2004 RMS June 7-8 Boston A Collaborative Design for Catastrophe Management The impact of new Science on Catastrophe Modeling CARe Boston June 7 th & 8 th 2004 Dr. Robert Muir-Wood Chief Research Office & EVP Copyright RMS 2004

Today’s questions q q1) What has been learnt that is new from recent smaller Catastrophes – such as Hurricane Isabel - or the San Simeon Earthquake - that has more general application to understanding the future losses from larger Catastrophes? q q2) What are the new scientific findings that have emerged since the 1990s to change how Hurricane Catastrophe risk should be modeled in the Northeast? © 2004 Risk Management Solutions, Inc. Confidential

Hurricane CAT modeling is years old - Model T 1909 REAC 400, 1960 Some other examples of 12 year old technologies: © 2004 Risk Management Solutions, Inc. Confidential

1) Something about Isabel Isabel at Cat 5 – NE of Puerto Rico © 2004 Risk Management Solutions, Inc. Confidential

VRG Windfield and Recorded Windspeeds 26 : Complete record 26 : Incomplete – i.e. peak missing Peak Gust mph Permanent stations © 2004 Risk Management Solutions, Inc. Confidential

Post-event insured mean loss estimates for Isabel SeptOctNovDecJanFeb $1Bn $2Bn PCS I I I AIR EQE RMS © 2004 Risk Management Solutions, Inc. Confidential

A forensic investigation of Isabel © 2004 Risk Management Solutions, Inc. Confidential

Tree damage close to the coast Treefall © 2004 Risk Management Solutions, Inc. Confidential

Urban tree damage Richmond VA (65mph) © 2004 Risk Management Solutions, Inc. Confidential

Treefall deep inland: Montgomery County <50mph © 2004 Risk Management Solutions, Inc. Confidential

American Association of Wind Engineers perspective on Isabel ( American Association of Wind Engineers perspective on Isabel ( q‘the overall wind velocities were below the ASCE 7 recommendations’ q‘the damage that resulted was not of a type that might have been expected for the average winds that occurred and in fact there was relatively limited direct structural damage.’ q‘there was a large amount of structural damage resulting from fallen trees striking structures.’ q‘the types of failures and damage that occurred in Isabel indicate that there is a whole new area of research that should be pursued by wind engineers.’ © 2004 Risk Management Solutions, Inc. Confidential

Comparative woodframe residential ZIP level %losses RMS has analyzed c 15% of all claims © 2004 Risk Management Solutions, Inc. Confidential

Comparative Mean Damage Ratios v Windspeed Band The ‘Isabel Effect’ is only seen below 70mph. © 2004 Risk Management Solutions, Inc. Confidential

Exposure Values in the path of Isabel’s windfield Falling windspeeds Rising exposure values © 2004 Risk Management Solutions, Inc. Confidential

Comparative Industry Exposure Value by Windspeed Band © 2004 Risk Management Solutions, Inc. Confidential

Why did trees blow down at lower windspeeds than ‘normal’ in Isabel? qGeneric effects A) Exceptionally wet antecedent conditions? B) Lack of high winds for many years? C) Inadequate tree maintenance – of older trees? D) Higher density of urban trees in this region? E) Poorer soils, influence of tree species? qRegional Effects © 2004 Risk Management Solutions, Inc. Confidential

Summer Rainfall before Isabel © 2004 Risk Management Solutions, Inc. Confidential

Overturning from saturated soil: Foxhall (50mph) Many mature trees fell away from the roadway: -asymmetric rootball -shallow urban soil layer -runoff concentrated © 2004 Risk Management Solutions, Inc. Confidential

Highest windspeeds in MidAtlantic region since 1970 Area impacted by Isabel has been untouched by Hurricane winds for >30 years © 2004 Risk Management Solutions, Inc. Confidential

C) Tree maintenance qPruning rigor correlates with recent damage qResistance to tree maintenance tends to correlate with affluence as mature trees increase property values © 2004 Risk Management Solutions, Inc. Confidential

D) Percentage of urban areas covered by trees versus population density (by State) Virginia has high tree density even in cities © 2004 Risk Management Solutions, Inc. Confidential

qGeneric effects Exceptionally wet antecedent conditions? Lack of high winds for many years Inadequate tree maintenance – of older trees? Higher density of urban trees in this region Poorer soils, influence of tree species qRegional Effects Why did trees blow down at lower windspeeds than ‘normal’: - allocating the causes ? Interrelated © 2004 Risk Management Solutions, Inc. Confidential

‘Trees are more of a threat to the U.S. power grid than terrorists’, Michael Gent, President of the North American Electric Reliability Council Oct 27 th 2003 © 2004 Risk Management Solutions, Inc. Confidential

Isabel’s power outages q q5.8 million customers lost power (largest ever in a natural disaster) q q‘Not a single transmission line went out of service where there were no trees’. (Ken DeFontes, VP of T&D: Baltimore Gas and Electric) q q‘Many utilities have fired their in-house tree trimming crews and hired cheaper contractors’, (Robert Burns, a senior researcher with the National Regulatory Research Institute). q q28% of residential claims and 10% of losses freezer-contents related – –average claim value $950 – –payments sometimes made outside the terms of the original insurance q qHigher proportion of commercial claims relate to power outage: © 2004 Risk Management Solutions, Inc. Confidential

Implications for Hurricane CAT loss modeling © 2004 Risk Management Solutions, Inc. Confidential

Role of Trees in affecting Residential vulnerabilities (for typical inventory) Loss% windspeed 50mph 100mph proportion of total loss from tree damage Building only Combined Tree only © 2004 Risk Management Solutions, Inc. Confidential

Impact of reducing the windspeed threshold for treefall Loss% windspeed 50mph 100mph proportion of total loss from tree damage c 10mph reduction in start of tree damage vulnerabilities Inland Windspeeds Building only Combined Tree only baseline © 2004 Risk Management Solutions, Inc. Confidential

Implications for modeling the risk Proportion of buildings with high tree proximity Impact of high antecedent rainfall Windspeeds at which loss is most sensitive to excess treefall ISABEL © 2004 Risk Management Solutions, Inc. Confidential

Lessons from Isabel: Tree Proximity in Building Inventory qIsabel demonstrates that at low windspeeds, treefall can be the principal determinant of residential building damage qDamage and loss underestimated by whole wind engineering community (and all Cat modelers) q‘Tree proximity’ is currently only implicitly included in building inventory –In future likely to be included explicitly Richmond, VA Low tree proximity High tree proximity © 2004 Risk Management Solutions, Inc. Confidential

2004 RMS © 2004 Risk Management Solutions, Inc. Confidential 2) Application of New Science in modeling hurricane risk in the Northeast US

The Puzzle of the “Missing Loss” in Northeast “Hurricanes”: Top 5 Storms After (Gloria) 1999 (Floyd*) Modeled as a Hurricane With Defaults Yr2000 Loss Exposure/Inflation Updated Yr 2000 Loss (Collins and Lowe, 2001) $9.4 Bn $2.1 Bn $1.4 Bn $2.0 Bn $10.1 Bn $18.4 Bn $5.0 Bn $2.31 Bn 1954 (Carol) $6.1 Bn $10.6 Bn X 2.0 X 4.8 X 1.6 X 1.7 X 2.5 Total $21.0 Bn $46.4 Bn X 2.2 * Loss also in Mid Atlantic and NC Multiple # # # # Default RMax and windfield parameters © 2004 Risk Management Solutions, Inc. Confidential

Development of ‘Anomalies’ in the 1990s paradigm for hurricane modeling in the North East US qStandard hurricane windfields exaggerate updated historical losses in the North East by an average of x2 –identified in RMS 1997 work on ‘historical updated’ losses –updated historical losses confirmed and refined by Collins and Lowe (2001) CAS study qResponse to the anomalies: –1997 RMS IRAS3.6 (RiskLink4.2) model employed ‘NorthEast region hurricane windfield parameters’ to get consistent empirical match with historical losses –however at the time there was no physical explanation for these empirical modifications © 2004 Risk Management Solutions, Inc. Confidential

Extratropical Transition (Typhoon Kochi June 2003) © 2004 Risk Management Solutions, Inc. Confidential

The surge in Extratropical Transition Research Key Hart and Evans papers on transitioning of historical US hurricanes using ECMWF reanalysis data © 2004 Risk Management Solutions, Inc. Confidential

Historical Transitioning Storms (around 45% of all Atlantic hurricanes undergo transition) Opal Hugo Hazel Bob 1938 Carol Gloria Floyd © 2004 Risk Management Solutions, Inc. Confidential

Deeper pressure after transitioning Hurricane pressure mb Transitioning pressure Deeper pressure before transitioning Minimum transitioning pressure v minimum hurricane pressure within 6hrs before transitioning initiated How often do transitioning storms reintensify? Cat 1 © 2004 Risk Management Solutions, Inc. Confidential

Transitioning & Forward Speed Forward Speed (mph) % of Systems in Some Stage of Transition NHC Data: q Systems transition when they are picked up by the jet stream; the interaction with the jet alters the system’s structure q The forward speed of storms is therefore strongly linked with transition q Transitioning storms in the stochastic model are identified by assessing forward speeds All storms above 40mph transition within next 6-12hrs © 2004 Risk Management Solutions, Inc. Confidential

Sustainable Hurricane Central Pressures in U.S. Atlantic Margin 960mb900mb 930mb Lowest sustainable September pressures from Emanuel et al. closest approach to Long Island to Long Island © 2004 Risk Management Solutions, Inc. Confidential

1938 Gloria Bob 1869 Role of forward speed in affecting transitioning status of North East Storms at landfall Central pressure (mb) Forward Speed (mph) Cat 4 Cat 3 Cat 2 Estimated Probability of Transitioning75-95% >95% <75% 95% 75% Theoretical limit © 2004 Risk Management Solutions, Inc. Confidential

Maximum Windspeeds of Transitioning Storms Mean wind speed (mph) in the mb range Transitioned: 69.4 Transitioning: 81.6 Tropical: NHC Data © 2004 Risk Management Solutions, Inc. Confidential

The 1938 “Hurricane” Damage Footprint Combined detailed forestry damage with Fujita scale property damage data (from Boose et al, 2000) © 2004 Risk Management Solutions, Inc. Confidential

Modeling the 1938 Storm: #2 Hurricane Windfield with Rmax 2 SDs larger than average $26bn Loss Windfield as a hurricane with RMax increased by 2 standard deviations to fit damage geography on the right hand side Significant over prediction of windspeeds and damage on the left hand side © 2004 Risk Management Solutions, Inc. Confidential

Modeling the 1938 Storm: #3 With a Transitioning Storm windfield $14bn Loss Windfield as a transitioning storm © 2004 Risk Management Solutions, Inc. Confidential

The Puzzle of the “Missing Loss” in Northeast “Hurricanes”: Top 5 Storms After (Gloria) 1999 (Floyd*) Modeled as Transitioning with Defaults with Defaults 2000 Loss Exposure/Inflation Updated Yr 2000 Loss (Collins and Lowe, 2001) $9.4 Bn $2.1 Bn $1.4 Bn $2.0 Bn $1.5 Bn $14.4 Bn $2.0 Bn $1.87 Bn 1954 (Carol) $6.1 Bn $4.4 Bn X 1.5 X 0.71 X 1.3 X 0.72 X 1.0 Total $21.0 Bn $24.2 Bn X 1.1 * Loss also in Mid Atlantic and NC Multiple # # # Default transitioning time, RMax and windfield parameters © 2004 Risk Management Solutions, Inc. Confidential

The Paradigm Shift in North-East Hurricane Loss Modeling Florida Hurricane North-East Hurricane ‘Old 1990s Paradigm’ % Rmax km Florida NE Hurricane NE Transitioning New 2003 Paradigm Rmax km % Using uncorrected hurricane windfields gives $60-80Bn 1000yr loss With separate hurricane and transitioning windfields gives $35Bn 1000yr loss © 2004 Risk Management Solutions, Inc. Confidential

Conclusions for North-East Hurricane risk qThe ‘Old Paradigm’ (with North-East risk beyond 100 year return periods driven by major Cat 4 storms with pure hurricane windfields) is no longer scientifically credible Additional cost to the US Insurance Industry of the ‘old paradigm’ model =c $140M per year © 2004 Risk Management Solutions, Inc. Confidential

2004 RMS © 2004 Risk Management Solutions, Inc. Confidential Session 17D tropical cyclone extratropical transition II Chairperson: Jenni L Evans, Penn State University, University Park, PA 10:15 AM 17 D.1 The impact of extra tropical transition on hurricane risk in the Northeast USThe impact of extra tropical transition on hurricane risk in the Northeast US Robert Muir-Wood, Risk Management Solutions Ltd., London, United Kingdom; and R. Dixon and A. Boissonnade 10:30 AM 17 D.2 The extratropical transitions of eastern Pacific Hurricane Lester (1992) and Atlantic Hurricane Andrew (1992): A comparison.The extratropical transitions of eastern Pacific Hurricane Lester (1992) and Atlantic Hurricane Andrew (1992): A comparison. Michael Dickinson, Univ. at Albany/SUNY, Albany, NY; and L. F. Bosart, K. L. Corbosiero, S. Hopsch, K. Lombardo, M. J. Novak, B. Smith, and A. C. Wasula 10:45 AM 17 D.3 Synoptic composites of the extratropical transition lifecycle of North Atlantic TCs as defined within cyclone phase spaceSynoptic composites of the extratropical transition lifecycle of North Atlantic TCs as defined within cyclone phase space Robert E. Hart, Florida State University, Tallahassee, FL; and J. L. Evans 11:00 AM 17 D.4 Predictability Associated with Extratropical Transition of Tropical Cyclones as defined by Operational Ensemble Prediction SystemsPredictability Associated with Extratropical Transition of Tropical Cyclones as defined by Operational Ensemble Prediction Systems Patrick A. Harr, NPS, Monterey, CA; and D. Anwender and S. C. Jones 26th Conference on Hurricanes and Tropical Meteorology 3—7 May 2004 Miami, FL Deauville Beach Resort, 6701 Collins Avenue, Miami, FL Deauville Beach Resort, 6701 Collins Avenue, Miami, FL RMS ET Research: at the 2004 AMS meeting May 7 The Science is new and only in the RMS model!