using ornl titan to develop 50k years of flood risk ... · ornl titan used to compute global...

Using ORNL Titan to develop 50k years of Flood Risk Scenarios (for FEMA / NFIPand other clients)

Dag Lohmann, April 17th 2018

KatRisk LLC752 Gilman St.Berkeley, CA 94710510-984-0056

www.KatRisk.com

KatRisk Deutschland GmbHWilhelmstr. 679098 Freiburg, Germany0761-5146-7600

http://www.KatRisk.com/

KatRisk HPC User Forum Agenda

KatRisk introduction

KatRisk cat response and flood maps: why new flood maps?

The core of catastrophe modeling

Using ORNL Titan to compute flood maps

From flood maps to risk models

Coupled tropical cyclone wind, flood and storm surge results for the US

KatRisk Introduction – HPC User Forum Founded in 2012, global flood and wind catastrophe models

Diverse customers– 3 of top 4 insurance brokers

– 2 of top 3 reinsurance companies

– ~ 30 primary insurers

– FEMA (US Hurricane Wind, Storm Surge and Inland Flood) + others

Sea level rise and changing precipitation extremes sensitivity

Heavy compute power needed to compute US on 10m resolution

Hurricane Wind Fields

New Orleans Storm Surge

Detailed Flood (Harvey)

KatRisk utilized resources of the Oak Ridge Leadership Computing Facility at the Oak Ridge National Laboratory, which is supported by the Office of Science of the U.S. Department of Energy under Contract No. DE-AC05-00OR22725.

5 Million hours, 2-d GPU SWE code

Detailed slides on sea level rise and US wide losses on http://www.katrisk.com

KatRisk Cat Response

For the last three years KatRisk has released wind and flood footprints of major events within days of an event

Inform KatRisk models with observations (Data Assimilation)

Cat Response slides are on http://www.katrisk.com/recent-eventsCompare flood footprint with FEMAand point observations (Pensacola 2014)

Harvey KatRisk Event Response

http://www.katrisk.com/recent-events

Flooded Downtown Area Outside of FEMA Hazard Zones

Blue Shading – KatRisk Flood ModelRed Hatched – FEMA Zones A and V

Pensacola Flooding April 2014

1

98

5

10

2

7

4 6

Photos Pensacola News Journal

3

Pensacola Flooding April 2014

Why new maps? Coverage and Extent of Modeling

Red outlines – FEMA 100 year flood zones

Blue – high resolution model including pluvial (surface) and fluvial (riverine) flooding

FEMA FIRMs cover much but not all of the US

In many areas they cover the main rivers but not smaller streams and surface water flooding

Need to model the the water getting to the rivers as well as out of the rivers

KatRisk Pluvial / Fluvial Modeling

10

Fluvial Flood Pattern

Pluvial Flood Pattern

Fluvial boundary conditions from upstream catchments

USGS catchment 0101000906

Boundary conditions from storm water runoff input

Combined Flood Footprint

Finite Volume Navier-Stokes Equations

Finite Volume Diffusive Wave

ORNL TITAN used to compute global pluvial and fluvial maps

USA Flood Maps (NY)

NY State FEMA and KatRisk coverage

Zoom into NY Flood Maps

KatRisk Red and White, FEMA Blue

NYC Flood Map


More NY State Flood Risk Map


History of Catastrophe Models AIR (1987) and RMS (1988) founded

– Build first EQ and hurricane models

1992: Hurricane Andrew

– $16B insured losses

– 11 insolvencies

1994: Northridge Earthquake


1996: First cat bonds, Rating Agencies require cat loss information

2001/2002: WTC and first terrorism model

2005: Hurricane Katrina


– 0 insolvencies

What is at the core of catastrophe models?Answer: Quantifying the economic and insured losses of natural catastrophes KatRisk economic losses for US hurricane, storm surge and inland flood: AAL = $39 Bn

Model run with economic exposure–About $80 Trillion insurable–Three Lines of Business (RES, COM, IND)–Average Vulnerability–KatRisk Default Flood Defences–Ran every 10th location–100 Samples (5 Million year EP)–Model IF/SS results sensitive to assumptions of BFE

–SpatialKat run-time GU/GR ~ 80 minon 25 cores Xeon E5-2690

Harvey = $80 Bn

16 Year RP Harvey ($80 Bn) was an event thathas a loss exceedance probabilityof 1/16 ~ 6% in any given year

AAL = Average Annual LossOEP = Occurrence Exceedance ProbabilityAEP = Aggregate Exceedance Probability

KatRisk Simplified Global Workflow

Probabilistic Deterministic Expensive Financial + Analysis + API

Probabilistic VARMA based Ocean SST model

Probabilistic Tropical Cyclone Track Model Probabilistic Precipitation and Temperature Model, Surface Meteorology

TC Precipitation Model

Land Surface Model River Routing Model

Hydraulic 2-d Flood Model

Tropical Cyclone Wind Model

Storm Surge Model, Tidal Model

2-d hydraulic

Exposure and GU Loss Model (API for third party data integration)

Insured Loss Model (Policies, Treaties)

Statistics, Analysis, Maps (WMS), Web Interface (GUI) and Web Service (API)

Probabilistically sampled vulnerability with correlated severity distributions

TITANAWS

2017 KatRisk US Inland Flood, Storm Surge, Hurricane Model

Summary Highlights and some Cat Model Industry Firsts Fully correlated multi-peril 50k year event set (up to 50 Million years

sampled) with TC and non-TC flood events

Groundbreaking low run-times from laptop to server to cloud

2-d hydraulic modeling everywhere (storm surge and inland flood) with user defined inland flood defenses (with KatRisk defaults)

Actuarial coherent view of risk computations with repeatable location aware correlated uncertainty sampling (allows buildings as footprints)

Global correlations through teleconnections and climate change sensitivity

Transparent financial model with multi-peril contracts

Expose key model sensitivities to user (flood defences, correlation, etc.)

KatRisk Hurricane and Storm Surge Model A climate conditioned hurricane track set developed for the Atlantic Basin (1km resolution,

10k * 5 years of events)

Combined with roughness, windfield, and vulnerability models, full wind loss modeling capabilities

Sample Tracks 100 Year Windspeed Map

Storm Surge and Inland Flood Storm surge (SS) has been simulated for the

entire 50k year track set and output on a 10m resolution grid with parametric wave model

Inland flood simulation with TC and non-TC rainfall. 50k years of continuous simulation of pluvial and fluvial flooding (KatRisk US Flood Model 2017)

Correlated Wind fields, storm surge, and TC precipitation

Make new stochastic monthly precipitation

Recipe: create non-TC precipitation from global VARMAX model– Run global SST model

– Condition prec on SST

– Create 10k periods with

5 years each

– Add other precipitation

sources (TC, AR) daily and

and sub-daily

– Movie shows 50 years of

stochastic precipitation

Storm Surge Modeling Storm surge has been analyzed for 50,000 years of hurricane tracks

Houston

Chesapeake Bay

New Orleans

New York

Images show KatRisk Score (1-10)

Peril – Peril Correlation: Harvey

KatRisk released modeled footprint during event, and updated throughout event

Loss estimates based on KatRisk footprints– 8.8 million point IED in Texas

– $40 - $50 Billion GU Texas Inland Flood Loss

– Large demand surge (1.4?) + wind and storm surge (<$2 Billion) + other areas ~ $80 Billion

Overview of US Economic Insurable Losses

USA AAL All Perils (TC, IF, SS) Combined = $39 Billion +- $6 Billion

Model run with economic exposure– About $80 Trillion insurable

– Three LOBs

– Average Vulnerability

– Ran every 10th location

– 100 Samples (5 Million year EP)

– Model IF/SS results sensitive to

assumptions of BFE

– SpatialKat run-time GU/GR ~ 80 min

on 25 cores Xeon E5-2690$80 Billion

16 Year RP

AAL and EP all Perils (Flood, Storm Surge, Wind)

CombinedWind

Inland FloodStorm Surge

CombinedWind


OEP AEP

$80 Billion

16 Yr RP

77 Yr RP

$80 Billion

Combined OEP and AEP curves for all perils and combined– AAL TC Wind = $12 Billion - $15 Billion

– AAL Inland Flood = $16 Billion - $22 Billion

– AAL Storm Surge = $4 Billion - $7 Billion

Wind drives tail riskFlood AEP highest in low return periods

OEP

EP all Perils (Flood, Storm Surge, Wind)

Zoom: all perils combined

CombinedWind


CombinedWind


OEP AEP

$80 Billion

16 Yr RP

77 Yr RP

Deeper look into TC vs. non-TC losses

CombinedWind


CombinedWind


OEP AEP

$80 Billion

420 Yr RP

25 Yr RP

Just TC only, wind, inland flood, storm surge

How special was Harvey for just TC flood? Answer: very

Deeper look into TC vs. non-TC losses

Zoom: Just TC only, wind, inland flood, storm surge

CombinedWind


CombinedWind


OEP AEP

420 Yr RP

$80 Billion

AAL TC Flood = $3.5 Billion to $5 Billion (18% to 25%)– Contribution of Atlantic is about 17% to 23.5%, Pacific the rest

Overview of Losses – TC contribution to Flood

AAL TC Flood = $3.5 Billion to $5 Billion (18% to 25%)– Contribution of Pacific is about 1% to 1.5%, Atlantic the rest

Overview of Losses – TC contribution to Flood

Effects of ENSO on Precipitation in Oct – March

https://www.climate.gov/news-features/featured-images/how-el-ni%C3%B1o-and-la-ni%C3%B1a-affect-winter-jet-stream-and-us-climate

Flood AAL differrence El Nino

Wet

Dry Strongest Effect on Precipitation is during Oct-Mar

1. Filter out non Oct-Mar Events (IF Only)

2. Compute State AAL3. Filter Out Oct-Mar and

Strong + ENSO Years4. Compute % Difference

Flood AAL Difference La Nina

Wet

Dry Strongest Effect on Precipitation is during Oct-Mar

1. Filter out non Oct-Mar Events (IF Only)

2. Compute State AAL3. Filter Out Oct-Mar and

Strong + ENSO Years4. Compute % Difference

USA AAL by Atlantic SST and ENSO

Hurricane losses dependency on Atlantic SST Anomaly and ENSO

AAL by Atlantic SST

AAL by ENSO

Introduction of SST leads to clusteringfor TCs that cause losses in the USA

# Atlantic TCs with SST Dispersion = 1.15# Atlantic TCs Poisson

SpatialKat Financial Model

Explicit inuring order between perils

Choose wind or flood first

Choose how wind and flood losses should be

executed within a contract

Choose how surge and inland flood should be

executed within a contract

Financial ModelLimits, Deductibles

and BlanketsLocation

CoverageSite

AccountPortfolio

FacultativeReinsurance

Special Conditions

Comprehensive client survey to ensure contracts execute as they

do in reality

Climate Sensitivity: Short Story about Sea Level

Representative Concentration Pathways

LIG127k

11k to today rise in sea level

Lohmann, AWI

Sea Level Rise Puzzle During Last Inter-Glacial (LIG) exposed fossil reef indicate 5m - 9m higher sea

level (Dutton & Lambeck, 2012, Dutton et al., 2015)

LIG with Sea Surface Temperature Southern Hemisphere + 1 - 3oC warmer (Capron et. al. 2014)

Lohmann, AWI

Melting West Antarctic Ice Sheet from below Last Interglacial: Climate Models and paleo-climate data are consistent

Antarctic Ice Sheet: Marine ice sheet instability -> Sea level rise

Threshold ~2°C based on paleo-climate and climate model studies

Lohmann, AWI

KatRisk Surge Climate Change Study

Compares USA surge losses with current conditions, conditions around 1900, and a uniform 30 cm sea level rise (SLR)– Current speed of SLR is about 2.8 to 3.6 mm/year (currently accelerating), and was about

1.8 mm/year in the 20th century

Use high resolution exposure of $6.88 trillion along the coasts results summarized on 200m gridded resolution

Buildings, contents, time element and appurtenant structures modeled

Ground-up AAL increased from $5 billion to $6.9 billion, implying an increase of about $60 million per centimeter SLR, or currently about $20 million per year (although the increase is not linear), equal to 0.4% of the AAL – but also with potential to accelerate.

Ground-up AAL increased from $4 billion to $5 billion based on a 20cm sea level rise between 1900 and today. Simulations for 1900 assume the same sea defenses, bathymetry, and tropical cyclone frequency and severity as today.

Number are slightly different compared to before – ran different BFE assumptions for this

Sea Level Rise 30cm

SS EP curves past, present and potential future

Current

Loss / RP 2 5 10 20 50 100 200 500 1000

1900 [$billion] 0.443 3.6 8.4 16.9 33.2 48.1 65.8 95.7 127.3

BASE [$billion] 0.65 4.8 10.8 20.9 39.5 56.4 75.9 108 141

SLR [$billion] 1.0 7.1 15.2 27.6 49.6 69.6 92.2 128 161

AAL = $5.0 Bn AAL = $6.9 BnAAL = $4.0 Bn

1900

Southern Florida Exposure

Southern Florida (AAL GU loss ratio 1900)

Southern Florida (AAL GU loss ratio now)

Southern Florida (AAL GU loss ratio SLR)

Increase in GU loss AAL [$Bn] by State

Increase in GU loss AAL between 1900 and today, as well as today to uniform 30cm SLR scenario.

Exposures are from current residential, commercial and industrial estimates

Risk increase is measured as increase in AAL by state

KatRisk US results for wind, flood, storm surge

Questions

using ornl titan to develop 50k years of flood risk ... · ornl titan used to compute global...

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