GCRI · Disaster Resilience and Recovery
Anticipatory action
Anticipatory action releases pre-agreed actions and pre-arranged money when a forecast crosses a trigger, before a hazard reaches its peak impact. Cash before a flood, livestock feed before a drought or evacuation support before a cyclone can reduce losses that response arrives too late to prevent. This page sets out how triggers, actions and financing fit together, how they are evaluated, and what evidence serves those who design and fund them.
Anticipatory action on the record.
Anticipatory action: how the risk develops.
Triggers, lead times and action limits. The dossier below sets out how the risk develops, what is measured, where the data come from, how it is modelled and who decides.
Forecasts set the trigger
A trigger links a forecast threshold, such as a probability of river levels exceeding a mark within days, to a decision to act. Its design trades missed events against acting when nothing happens.
Money must be ready
Funds released only after appeals and approvals arrive too late. Pre-arranged financing, from contingency funds to insurance, lets action start when the trigger is reached.
Actions are agreed in advance
Who receives what, through which channels and by when is decided before the season. Delivery systems such as social protection registries let assistance move quickly.
Learning from every activation
Each activation, and each missed event, tests the trigger and the actions. Evaluations compare outcomes with what would otherwise have happened and adjust the design.
Hazards now in the Philippines.
Flood water, population density, 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
Hazards now, for this page
Keyboard, with the map focused
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Latest available
NASA GIBS / EOSDIS · ASTER GDEM (METI, NASA) · Blue Marble (NASA) · © OpenStreetMap contributors (ODbL) · Natural Earth
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Hazards now, 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 · U.S. Geological Survey · 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
- 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
- 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
- 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
- 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 hexagonal cells where shown (modified). NASA open data
- MODIS land products (vegetation indices, gross primary production, land cover), NASA LP DAAC and LANCE; 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.
- Live: U.S. Geological Survey 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).
- 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 (20 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
- Population density, 2020: Population: CIESIN, Columbia University, Gridded Population of the World v4.11 (2018), NASA SEDAC, CC BY 4.0 · static
- Precipitation rate, daily mean: GPM IMERG, NASA GES DISC · 12 Oct 2026
- True colour: VIIRS NOAA-20 corrected reflectance, NASA LANCE · 13 Oct 2026
- Active fires and thermal anomalies: VIIRS NOAA-20 375 m (FIRMS), NASA LANCE FIRMS · 13 Oct 2026
- Land cover type (IGBP), yearly: MODIS Terra and Aqua land cover (MCD12Q1), NASA LP DAAC · 2024
Anticipatory action triggers sit on forecasts from several domains.
- WaterCouplingFlood and drought forecasts are the commonest triggers.What to watchTrigger skill: hits, misses and false alarms
- FoodCouplingPre-agreed food and cash assistance protects livelihoods before a shock peaks.What to watchTiming of assistance against impact
- HealthCouplingOutbreak triggers are emerging, with less forecast skill.What to watchTrigger evaluation records
Trigger evaluations are designed for the Methods and Technical series. OCHA's anticipatory action frameworks and the CERF anticipatory window define the practice; triggers never release funds automatically on these pages, and the owning agencies decide.
- Trigger verification against observed impacts.
- Evaluations of past anticipatory actions.
Hazard to loss: the exceedance curve.
How often a given loss is exceeded, from a Gumbel hazard, a lognormal fragility and a protection standard; the area under the curve is the average annual loss. Teaching model with stated illustrative values, not a prediction. The map on this page shows The Philippines; the model itself is not tied to a place.
Controls
- Typical annual hazard intensity (location)
- 1.00 intensity index
- Spread of extremes (scale)
- 0.80 intensity index
- Intensity at which half the value is lost
- 4.00 intensity index
- Dispersion of vulnerability
- 0.55
- Share of value in the hazard footprint
- 40%
- Protection standard (return period)
- 50 years
Readouts
- Average annual loss
- 0.51% of value
- Loss at 1 in 100 years
- 24.5% of value
- Loss at 1 in 250 years
- 28.4% of value
- Intensity at 1 in 100 years
- 4.68 intensity index
Numbers, methods and sources
| Return period (years) | Intensity (intensity index) | Loss (% of value) |
|---|---|---|
| 1 | 0.09 | 0.00 |
| 2 | 1.27 | 0.00 |
| 4 | 1.91 | 0.00 |
| 7 | 2.47 | 0.00 |
| 13 | 3.00 | 0.00 |
| 24 | 3.51 | 0.00 |
| 44 | 4.02 | 0.00 |
| 82 | 4.53 | 23.55 |
| 154 | 5.03 | 26.44 |
| 287 | 5.53 | 28.87 |
| 536 | 6.03 | 30.88 |
| 1,000 | 6.53 | 32.53 |
Methods
- Gumbel extreme-value hazard Gumbel (1958), Statistics of Extremes, Columbia University Press
- Lognormal fragility (vulnerability) FEMA (2003), HAZUS-MH Technical Manual
- Exceedance-probability curve and average annual loss Grossi and Kunreuther (2005), Catastrophe Modeling, Springer
- Levee effect Di Baldassarre and others (2013), Socio-hydrology, HESS 17
- Uncertainty fan (parameter Monte Carlo) Spiegelhalter, Pearson and Short (2011), Visualising uncertainty about the future, Science 333
- One-at-a-time sensitivity (tornado) Saltelli and others (2008), Global Sensitivity Analysis: The Primer, Wiley
Data
The model runs on the teaching values set by the controls. To calibrate it for a place, read it against these admitted layers and series, which this page's map can draw:
- Rivers Natural Earth
- Urban extents Natural Earth
- Cities Natural Earth
- Earthquakes M4.5+, past week (USGS) U.S. Geological Survey · register usgs.earthquake.summary-feeds
- Rain rate, last half hour (IMERG) NASA GPM IMERG Early · register nasa.gibs.context-live-layers
- River discharge forecast, 30 days with range (GloFAS via Open-Meteo) Open-Meteo.com (CC BY 4.0), Copernicus GloFAS · register open-meteo.public-pages
- Built-up and settlement extent, 2010 (HBASE, Landsat) CIESIN/Columbia, NASA SEDAC HBASE · register sedac.context-urban-layers
Across the six pillars, led by Nexus Consortium
- Experiments Labs
- Built in Disaster Resilience and Recovery in Foundry
- Tested at Disaster Resilience and Recovery in Universe
- Codified in Hazards and Disaster Risk Reduction in Standards
- Published in Disaster Resilience and Recovery in Reports
- Taught in Faculty of Hazards, Disasters and Resilience in Academy
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 |
|---|---|---|---|---|
| Anticipatory action frameworks in place | count by country and hazard | annual | Anticipation Hub and agency records | REPORTED |
| Trigger hit rate | percent of hazard events preceded by a trigger | per season | Trigger verification | OBSERVED |
| False activation rate | percent of activations without the hazard | per season | Trigger verification | OBSERVED |
| Time from trigger to assistance | days | per activation | Activation records | OBSERVED |
| People reached before peak impact | count | per activation | Distribution records | REPORTED |
| Pre-arranged financing available | amount by instrument | annual | Fund and policy records | DECLARED |
Model anticipatory action as a system. Run the cascade.
Assembled from the Nexus Standards area profile Early warning and anticipatory action: 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
- Ice-jam flood
- Tropical cyclone
- Heatwave
- HIV epidemic
- Storm surge (set off downstream)
- Intense rainfall (set off downstream)
- River flood (set off downstream)
- Flash flood (set off downstream)
- Dangerous surf (set off downstream)
- Widespread power outage (set off downstream)
- Mass displacement (set off downstream)
- Coastal flood (set off downstream)
- Extreme fire weather (set off downstream)
- Wildfire (set off downstream)
- Heat-driven grid stress (set off downstream)
- Agricultural drought (set off downstream)
- Flash drought (set off downstream)
- Snow drought (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-10Policies and clauses (machine-readable obligations: definition, binding, evaluation and enforcement)NS-11Verification and monitoring (evidence, attestations, zero-trust conformance observation)NRS-C7Early warning, triggers and anticipatory actionNRS-S9System profile: NXS-AAP (Anticipatory action and triggers)NRS-H117Hazard family: Social cohesion and atrocity risk (NHS-1 soc.cohesion)NRS-H83Hazard family: Health system capacity failure (NHS-1 health.system)NRS-H98Hazard family: Agentic AI acting at scale (NHS-1 tech.ai-agentic)NRS-H22Hazard family: Solar-terrestrial storms (NHS-1 space.solar-storm)
Observation
- NWS API active alerts (CAP 1.2 as GeoJSON) (listed for reference)
- GloFAS global flood forecasts and reanalysis (listed for reference)
- ECMWF open data (IFS and AIFS real-time forecasts) (listed for reference)
- CHIRPS quasi-global gridded precipitation (listed for reference)
- Number of countries that have multi-hazard early warning systems
- Number of countries that have multi-hazard monitoring and forecasting systems
- Number of people per 100,000 covered by early warning information through local governments or national dissemination mechanisms
- Number of countries with accessible, understandable, usable and relevant disaster risk information and assessment
Example geography
- Southeast Asia: 51 hexagonal cells
- Surface water through cloud, 30 m (OPERA DSWx-S1 radar), NASA GIBS
- Rain rate, last half hour (IMERG), NASA GIBS
- Surface air temperature, daytime (AIRS), NASA GIBS
- Night lights tonight, outages (VIIRS Day/Night Band), 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 |
|---|---|---|
| Anticipation Hub (German Red Cross, IFRC and Red Cross Red Crescent Climate Centre) | Map and documentation of anticipatory action frameworks and evidence | Public, terms to check |
| UN OCHA anticipatory action framework documents | Triggers, actions and financing of OCHA-facilitated pilots | Public, UN terms of use |
| IFRC DREF anticipatory pillar and early action protocols | Approved early action protocols and activations | Public, IFRC terms (to check) |
| Global Flood Awareness System and other forecast archives | Forecasts for trigger design and verification | Free, Copernicus terms |
| Start Network Start Ready and Start Fund records | Risk pool and anticipation alerts from NGOs | Public summaries, terms to check |
How anticipatory action 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 anticipatory action 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 |
|---|---|---|
| Humanitarian agencies and Red Cross Red Crescent societies | Which hazards and thresholds to use as triggers | Trigger design studies; forecast verification |
| Ministries of social protection | Whether to extend social protection systems to deliver anticipatory cash | Delivery readiness reviews; evaluation evidence |
| Ministries of finance and donors | How much pre-arranged financing to commit and through which instruments | Financing maps; activation costs and timing |
Outputs this topic produces
- Trigger design studies balancing hits, misses and false activations
- Evaluation designs comparing anticipatory and post-event assistance
- Delivery readiness reviews for social protection channels
- Financing maps linking instruments to triggers
- Which actions reduce impact if taken before a hazard, and how much lead time do they need?
- How are triggers set, and how is the trade-off between acting in vain and failing to act handled?
- Do early actions reach the people most at risk, and with what effect compared with later response?
- How should plans deal with forecasts that change, or hazards that arrive earlier than expected?
- Which hazards suit anticipatory action, and which do not?
Acting in the window between forecast and impact.
Some hazards give usable warning: floods on large rivers, tropical cyclones, droughts and heatwaves can be forecast days to months ahead. Others, such as earthquakes, give almost none. Where lead time exists, actions such as moving livestock, harvesting early, reinforcing shelters, prepositioning supplies or providing cash can reduce losses that would otherwise require costlier response later.
Anticipatory action depends on decisions made in advance. A trigger links a forecast threshold to a pre-agreed action and pre-arranged funding, so that action does not wait for negotiation. Because forecasts are probabilistic, any trigger will sometimes activate when the hazard does not materialise and sometimes miss events. Good design states those trade-offs openly and accepts that some activations will be in vain.
How the evidence is built, and where it stops.
- 01
Trigger design
Linking forecast probabilities to thresholds with forecasting and decision analysis. Historical data to test triggers is often short.
- 02
Impact evaluation
Comparing outcomes for those reached early with similar groups, with social and behavioural science. Ethical and practical limits constrain control groups.
- 03
Lead-time analysis
Matching the time each action needs to the warning available. Operational delays often consume the window.
- 04
Scenario exercises
Testing plans before they are needed. See multi-hazard exercises.
How it is studied, and what the methods cannot say.
- 01Forecasting and time-series analysisTrigger verification · Flood forecast lead time · Seasonal outlooks for drought preparednessApplied here
- 02Decision analysis under uncertaintyCost-benefit of risk reduction · Acting on forecasts · Recovery prioritisationApplied here
- 03Optimisation and operations researchPrepositioning relief supplies · Evacuation and shelter planning · Restoration sequencingApplied here
- 04Hydrology and water scienceFlood risk mapping for planning · Thresholds for anticipatory actionApplied 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 anticipatory action?
What is a trigger?
What happens if the hazard does not arrive?
Is anticipatory action the same as early warning?
Does the platform release funds or set triggers?
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