GCRI · Disaster Resilience and Recovery
Multi hazard exercises
Exercises test plans, people and systems before a real disaster does. They range from discussion-based tabletop exercises to functional exercises and full-scale drills, and increasingly combine hazards, sectors and borders. This page sets out how exercises are designed, run and evaluated, why lessons are often identified but not learned, and what evidence serves the authorities that commission and run them.
Multi hazard exercises on the record.
Multi hazard exercises: how the risk develops.
Scenario design and learning. The dossier below sets out how the risk develops, what is measured, where the data come from, how it is modelled and who decides.
The scenario sets the test
An exercise tests only what its scenario stresses. Scenarios built around familiar single hazards leave untested the compound and cascading events that cause the greatest difficulty.
Discussion reveals assumptions
Tabletop exercises surface assumptions about roles, resources and timing that differ between agencies. Many problems appear before any resource moves.
Functional tests reveal limits
Functional and full-scale exercises move information, people and equipment, exposing bottlenecks in communication, logistics and decision-making that discussion misses.
Lessons must change practice
After-action reviews identify improvements, but lessons are learned only when plans, training and resources change. Without tracking, the same findings recur in the next exercise.
Climate signals in the Philippines.
Population density, daytime surface heat, rain and true-colour imagery over the Philippines, from NASA GIBS. Each layer carries its own date.
The interactive map needs JavaScript; the layer list and sources are below.
Layers 4
Climate signals, for this page
Keyboard, with the map focused
Hold Ctrl or ⌘ and scroll to zoom
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 the Philippines.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 · NASA HLS S30Sources 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 hexagonal 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 hexagonal 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 hexagonal cells where shown (modified). doi:10.7927/H49C6VHW. CC BY 4.0
- 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 hexagonal 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 hexagonal 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 hexagonal 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 hexagonal 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 hexagonal cells where shown (modified). ODbL
- Blue Marble, NASA Earth Observatory; imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into hexagonal 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.
- 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.
- Observed (EO): NASA HLS S30 (contains modified Copernicus Sentinel data 2026). 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).
- 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 (22 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
- 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
- Precipitation rate, daily mean: GPM IMERG, NASA GES DISC · 12 Oct 2026
- True colour: VIIRS NOAA-20 corrected reflectance, NASA LANCE · 13 Oct 2026
- Sea surface temperature anomaly: GHRSST MUR25, NASA JPL PO.DAAC · 12 Oct 2026
- Flood water, 3-day composite: VIIRS Global Flood Product, NASA LANCE · 14 Oct 2026
Exercises are where cross-domain plans meet reality.
- EnergyCouplingBlackout scenarios test water, health and communications together.What to watchDependencies exposed in exercises
- HealthCouplingMass-casualty and outbreak exercises test surge and supply.What to watchSurge activation times
- WaterCouplingUtility exercises test alternative supply and communication.What to watchTime to alternative supply
Exercise findings are designed for the Universe Annual Synthesis. Design and evaluation draw on established exercise doctrine; results and dissent are kept in after-action records under NS-11 of the proposed Nexus Standards, and simulated messages never reach the public.
- After-action reviews a public body publishes.
- Exercise designs for compound scenarios.
Anticipatory action console.
The screen a team would use to follow this subject: its measures, states and decisions. Names are examples and values are illustrative.
Anticipatory action console
Multi hazard exercises · Province C · Monsoon season
Protocol
- Readinessforecast lead 10 d
- Activationlead 3 d
- Early actions72 h window
- Responseif event
- Learningreview
River forecast at trigger gauge
Pre-agreed actions
| Cash to at-risk households | 72 h | 44 | Yes |
| Livestock evacuation | 48 h | 19 | Partial |
| Shelter kits | 72 h | 23 | Yes |
What is measured, and how well.
Each indicator carries its unit, its cadence, the kind of source behind it and the evidence label a value would carry. No values are shown: a programme supplies them under its own authority.
| Indicator | Unit | Cadence | Source type | Label |
|---|---|---|---|---|
| Exercises held | count by type and hazard | annual | Exercise programme records | REPORTED |
| Multi-agency participation | count of organisations taking part | per exercise | Exercise records | REPORTED |
| Exercise objectives met | percent of objectives | per exercise | Evaluation reports | REPORTED |
| Improvement actions completed | percent of actions closed on time | quarterly | Action tracking | REPORTED |
| Repeat findings | count of findings recorded in earlier exercises | per exercise | After-action reviews | REPORTED |
| Exercises with compound or cascading scenarios | percent of exercises | annual | Exercise programme records | REPORTED |
Model multi hazard exercises as a system. Run the cascade.
Assembled from the Nexus Standards area profile Compound and cascading hazard standards: the hazards it names, the systems and sectors that carry the loss, the controls that dampen it and the data that observe it. Choose the components, pick an initiating hazard and step through the cascade. The Map view places the run on an example geography with open data. Every coupling weight is a stated assumption you can change. A teaching model, not a forecast, an assessment or a certification. To model a place of your own choosing, open the full System Builder.
Hazards
- Natech event
- Chemical spill or leak (set off downstream)
- Emergency-response overload (set off downstream)
- Toxic gas release (set off downstream)
- Industrial fire (set off downstream)
Systems and couplings
Controls
NS-0Constitution and principlesNS-3Risk record UNIs (grammar, legacy crosswalk, allocation authority)NS-9Contextual UNIs (deployments, instances, programme instances)NS-11Verification and monitoring (evidence, attestations, zero-trust conformance observation)NRS-H61Hazard family: Cascading failure (NHS-1 sys.cascade)NRS-H62Hazard family: Compound and multi-hazard events (NHS-1 sys.compound)NRS-H60Hazard family: Supply-chain and flow disruption (NHS-1 sys.supply-chain)NRS-H94Hazard family: Systemic cyber events (NHS-1 cyber.systemic-cyber)NRS-H107Hazard family: Digital infrastructure concentration and monoculture (NHS-1 tech.digital-concentration)NRS-H7Hazard family: Large-scale circulation anomalies (NHS-1 atmo.climate-mode)
Observation
- Copernicus EMS rapid mapping activations (listed for reference)
- OpenStreetMap planet and replication (listed for reference)
- ERA5 reanalysis (Copernicus Climate Data Store) (listed for reference)
- Direct economic loss attributed to disasters in relation to global GDP
- Number of disruptions to basic services attributed to disasters
Example geography
- Bangladesh: 134 hexagonal cells
- Night lights tonight, outages (VIIRS Day/Night Band), NASA GIBS
- Carbon monoxide, smoke transport (AIRS), NASA GIBS
- Vegetation disturbance alerts, 30 m (OPERA DIST-ALERT), NASA GIBS
Where the evidence comes from.
Named public datasets and institutional records, each with its licence class. Sources by agreement are used only under their terms and never republished.
| Source | What it gives | Licence class |
|---|---|---|
| UNDRR guidance on scenario-based exercises | Design guidance for preparedness exercises | Public, UN terms of use |
| WHO simulation exercise manual | Methods for planning, conducting and evaluating simulation exercises | Public, WHO terms of use |
| US Homeland Security Exercise and Evaluation Program (HSEEP) | Exercise design and evaluation doctrine | Public domain, US government |
| EU Civil Protection Mechanism exercise reports | Multinational exercise programmes and lessons | Public, EU terms of use |
| INSARAG guidelines and exercises | International urban search and rescue standards and exercise practice | Public, UN terms of use |
How multi hazard exercises is modelled, measured and tested.
The model, its assumptions, its data and its uncertainty, in the form a scientist or engineer would check. Structures follow published methods. The values drawn are illustrative, not findings.
Uncertainty bands
How far the outlook for multi hazard exercises could spread, shown as ranges rather than a single line.
- Central estimate
- median of the ensemble
- Ranges
- likely and very likely, in IPCC calibrated language
- Ensemble
- members, scenarios and initial conditions stated
- Read with
- the sensitivity of the result to each input
Who decides, and what the evidence serves.
Disaster Resilience and Recovery prepares evidence. The decisions below are taken by the authorities named, under their own rules, and never by the platform.
| Who decides | The question | Evidence this page serves |
|---|---|---|
| National disaster management authorities | Which scenarios and agencies the exercise programme should cover | Programme records; repeat findings |
| Exercise sponsors in ministries and agencies | Which objectives an exercise must test | Evaluation frameworks; previous findings |
| Heads of participating organisations | Which improvement actions to fund and when | After-action reviews; action tracking |
Outputs this topic produces
- Exercise designs for compound and cascading scenarios
- Evaluation frameworks with objectives and observable criteria
- Lesson tracking templates linked to plans and training
- Exercise reports prepared for the commissioning authority
What experts ask.
Exercise designers and evaluators work on a demanding set of questions.
- What should an exercise test: plans, people, systems, decisions or coordination?
- How realistic must a scenario be, and how can it include cascading and compound effects?
- Who should take part, including operators, local governments and communities?
- How are performance and lessons recorded objectively?
- How are lessons turned into changed plans, and how is that change verified?
Why exercises reveal what plans hide.
Plans describe intended behaviour; exercises show actual behaviour. Discussion-based exercises walk participants through a scenario and expose gaps in understanding and authority. Functional and full-scale exercises test systems and people under time pressure. Multi-hazard scenarios, such as a flood that cuts power during a heatwave, reveal dependencies between agencies and infrastructure that are invisible when each plans alone.
The value of an exercise lies in what changes afterwards. Lessons identified are not lessons learned until plans, training or resources change and the change is tested again. Exercise programmes that focus on demonstration rather than discovery, or that avoid exposing failures, produce reassurance without improvement.
How the evidence is built, and where it stops.
- 01
Scenario design
Building plausible, challenging scenarios with decision analysis and hazard science from Earth and geophysical science and hydrology. Scenarios can be anchored too closely on past events.
- 02
Observation and evaluation
Trained evaluators record decisions and timing against objectives. Observer bias and participant awareness affect results.
- 03
After-action review
Structured debriefs that identify causes, not blame. Candour depends on a safe environment.
- 04
Improvement tracking
Recording lessons and verifying implementation. Tracking often lapses between exercises.
How it is studied, and what the methods cannot say.
- 01Decision analysis under uncertaintyCost-benefit of risk reduction · Acting on forecasts · Recovery prioritisationApplied here
- 02Social and behavioural scienceWarning response surveys · Participatory risk assessment · Social vulnerability analysisApplied here
- 03Forecasting and time-series analysisTrigger verification · Flood forecast lead time · Seasonal outlooks for drought preparednessApplied here
- 04Earth and geophysical scienceEarthquake scenarios for exercises · Landslide hazard in recovery planningApplied here
Where this page's references lead.
The bodies and documents this page is read against. Status and editions change; each link goes to the issuing body.
Questions and answers.
What is a tabletop exercise?
What is the difference between a functional and a full-scale exercise?
Why do the same lessons recur?
What is the difference between a tabletop and a full-scale exercise?
Will the platform run exercises?
Are exercise results published?
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