KatRisk RAA 2016
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KatRisk RAA 2016 presentation highlights the latest technology in catastrophe modeling utilizing supercomputing, globally correlated event sets and hyper-resolution flood models.
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KatRisk RAA 2016
- 1. From Hazard Maps to Loss Analytics and Software Solutions RAA Cat Risk Management February 2016 KatRisk LLC 752 Gilman St. Berkeley, CA 94710 510-984-0056 www.KatRisk.com Confidential
- 3. Hazard Maps 3 Hazard Maps Location Loss Analytics Probabilistic Models Complete Coming in 2016 35 Countries in Europe 15 Countries in Asia US and Canada
- 4. Modeling Overview 4 q All areas covered with 2-d hydraulic modeling approaches q No lower limit on the size of catchment modeled q Includes both riverine and pluvial (surface water) flooding q Six return periods for each region: 10, 20, 50, 100, 200, 500 years q Flood depths as well as flood extent Hazard Maps Location Loss Analytics Probabilistic Models
- 5. Coverage and Extent of Modeling Red outlines – FEMA 100 year flood zones Blue – high resolution model including pluvial (surface) and fluvial (riverine) flooding q FEMA FIRMs cover much but not all of the US q In many areas they cover the main rivers but not smaller streams and surface water flooding q Need to model the the water getting to the rivers as well as out of the rivers 5 Hazard Maps Location Loss Analytics Probabilistic Models
- 6. TITAN Supercomputer 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. 6 Hazard Maps Location Loss Analytics Probabilistic Models
- 7. Canada Flood Map Examples 7 Hazard Maps Location Loss Analytics Probabilistic Models
- 8. Europe Flood Map Examples 8 Hazard Maps Location Loss Analytics Probabilistic Models
- 9. Asia Flood Map Examples Bangkok Jakarta Kuala Lumpur Seoul 9 Hazard Maps Location Loss Analytics Probabilistic Models
- 10. Flooded Downtown Area Outside of FEMA Hazard Zones Blue Shading – KatRisk Flood Model Red Hatched – FEMA Zones A and V Pensacola Flooding April 2014 10 1 9 4 Hazard Maps Location Loss Analytics Probabilistic Models
- 11. 1 98 5 10 2 7 4 6 Photos Pensacola News Journal 3 Pensacola Flooding April 2014 Hazard Maps Location Loss Analytics Probabilistic Models
- 12. South Carolina Flood Event 12 Hazard Maps Location Loss Analytics Probabilistic Models
- 15. Additional Data Layers 15 q Inland Flood Score: Relative risk score based on flood depths surrounding a geocoded long/lat q Leveed Areas: Areas designated as protected by levee either on FEMA flood zones maps or the US Army Corps of Engineers National Levee Database q FEMA zones q SLOSH Storm Surge: NOAA SLOSH storm surge flood heights for Category 1-5 Hurricanes and a KatRisk relative storm surge risk score Storm Surge Score Hazard Maps Location Loss Analytics Probabilistic Models
- 16. What to do with Hazard Data 16 Davenport IA Davenport IA Ambler, PA May 2014 Relative Risk Score Risk selection metrics • Flood Depth at 6 return periods • Presence of levees • FEMA zone designation Hazard Maps Location Loss Analytics Probabilistic Models
- 17. Portfolio Risk Analytics 17 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% Negligible Minimal Very Low Low Moderately Low Moderate Moderately High High Very High Extreme 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% Negligible Minimal Very Low Low Moderately Low Moderate Moderately High High Very High Extreme High Risk Portfolio – over ½ in FEMA A Zones Low/Moderate Risk Portfolio Hazard Maps Location Loss Analytics Probabilistic Models
- 18. Location Loss Analytics 18 Hazard Maps Location Loss Analytics Probabilistic Models q Flood depths at multiple return periods is equivalent to having a hazard return period at each grid cell.
- 19. Modeling Vulnerability q Vulnerability Characteristics o Occupancy o Construction o Number of Stories o Presence of basement o First Floor Elevation o Vulnerability modifiers by coverage q Loss Distributions modeled around Mean Damage Ratio q All vulnerability data is open 19 Lumped probabilities of 0 and 100% damage, dependent on the mean damage ratio Hazard Maps Location Loss Analytics Probabilistic Models
- 20. Loss Analytics Data Input/Output 20 q Input o Location (Country,State,Long/Lat) o Coverage Values § Building § Contents § BI/ALE o Occupancy o Construction o Number of Stories o Presence of Basement o First Floor Elevation o Vulnerability Factors o Deductible/Limit q Default values assigned if unknown q Output o Flood depths at 6 return periods o Flood risk score o 100 year maximum depth within 100 meters o Average Annual Loss o Return Period Losses o In the US § Levee information § FEMA zone § HUC zone § SLOSH storm surge heights § Hurricane wind speeds Hazard Maps Location Loss Analytics Probabilistic Models
- 21. Loss Analytics Software 21 q Built using R/R-Shiny: All code and data open q Deployed or via the web q Fast analysis results, millions of locations overnight q Multi-region analyses in one run q Demo for the US at http://www.katalyser.com/katrisk_flood_analytics_demo/ Hazard Maps Location Loss Analytics Probabilistic Models
- 22. Event Based Portfolio Models q Currently developing event based probabilistic models that are consistent with flood hazard maps q Planned release of US and Canada models in 2016 q Covering all sources of flooding within a correlated event set o Inland flood o Explicit modeling of tropical cyclone rainfall and storm surge (along with wind) q Representing correlations in space and time of weather and climate events q Having a flexible modeling framework that allows for the inclusion of climate change scenarios and forecasting 22 Hazard Maps Location Loss Analytics Probabilistic Models
- 24. US and Asia Wind Modeling q To support our probabilistic event models, hurricane track sets have been developed for the Atlantic Basin and Northwest Pacific Basin q Currently developing tracks for all other basins worldwide q Running US storm surge analyses for the 50k year event set q Combined with roughness, windfield, and vulnerability models, full wind loss modeling capabilities are available Loss Costs 24 Hazard Maps Location Loss Analytics Probabilistic Models
- 25. Task #1: Work on Global Correlations ν Get ocean and atmospheric data and establish correlations Ocean SST and precipitation Main modes of SST variability from principal component analysis (PCA) 25 Hazard Maps Location Loss Analytics Probabilistic Models SST Precip Movie
- 26. Task #2: Establish correlations TC precip ENSO AMOThree month lag anomaly correlation with PCAs 26 q “Trigger” pluvial and fluvial flood hazard maps based on probabilistic meteorology and hydrological model o Combine TC and non-TC precip o Base hurricane model and global precipitation model on same data set of global SST expressing natural variability and global correlations Hazard Maps Location Loss Analytics Probabilistic Models
- 27. Example: US & Caribbean Hurricane Sample Tracks KatRisk TC Model Loss Cost Map 27 q 25 climate conditioned hurricane track sets have been developed for the Atlantic Basin (1km resolution, 50k years of events) q Combined with roughness, wind filed, and vulnerability models, full wind loss modeling capabilities are available q Free online wind loss analysis tool (Katalyser) available at our website Hazard Maps Location Loss Analytics Probabilistic Models
- 28. US Rates and Losses 1900-2010 28 q Losses conditional on SST q Two most dominant SST patterns (ENSO, AMO) drive models q Historical losses are from our hurricane model using current US exposure Hazard Maps Location Loss Analytics Probabilistic Models
- 29. 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 clustering # Atlantic TCs with SST Dispersion = 1.36 # Atlantic TCs Poisson 29 Hazard Maps Location Loss Analytics Probabilistic Models
- 30. Regional: Florida and Southeast Florida Southeast Dependency on Atlantic SST Anomaly and ENSO 30
- 31. Katalyser Software Application 31 q R/R-Shiny based application q Open code and data Exposure Analytics and Visualization Hazard Maps Location Loss Analytics Probabilistic Models
- 32. Analytical Capabilities 32 q Set user defined model parameters q Look at overall EP curves and drill down to key events q Visualize individual events and impacted locations Hazard Maps Location Loss Analytics Probabilistic Models
- 33. How Products are Being Accessed q Flood Map Data and Location Loss Analytics o Direct delivery of GIS files and Software Code o Web Mapping Service (WMS) o Delivery on third party GIS platforms o Online batch lookup q Probabilistic Models o Katalyser Analysis Platform o Working with third party platforms 33
- 34. Recap 34 Hazard Maps Location Loss Analytics Probabilistic Models and Software q Currently covering: o US o Canada o Europe o 15 Asia Countries q Coming next: o South/Central America o Mexico o Australia/NZ o Rest of Asia o Middle East o Africa q Available for all modeled regions q Hazard data retrieval and loss calculations q Open code and data q Deployed, Hosted, APIs q In development q US and Canada capabilities in 2016