage, producing façade and internal, non-structural damage in the central business district. Although the shaking intensities were close to those experienced during the Cook Strait sequence in 2013, which mostly affected short and mid-rise structures, the longer duration and frequency content of the larger magnitude Kaikoura event has caused more damage to taller structures which have longer natural periods.

From: Wellington City Council

Within Wellington, cordons are currently in place around a few buildings in the CBD (see above) as engineers carry out more detailed inspections. Some are being demolished or are set to be, including a nine-story structure on Molesworth Street and three city council buildings. It should be noted that most of the damage has been to buildings on reclaimed land close to the harbor where ground motions were likely amplified by the underlying sediments.

From: http://www.stuff.co.nz/national/86505695/quakehit-wellington-building-at-risk-of-collapse-holds-up-overnight; The building on Molesworth street before the earthquake (L) and on Tuesday (R).

From: http://www.stuff.co.nz/national/86505695/quakehit-wellington-building-at-risk-of-collapse-holds-up-overnight; The building on Molesworth street before the earthquake (L) and after on November 16 (R).

Isolated incidences of total damage in an area of otherwise minor damage demonstrate why RMS is moving to the new HD financial modeling framework. The RMS RiskLink approach applies a low mean damage ratio across the area, whereas RMS HD damage functions allow for zero or total loss – as well as a distribution in between which is sampled for each event for each location. The HD financial modeling framework is able to capture a more realistic pattern of gross losses.

Business Interruption

The Kaikoura Earthquake will produce business interruption losses from a variety of causes such as direct property or content damages, relocation costs, or loss of access to essential services (i.e. power and water utilities, information technology) that cripple operations in otherwise structurally sound buildings. How quickly businesses are able to recover depends on how quickly these utilities are restored. Extensive landslide damage to roads means access to Kaikoura itself will be restricted for months. The New Zealand government has announced financial assistance packages for small business to help them through the critical period immediately after the earthquake. Similar assistance was provided to businesses in Christchurch after the Canterbury Earthquake Sequence in 2010-2011.

That earthquake sequence and others around the world have provided valuable insights on business interruption, allowing our New Zealand Earthquake HD model to better capture these impacts. For example, during the Canterbury events, lifelines were found to be repaired much more quickly in urban areas than in rural areas, and areas susceptible to liquefaction were associated with longer down times due to greater damage to underground services. The new business interruption model provides a more accurate assessment of these risks by accounting for the influence of both property and contents damage as well as lifeline downtime.

It remains to be seen how significant any supply chain or contingent business interruption losses will be. Landslide damage to the main road and rail route from Christchurch to the inter-island ferry terminal at Picton has disrupted supply routes across the South Island. Alternative, longer routes with less capacity are available.

Next Generation Earthquake Modeling at RMS

RMS designed the update to its New Zealand Earthquake High Definition (HD) model, released in September 2016, to enhance location-level damage assessment and improve the gross loss quantification with a more realistic HD financial methodology. The model update was validated with billions of dollars of claims data from the 2010-11 Canterbury Earthquake Sequence.

Scientific and industry lessons learned following damaging earthquakes such as last month’s in Kaikoura and the earlier event in Christchurch increase the sophistication and realism of our understanding of earthquake risk, allowing communities and businesses to shift and adapt – so becoming more resilient to future catastrophic events.

India’s Need for Disaster Risk Reduction: Can it Turn a Plan into Action?

This was the first time I’d ever heard a Prime Minister praising the benefits of “risk mapping.” Mid-morning on Thursday November 3 in a vast tent in the heart of New Delhi, the Indian Prime Minister, Narendra Modi, was delivering an introductory address to welcome four thousand delegates to the 2016 Asian Ministerial Conference on Disaster Risk Reduction.

Modi mentioned his own personal experience of disaster recovery after the 2001 Gujarat earthquake in which more than 12,000 people died, before presenting a ten-point plan of action in response to the 2015 Sendai Framework for disaster risk reduction. There were no guarantees of new regulations or changes in policy, but three of his ten points were particularly substantive.

First there was a call for appropriate protections to be applied to all government sponsored construction of infrastructure or housing against the relevant hazards at that location. Second he called for “work towards” achieving universal “coverage” (insurance if not by name?) against disasters– from the poorest villager to big industries and state governments. Third he called for standardized hazard and risk mapping to be developed not only for earthquake but for other perils: chemical hazards, cyclones, all varieties of floods and forest fires.

More Economic Development Means More Exposure to Risk

India is at a development threshold, comparable to that reached by Japan at the end of the 1950s and China in the 1990s. Rapid economic growth has led to a dramatic expansion of building and value in harm’s way and there now needs to be a significant compensatory focus on measures to reduce risk and expand protections, whether through insurance systems or flood walls.  Development in India has been moving too fast to hope that adequate building standards are being consistently followed – there are not enough engineers or inspectors.

The Chennai floods at the end of 2015 have come to highlight this disaster-prone landscape. Heavy end-of-year monsoonal downpours fell onto saturated ground after weeks of rainfall, which were then ponded by choked drainage channels and illegal development, swamping hundreds of thousands of buildings along with roads and even the main airport. The city was cut off and economic losses totaled billions of U.S. dollars, with more than 1.8 million people being displaced.

Sorting out Chennai will take co-ordinated government action and money: to implement new drainage systems, relocate or raise those at highest risk and apply flood zonations. Chennai provides a test that Disaster Risk Reduction really is a priority, as Mr. Modi’s speech suggested. The response will inevitably encounter opposition, from those who cannot see why they should be forced to relocate or pay more in their taxes to construct flood defenses.

The one community notably missing from Prime Minister Modi’s call to action was the private sector, even though a pre-conference session the day before, organized by Federation of Indian Chambers of Commerce (FICCI), had identified that 80% of construction was likely to be privately financed.

I gave two talks at the conference – one in the private sector session – on how modelers like RMS have taken a lead in developing those risk maps and models for India, including high resolution flood models that will help extend insurance. Yet armed with information by which to differentiate risk and identify the hot spots, the government may need to step in and provide its own coverages for those deemed too high risk by private insurers.

Auditing Disaster Risk Reduction with Cat Models

In a side meeting at the main conference I presented on the need to have independent risk audits of states and cities, to measure progress in achieving their disaster risk reduction goals, in particular when it comes to earthquake mortality – for which experience from the last few decades gives no perspective on the true risk of potentially large and destructive future earthquakes happening in India – this is where probabilistic catastrophe models are invaluable. The Nepal earthquake of 2015 has highlighted the significant vulnerability of ordinary brick and concrete buildings in the region.

I came away seeing the extraordinary opportunity to reduce and insure risk in India, if ten-point lists can truly be converted into co-ordinated action.

Meanwhile as a test of the government’s resolve in the days leading up to the conference, Delhi was shrouded in its worst ever smog: a toxic concoction of traffic fumes, coal smoke, and Diwali fireworks, enriched to extremely dangerous levels in micro-particles, a smog so thick and pervasive that it seeped inside buildings, so that several attendees asked why the toxic smog was not itself being classified and treated as a true “manmade disaster.”

The Cure for Catastrophe?

On August 24, 2016 – just a few weeks ago – an earthquake hit a remote area of the Apennine mountains of central Italy in the middle of the night. Fewer than 3000 people lived in the vicinity of the strongest shaking. But nearly 1 in 10 of those died when the buildings in which they were sleeping collapsed.

This disaster, like almost all disasters, was squarely man-made. Manufactured by what we build and where we build it; or in more subtle ways – by failing to anticipate what will one day inevitably happen.

Italy has some of the richest and best researched disaster history of any country, going back more than a thousand years. The band of earthquakes that runs through the Apennines is well mapped – pretty much this exact same earthquake happened in 1639. If you were identifying the highest risk locations in Italy, these villages would be on your shortlist. So in the year 2016, 300 people dying in a well-anticipated, moderate-sized earthquake, in a rich and highly-developed country, is no longer excusable.

Half the primary school in the town of Amatrice collapsed in the August 24th earthquake. Very fortunately, it being the middle of the night, no children were in class. Four years before, €700,000 had been spent to make the school “earthquake proof.” An investigation is now underway to see why this proofing failed so spectacularly. If only Italy was as good at building disaster resilience as mobilizing disaster response: some 7000 emergency responders had arrived after the earthquake – more than twice as many as those who lived in the affected villages.

The unnatural disaster

When we look back through history and investigate them closely we find that many other “natural disasters” were, in their different ways, also man-made.

The city of Saint-Pierre on the island of Martinique was once known as the “little Paris of the Caribbean.” In 1900 it had a population of 26,000, with tree-lined streets of balconied two and three story houses. From the start of 1902 it was clear the neighbouring volcano of Mont Pelée was heading towards an eruption. The island’s governor convened a panel of experts who concluded Saint-Pierre was at no risk because the valleys beneath the volcano would guide the products of any eruption directly into the sea. As the tremors increased, the Governor brought his family to Saint-Pierre to show the city was safe, and therefore, likely all but one of the city’s inhabitants, died when the eruption blasted sideways out of the volcano. There are some parallels here with the story of those 20,000 people drowned in the 2011 Japanese tsunami, many of whom had assumed they would be protected by concrete tsunami walls and therefore did not bother to escape while they still had time. We should distrust simple notions of where is safe, based only on some untested theory.

Sometimes the disaster reflects the unforeseen consequence of some manmade intervention. In Spring 1965, the U.S. Army Corps of Engineers completed the construction of a broad shipping canal – known as the Mississippi River Gulf Outlet (“Mr Go”) linking New Orleans with the Gulf of Mexico. Within three months, a storm surge flood driven by the strong easterly winds ahead of Hurricane Betsy was funnelled up Mr Go into the heart of the city. Without Mr Go the city would not have flooded. Four decades later Hurricane Katrina performed this same trick on New Orleans again, only this time the storm surge was three feet higher. The flooding was exacerbated when thin concrete walls lining drainage canals fell over without being overtopped. Channels meant for pumping water out of the city reversed their intended function and became the means by which the city was inundated.

These were fundamental engineering and policy failures, for which many vulnerable people paid the price.


My new book, “The Cure for Catastrophe,” challenges us to think differently about disasters. To understand how risk is generated before the disaster happens. To learn from countries, like Holland, which over the centuries mastered their ever-threatening flood catastrophes, through fostering a culture of disaster resilience.

Today we can harness powerful computer technology to help anticipate and reduce disasters. Catastrophe models, originally developed to price and manage insurance portfolios, are being converted into tools to model metrics on human casualties or livelihoods as well as monetary losses. And based on these measurements we can identify where to focus our investments in disaster reduction.

In 2015 the Tokyo City government was the first to announce it aims to halve its earthquake casualties and measure progress by using the results of a catastrophe model. The frontline towns of Italy should likewise have their risks modeled and independently audited, so that we can see if they are making progress in saving future lives before they suffer their next inevitable earthquake.


The Cure for Catastrophe is published by Oneworld (UK) and Basic Books (US)

Disasters Without Borders

On November 24 and 25, 2015 the first Scientific Symposium was held in London to discuss science for policy and operations for the new “Disaster Risk Management Knowledge Centre.” The Centre was launched by the European Commission in September this year to help member states respond to emergencies and to prevent and reduce the impact of disasters. The Centre will offer EU countries technical and scientific advice, provide an online repository of relevant research results, and create a network of crisis management laboratories. RMS was the only catastrophe modeler invited to present to the meeting.

Jointly organized by the UK Met Office and the European Commission, the symposium exposed some of the tensions between what countries can do on their own and where they require a supranational European institution. The British government contingents were particularly keen to show their leadership. The UK Cabinet Office co-ordinates inputs across government departments and agencies to manage a national risk register, identifying the likelihood and potential impact of a wide range of threats facing the country: from an Icelandic volcanic eruption to a storm surge flood to a terrorist incident. The office of the Chief Government Scientist then leads the response to the latest disaster, reporting directly to the Prime Minister.

These were not responsibilities the UK would ever consider transferring to a new European institution, because they go right to the heart of the function of a government—to protect the people and the national interest. However no single country can provide total management of events that run across borders, in particular when it is the country upstream that is controlling what heads your way, as with water storage dams. For this a Europe wide agency will be vital. The Centre will be most useful for the smaller European countries, unable to sustain research across the full range of hazards, or monitor activity around the clock. However do not expect the larger countries to share all their disaster intelligence.

Where does RMS fit into this picture? As described at the London symposium, probabilistic models will increasingly be key to making sense of potential disaster impacts and for ensuring organizations don’t become fixated on planning against a single historical scenario. RMS has more experience of probabilistic modeling than any other European science or government agency, in particular in areas such as the modeling of floods and flood defenses or for multi-hazard problems.

Two ideas with the potential for RMS leadership got picked up at the symposium. For an intervention such as a new flood defense, the results of the probabilistic model become used to define the “benefits”—the future losses that will not happen. A versatile model is required in which the user can explore the influence of a particular flood defense or even see the potential influence of climate change. Second we can expect to see a move towards the risk auditing of countries and cities, to show their progress in reducing disaster casualties and disaster impacts, in particular as part of their Sendai commitments. We know that risk cannot be defined based only on a few years of disaster data—the outcomes are far too volatile. Progress will need to be defined from consistent modeling. Catastrophe modeling will become a critical tool to facilitate “risk-based government”:  from measuring financial resilience to targeting investment in the most impactful risk reduction.

The Sendai World Conference on Disaster Risk Reduction and the Role for Catastrophe Modeling

The height reached by the tsunami from the 2011 Great East Japan earthquake is marked on the wall of the arrivals hall at Sendai airport. This is a city on the disaster’s front line. At the four year anniversary of the catastrophe, Sendai was a natural location for the March 13-18, 2015 UN World Conference on Disaster Risk Reduction, to launch a new framework document committing countries to a fifteen year program of actions. Six people attended the conference from RMS: Julia Hall, Alastair Norris, Nikki Chambers, Yasunori Araga, Osamu Takahashi, and myself, to help connect the worlds of disaster risk reduction (DRR) with catastrophe modeling.

The World Conference had more than 6,000 delegates and a wide span of sessions, from those for government ministers only, through to side events arranged in the University campus facilities up the hill. Alongside the VVIP limos, there were several hundred practitioners in all facets of disaster risk, including representatives from the world of insurance and a wide range of private companies. Meanwhile, the protracted process of negotiating a final text for the framework went on day and night through the life of the meeting (in a conference room where one could witness the pain) and only reached final agreement on the last evening. The Sendai declaration runs to 25 pages, contains around 200 dense paragraphs, and arguably might have benefited from some more daylight in its production.

RMS was at the conference to promote a couple of themes—first, that catastrophe modeling should become standard for identifying where to focus investments and how to measure resilience, moving beyond the reactive “build back better” campaigns that can only function after a disaster has struck. Why not identify the hot spots of risk before the catastrophe? Second, one can only drive progress in DRR by measuring outcomes. Just like more than twenty years ago when the insurance industry embraced catastrophe modeling, the disasters community will also need to measure outcomes using probabilistic models.

In pursuit of our mission, we delivered a 15-minute “Ignite” presentation on “The Challenges of Measuring Disaster Risk” at the heart of the main meeting centre, while I chaired a main event panel discussion on “Disaster Risk in the Financial Sector.” Julia was on the panel at a side event organized by the Overseas Development Institution on “Measuring Resilience” and Robert was on the panel for a UNISDR session to launch their global work in risk modeling, and on a session organized by Tokio Marine with the Geneva Association on “How can the insurance industry’s wealth of knowledge better serve societal resilience?”—at which we came up with the new profession of “resilience broker.”

The team was very active, making pointed interventions in a number of the main sessions, highlighting the role of catastrophe models and the challenges of measuring risk, while Alastair and Nikki were interviewed by the local press. We had prepared a leaflet that articulated the role of modeling in setting and measuring targets around disaster risk reduction that was widely distributed.

We caught up with many of our partners in the broader disasters arena, including the Private Sector Partners of the UNISDR, the Rockefeller 100 Resilient Cities initiative, the UNEP Principles for Sustainable Insurance, and Build Change. The same models required to measure the 100-year risk to a city or multinational company will, in future, be used to identify the most cost effective actions to reduce disaster risk. The two worlds of disasters and insurance will become linked through modeling.