Illustrative: a joint probability density whose dependence shifts over time

Risk Academy, led by the Nexus Consortium · Course catalogue · Hazards, Disasters and Resilience

Disaster Risk Reduction and Early Warning

Multi-hazard and compound risk assessment

Multi-hazard and compound risk assessment, 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

Multi-hazard and compound risk assessment: foundations and practice

This area covers hazards that occur together, in sequence or by triggering one another, and the risk assessment methods that treat them jointly rather than one at a time.

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

Why now

The Sendai Framework midterm review (2023) and the 2025 update of the UNDRR and ISC Hazard Information Profiles move practice from single-hazard to multi-hazard assessment, and compound events (heat with drought, surge with rain) are now a named class in IPCC AR6. Nature Climate Change, Future climate risk from compound events (Zscheischler et al.), 2018

Learning outcomes

  1. Define compound event and the other key terms of the discipline and use them correctly in a written case
  2. Explain hazard interactions: triggering, amplification and coincidence and compound events and joint probabilities 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 consecutive disasters and changing vulnerability, stating evidence, date and limits

Modules

  1. Hazard interactions: triggering, amplification and coincidence
    • Hazard interactions: triggering, amplification and coincidence
    • Compound events and joint probabilities
    • Consecutive disasters and changing vulnerability
  2. Cascading impacts across exposed systems
    • Cascading impacts across exposed systems
    • The UNDRR and ISC Hazard Information Profiles
    • Multi-hazard risk indices and maps
  3. Dependence modelling with copulas
    • Dependence modelling with copulas
    • Natech events and technological cascades
    • Multi-hazard early warning
  4. Lab: the discipline's method
    • Each driver has its own exceedance probability; a dependence measure fitted to concurrent records sets a copula; the copula gives the chance that both exceed their thresholds in the same event, which under dependence can be ten times the product of the margins, and the design standard has to be set on that joint number.
    • Work the method through a documented case and explain each result
    • Read the method's sources and stated values

Labs with Academy tools

Open data

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

References

  1. Wahl, Jain, Bender, Meyers and Luther, Increasing risk of compound flooding from storm surge and rainfall for major US cities, 2015
  2. Zscheischler et al., Future climate risk from compound events, 2018
  3. Nelsen, An Introduction to Copulas, 2006
02Live map

Climate signals in Canada

Surface heat, rain, snow, sea ice, marine heat and water storage, each a dated satellite or model product, over Canada.

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

Layers 2

Climate signals

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.

Climate signals, framed on Canada.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 EONETSources 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
  • GPM IMERG precipitation, NASA Precipitation Processing System; distributed by the NASA Goddard Earth Sciences Data and Information Services Center (GES DISC); imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into H3 cells where shown (modified). NASA open data
  • GHRSST Level 4 MUR analyses, NASA Jet Propulsion Laboratory; distributed by the NASA Physical Oceanography DAAC (PO.DAAC); imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into H3 cells where shown (modified). NASA open data
  • GRACE and GRACE-FO JPL mascon solution, NASA Jet Propulsion Laboratory; distributed by the NASA Physical Oceanography DAAC (PO.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.
  • 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).
  • Air quality forecast, 5 days, PM2.5 (CAMS via Open-Meteo): Contains modified Copernicus Atmosphere Monitoring Service information 2026.
  • Past year, daily temperature (ERA5 via Open-Meteo): Contains modified Copernicus Climate Change Service information 2026.
  • Past year, daily temperature and sunshine (NASA POWER): These data were obtained from the NASA Langley Research Center (LaRC) POWER Project funded through the NASA Earth Science/Applied Science Program..
  • 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 (21 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

  • Land surface temperature, day, 8-day composite: VIIRS NOAA-20 Level 3, 8-day, NASA LANCE · 14 Sep 2026
  • Precipitation rate, daily mean: GPM IMERG, NASA GES DISC · 12 Oct 2026
  • Snow cover: VIIRS NOAA-20 NDSI, NASA LANCE · 13 Oct 2026
  • Sea ice concentration: GHRSST MUR, NASA JPL PO.DAAC · 12 Oct 2026
  • Sea surface temperature anomaly: GHRSST MUR25, NASA JPL PO.DAAC · 12 Oct 2026
  • Water storage anomaly, monthly: GRACE-FO JPL mascons, NASA JPL PO.DAAC · July 2022

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

What is changing, with standards and evidence

Multi-hazard and compound risk assessment: frontier methods

The methods, data, tools and studies that changed multi-hazard and compound risk assessment between 2024 and 2026, taught by reproducing them on open data.

Level
L3 Advanced
Study time
about 28 hours (planning estimate)
Status
Planned
Prerequisites
Multi-hazard and compound risk assessment: foundations and practice; Working knowledge of a scripting language (Python or R) for the labs

Why now

The Sendai Framework midterm review (2023) and the 2025 update of the UNDRR and ISC Hazard Information Profiles move practice from single-hazard to multi-hazard assessment, and compound events (heat with drought, surge with rain) are now a named class in IPCC AR6. Nature Climate Change, Future climate risk from compound events (Zscheischler et al.), 2018

Learning outcomes

  1. Explain what changed in multi-hazard and compound risk assessment since 2024 and cite the studies, data or rules behind each change
  2. Reproduce hazard interactions 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. Hazard interactions
    • Triggering, amplification and concurrence
    • The Hazard Information Profiles as a shared vocabulary
    • Interaction matrices and networks
  2. Compound event statistics
    • Copulas and multivariate return periods
    • Storylines and event sets
    • Dependence under climate change
  3. Dynamic vulnerability
    • Damage accumulation across successive events
    • Recovery state as a risk driver
    • Multi-risk indicators and their limits
  4. 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
  5. Technology that helps and the risks it carries
    • Drones, Earth observation, machine learning forecasting and cell broadcast warnings.
    • Telecom and positioning failure, and AI-generated misinformation in a crisis.

Labs with Academy tools

Open data

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

References

  1. Nature Climate Change, Future climate risk from compound events (Zscheischler et al.), 2018
  2. UNDRR, Sendai Framework for Disaster Risk Reduction 2015 to 2030, 2015
  3. UNDRR and ISC, Hazard Information Profiles, 2025 to check
  4. Wahl, Jain, Bender, Meyers and Luther, Increasing risk of compound flooding from storm surge and rainfall for major US cities, 2015
  5. Nelsen, An Introduction to Copulas, 2006
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

Compound event

A combination of drivers or hazards, simultaneous or successive, whose joint occurrence produces an impact larger than each alone.

Term

Hazard interaction

A relationship in which one hazard triggers, amplifies or coincides with another.

Term

Joint return period

The average interval between events in which two variables both exceed their thresholds, which depends on their dependence.

Term

Consecutive disasters

Disasters that strike before recovery from an earlier one is complete, so vulnerability has changed.

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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