Illustrative: event footprints crossing a portfolio, losses rising and the exceedance-probability curve

Risk Academy, led by the Nexus Consortium · Course catalogue · Risk Science and Methods

Quantitative Risk Analysis

Catastrophe, exposure and vulnerability modelling

Catastrophe, exposure and vulnerability modelling, taught twice over: as the working methods of the field and as its frontier since 2024, with labs on the Academy's tools, open data and the Nexus Standards.

Core course Frontier course

The discipline

01Core course · L2 Intermediate

Catastrophe, exposure and vulnerability modelling: foundations and practice

This area covers how risk is estimated from hazard, exposure and vulnerability: exposure data and building inventories, vulnerability and fragility functions, the components of catastrophe models, event sets and exceedance curves, secondary uncertainty and model validation, including open models.

Level
L2 Intermediate
Study time
about 24 hours (planning estimate)
Status
In authoring
Prerequisites
An L1 course in the area, or an entry review

Why now

It illustrates how model-calculated losses, not field surveys, drive parametric settlement speed and basis risk. Caribbean Catastrophe Risk Insurance Facility, CCRIF to Make Payout to the Government of Panama Following Magnitude 7.7 Earthquake, 15 October 2026

Learning outcomes

  1. Define exposure and the other key terms of the discipline and use them correctly in a written case
  2. Explain hazard, exposure, vulnerability and capacity and exposure data and building inventories with a worked example and its source
  3. Apply the discipline's method to a documented case and explain each result with its source
  4. Analyse a named case against vulnerability and fragility functions, stating evidence, date and limits

Modules

  1. Hazard, exposure, vulnerability and capacity
    • Hazard, exposure, vulnerability and capacity
    • Exposure data and building inventories
    • Vulnerability and fragility functions
  2. Catastrophe model components
    • Catastrophe model components
    • Event sets and exceedance curves
    • Model validation
  3. Open catastrophe models
    • Open catastrophe models
    • Secondary uncertainty
  4. Lab: the discipline's method
    • A hazard model delivers an intensity at a site; a fragility curve turns intensity into the probability of a damage state; a damage ratio turns the state into a share of replacement cost; multiplied by the exposed value and summed over sites and events, that share becomes the loss curve a portfolio decision rests on.
    • Work the method through a documented case and explain each result
    • Read the method's sources and stated values

Labs with Academy tools

Nexus Standards

Teaches

  • NRS-C3 Hazard, exposure, vulnerability and capacity data
  • NRS-F3 Insurance, catastrophe risk and protection gaps
  • NRS-M3 Method fabric: Exposure and asset intelligence
  • NRS-M4 Method fabric: Vulnerability, fragility and resilience
  • NRS-M5 Method fabric: Consequence and loss
  • NRS-M6 Method fabric: Catastrophe risk

Relies on

  • NS-1 The UNI and the artefact catalogue
  • NS-16 UNI application profile (how articles, documents, code, data, APIs and interfaces carry the UNI)
  • NRS-C1 Risk vocabulary and ontology
  • NRS-C2 Risk assessment method
  • NRS-C4 Risk data model, identifiers and exchange
  • NRS-C8 Evidence, uncertainty and provenance
  • NRS-C9 Risk models, methods and validation

Assessment

  • 40%Lab recordWork the discipline's method through a documented case and explain each result with its source and date
  • 40%Case memoApply the discipline's methods to a named place or organisation, stating evidence and limits
  • 20%Key terms checkShort answers on the key terms, marked against the definitions

Delivery

  • Self-paced online, with the labs in the browser
  • Cohort study over six to eight weeks, with a weekly lab review
  • Co-delivered with a partner institution, inside its own courses

Partner on this course

  • Co-teach a module and bring a current case from your work
  • Host a cohort for your learners, with your own schedule and review
  • Contribute a lab: a dataset your institution publishes openly, or a model
  • Review the course content and its references before it opens
  • Translate the course and adapt its cases to your region

How institutions and experts take part

In the Academy LMS

Course on the learning platform
Intermediate, 4 topics
Cohort group
A community group for each cohort of learners
Achievement
Recorded on completion of the assessed work

Open now in this discipline

References

  1. Caribbean Catastrophe Risk Insurance Facility, CCRIF to Make Payout to the Government of Panama Following Magnitude 7.7 Earthquake, 15 October 2026
  2. Cornell, Engineering seismic risk analysis, Bulletin of the Seismological Society of America, 1968
  3. Porter, A beginner's guide to fragility, vulnerability, and risk, Encyclopedia of Earthquake Engineering, 2015
  4. Silva et al., Development of a global seismic risk model, Earthquake Spectra, 2020
02Live map

Hazards and exposure in Italy

Flood water, active fires and surface heat beside population and night-time lights, over Italy.

The interactive map needs JavaScript; the layer list and sources are below.

Layers 3

Hazards and exposure

Latest available

NASA GIBS / EOSDIS · ASTER GDEM (METI, NASA) · Blue Marble (NASA) · © OpenStreetMap contributors (ODbL) · Natural Earth

Loading the latest NASA imagery.

Drag to move. Ctrl or ⌘ and scroll, pinch or the buttons to zoom; hover for the values under the pointer; reset returns to the region.

Hazards and exposure, framed on Italy.Satellite and model products as NASA publishes them, each with its own date. They are indicators, not assessments of any place.

Data: NASA GIBS · ASTER GDEM · Blue Marble · © OpenStreetMap contributors · Natural Earth · NASA EONET · U.S. Geological SurveySources and licences

  • We acknowledge the use of imagery provided by services from NASA's Global Imagery Browse Services (GIBS), part of NASA's Earth Science Data and Information System (ESDIS). Colours redrawn from the published colour map; values averaged into H3 cells where shown (modified). NASA open data
  • We acknowledge the use of imagery provided by services from NASA's Global Imagery Browse Services (GIBS), part of NASA's Earth Science Data and Information System (ESDIS). Colours redrawn from the published colour map; values averaged into H3 cells where shown (modified). NASA open data
  • VIIRS near-real-time products (flood, land surface temperature, snow cover, corrected reflectance), NASA LANCE; imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into H3 cells where shown (modified). NASA open data
  • NASA Fire Information for Resource Management System (FIRMS), VIIRS 375 m active fire product, NASA LANCE; vector tiles via NASA GIBS. Colours redrawn from the published colour map; values averaged into H3 cells where shown (modified). NASA open data
  • Center for International Earth Science Information Network (CIESIN), Columbia University. 2018. Gridded Population of the World, Version 4 (GPWv4): Population Density, Revision 11. NASA Socioeconomic Data and Applications Center (SEDAC). Licensed under CC BY 4.0. Colours redrawn from the published colour map; values averaged into H3 cells where shown (modified). doi:10.7927/H49C6VHW. CC BY 4.0
  • VIIRS Black Marble night-time lights, NASA Goddard Space Flight Center; distributed by the NASA Level-1 and Atmosphere Archive and Distribution System (LAADS DAAC); imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into H3 cells where shown (modified). NASA open data
  • MODIS and VIIRS atmosphere products, NASA LANCE and LAADS DAAC; imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into H3 cells where shown (modified). NASA open data
  • ASTER GDEM is a product of METI and NASA (ASTER Global Digital Elevation Model V003, NASA LP DAAC); imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into H3 cells where shown (modified). Cite as: NASA/METI/AIST/Japan Spacesystems and U.S./Japan ASTER Science Team (2019). ASTER Global Digital Elevation Model V003. doi:10.5067/ASTER/ASTGTM.003. NASA open data
  • Made with Natural Earth. Free vector and raster map data @ naturalearthdata.com. Public domain
  • © OpenStreetMap contributors (ODbL), via NASA GIBS (coastlines, boundaries, roads and place names). Colours redrawn from the published colour map; values averaged into H3 cells where shown (modified). ODbL
  • Blue Marble, NASA Earth Observatory; imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into H3 cells where shown (modified). NASA open data
  • Context on the globe and flat map: coastlines, boundaries, roads and place names from NASA GIBS reference layers (OpenStreetMap data, ODbL, © OpenStreetMap contributors); Blue Marble imagery as an optional base; 3D terrain and the elevation read-out from the ASTER GDEM elevation colour index (5 m to 200 m classes, exaggerated for legibility). Boundaries are drawn as published and imply no position on any territory.
  • Globe: MapLibre GL JS 6.9.1, BSD-3-Clause, © MapLibre contributors.
  • Live events: NASA Earth Observatory Natural Event Tracker (EONET); events are indicative and keep their original source links.
  • Live: NASA EONET Events are indicative, not authority warnings.
  • Live: U.S. Geological Survey Events are indicative, not authority warnings.
  • NASA GIBS: We acknowledge the use of imagery provided by services from NASA's Global Imagery Browse Services (GIBS), part of NASA's Earth Science Data and Information System (ESDIS).
  • River discharge forecast, 30 days with range (GloFAS via Open-Meteo): Contains modified Copernicus Emergency Management Service information 2026; not a flood warning.
  • Weather data by Open-Meteo.com (https://open-meteo.com/), licensed under CC BY 4.0 (https://creativecommons.org/licenses/by/4.0/).
  • Optional layers (10 sources in the layer list: live, forecast, observed and context) print their provider credit on the map and here when switched on; forecasts are model output and derived indices are estimates.

Layers and dates

  • Flood water, 3-day composite: VIIRS Global Flood Product, NASA LANCE · 14 Oct 2026
  • Active fires and thermal anomalies: VIIRS NOAA-20 375 m (FIRMS), NASA LANCE FIRMS · 13 Oct 2026
  • Population density, 2020: Population: CIESIN, Columbia University, Gridded Population of the World v4.11 (2018), NASA SEDAC, CC BY 4.0 · static
  • Land surface temperature, day, 8-day composite: VIIRS NOAA-20 Level 3, 8-day, NASA LANCE · 14 Sep 2026
  • Night-time lights, daily: VIIRS Black Marble (VNP46A2), NASA LAADS DAAC · 12 Oct 2026
  • Aerosol optical depth, daily: VIIRS NOAA-20 Deep Blue AOD, NASA LANCE · 13 Oct 2026

03How learning runs

How learning runs, as a process you can run

Select a scenario and press Play: course, pathway, practice, faculty, cells and record.

04What is changing

Frontier course · L3 advanced, programme courses and standards

Catastrophe, exposure and vulnerability modelling: frontier methods

The methods, data, tools and studies that changed catastrophe, exposure and vulnerability modelling between 2024 and 2026, taught by reproducing them on open data.

Level
L3 Advanced
Study time
about 28 hours (planning estimate)
Status
Planned
Prerequisites
Catastrophe, exposure and vulnerability modelling: foundations and practice; Working knowledge of a scripting language (Python or R) for the labs

Why now

It illustrates how model-calculated losses, not field surveys, drive parametric settlement speed and basis risk. Caribbean Catastrophe Risk Insurance Facility, CCRIF to Make Payout to the Government of Panama Following Magnitude 7.7 Earthquake, 15 October 2026

Learning outcomes

  1. Explain what changed in catastrophe, exposure and vulnerability modelling since 2024 and cite the studies, data or rules behind each change
  2. Reproduce CCRIF earthquake model triggered a payout to Panama on open data and state the uncertainty of the result
  3. Evaluate a 2024 to 2026 study: its question, data, method, limits and what it changes for practice
  4. Design an analysis that combines a frontier method with the faculty's instruments, and justify each choice

Modules

  1. CCRIF earthquake model triggered a payout to Panama
    • After the magnitude 7.7 earthquake of 9 October 2026, CCRIF's SPHERA model estimated shaking up to 0.5 g in Panama; modelled government losses exceeded the attachment point, triggering a USD 17.4 million payout within 14 days.
    • It illustrates how model-calculated losses, not field surveys, drive parametric settlement speed and basis risk.
    • Caribbean Catastrophe Risk Insurance Facility, 15 October 2026
  2. The open catastrophe modelling platform completes its move to a single programming language
    • Oasis LMF 2.5.0 removed C++ ktools dependencies, supports only the ORD results format, adds combining results for portfolio analysis and fully supports OED version 5, with a two-yearly release cadence from 2026.
    • Open, standardised model tooling lowers barriers to transparent catastrophe modelling and model comparison.
    • Oasis Loss Modelling Framework, 10 February 2026
  3. CCRIF made a record USD 70.8 million payout to Jamaica
    • After Hurricane Melissa, CCRIF announced a USD 70.8 million tropical cyclone payout to Jamaica, the largest single payout in its history; a second payout brought the total to USD 91.9 million.
    • Parametric payouts test how well modelled hazard and loss triggers match real damage, a basis risk lesson.
    • Caribbean Catastrophe Risk Insurance Facility, 31 October 2025
  4. Myanmar M7.7 earthquake triggered a red PAGER alert
    • The magnitude 7.7 Mandalay earthquake of 28 March 2025 led the USGS PAGER system, which rapidly estimates fatalities and economic losses from shaking and exposure, to issue a red alert.
    • It is a reference case for testing rapid loss estimation and exposure data in a setting with sparse building inventories.
    • US Geological Survey, 28 March 2025
  5. Reproduction lab
    • Extend the discipline's method with one frontier method and compare its results
    • State the uncertainty and the limits of the result
    • Peer review against a shared checklist

Labs with Academy tools

Nexus Standards

Teaches

  • NRS-C3 Hazard, exposure, vulnerability and capacity data
  • NRS-F3 Insurance, catastrophe risk and protection gaps
  • NRS-M3 Method fabric: Exposure and asset intelligence
  • NRS-M4 Method fabric: Vulnerability, fragility and resilience
  • NRS-M5 Method fabric: Consequence and loss
  • NRS-M6 Method fabric: Catastrophe risk

Relies on

  • NS-1 The UNI and the artefact catalogue
  • NS-16 UNI application profile (how articles, documents, code, data, APIs and interfaces carry the UNI)
  • NRS-C1 Risk vocabulary and ontology
  • NRS-C2 Risk assessment method
  • NRS-C4 Risk data model, identifiers and exchange
  • NRS-C8 Evidence, uncertainty and provenance
  • NRS-C9 Risk models, methods and validation

Assessment

  • 50%Method reproductionReproduce one frontier method on open data and state the uncertainty of the result
  • 30%Study reviewA critical review of a 2024 to 2026 study: question, data, method, limits, what it changes
  • 20%Peer reviewReview two other learners' reproductions against a shared checklist

Delivery

  • Self-paced online, with the labs in the browser
  • Cohort study over six to eight weeks, with a weekly lab review
  • Co-delivered with a partner institution, inside its own courses

Partner on this course

  • Co-teach a module and bring a current case from your work
  • Host a cohort for your learners, with your own schedule and review
  • Contribute a lab: a dataset your institution publishes openly, or a model
  • Review the course content and its references before it opens
  • Translate the course and adapt its cases to your region

How institutions and experts take part

In the Academy LMS

Course on the learning platform
Expert, 5 topics
Cohort group
A community group for each cohort of learners
Achievement
Recorded on completion of the assessed work

Open now in this discipline

References

  1. Caribbean Catastrophe Risk Insurance Facility, CCRIF to Make Payout to the Government of Panama Following Magnitude 7.7 Earthquake, 15 October 2026
  2. Oasis Loss Modelling Framework, Oasis Insight Newsletter, February 2026, 10 February 2026
  3. Caribbean Catastrophe Risk Insurance Facility, CCRIF To Make Record US$70.8 Million (J$11.4 Billion) Payout to Jamaica Following the Devastation Caused by Hurricane Melissa, 31 October 2025
  4. US Geological Survey, M 7.7 – 2025 Mandalay, Burma (Myanmar) Earthquake, 28 March 2025
  5. Cornell, Engineering seismic risk analysis, Bulletin of the Seismological Society of America, 1968
  6. Porter, A beginner's guide to fragility, vulnerability, and risk, Encyclopedia of Earthquake Engineering, 2015
  7. Silva et al., Development of a global seismic risk model, Earthquake Spectra, 2020
05Take part

Take part in the work

Start from who you are.

06Questions

Questions, answers and key terms

Is the course free?
Yes. Every course and learning material of Risk Academy, led by the Nexus Consortium, is free to study, self-paced or with a cohort. Ordinary participation has no fee; paid work, internships and fellowships are separate arrangements.
What does completing a course give me?
A completion record: the course, its version, the date and what was assessed, private by default and shared by you. It stacks into discipline, department and programme achievements. A record states what was studied and assessed and does not certify competence; it is not a licence, a professional title or an employment status.
Where do the data and the places come from?
Every faculty teaches on a twin of a real place built from open data; each layer carries its provider, licence and date, and every result on the Academy states its source. Maps and figures are indicators for teaching, never an assessment of a place.
How do I take part beyond the course?
Form a competence cell of three to seven people, study a shared pathway, take a supervised assignment in the National Working Groups, or bring a cohort from your institution. For organisations.

Key terms

Term

Exposure

The people, assets and activities located where hazards can affect them.

Term

Fragility curve

A function giving the probability of reaching a damage state for a given hazard intensity.

Term

Event set

A large collection of simulated events that represents possible hazard occurrences.

Term

Exceedance probability curve

A curve showing the probability that losses exceed each level.

ReportsContribute

Contribute evidence from this page.

Reports is the Consortium's quarterly publication. What you know about this subject can become evidence, a case or a correction in the next edition, credited to you and published under CC BY 4.0 where it is your own work.

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