GCRI · Science and methods
Early warning research
A warning works only if the hazard is detected, the forecast is good enough, the message arrives in time and people know what to do. Each link can fail. The last mile, from warning to action, fails most often. The Global Centre for Risk and Innovation (GCRI) studies warning science, forecast verification and communication, in support of the authorities that alone issue warnings. Part of science and methods.
01Register
Early warning research on the record.
The Global Centre for Risk and Innovation
- 01InstitutionThe Global Centre for Risk and Innovation (GCRI)
- 02The warning chainFour links, each a place to fail
- 03Forecast verificationThe scores used to judge a forecast or a warning, and what each rewards
- 04The global frame in 2026Early Warnings for All, and what the monitoring shows
- 05GCRI’s partResearch and capability for the agencies that hold the warning mandate
- 06Research questionsWhat GCRI studies
- 07Public authorityOnly authorised agencies issue warnings
02The warning chain
Four links, each a place to fail.
- 01
Risk knowledge
Knowing which hazards threaten whom, and how badly.
- 02
Detection and forecasting
Observation and forecasts with verified skill, using forecasting and time-series analysis and Earth observation.
- 03
Dissemination
Messages that reach everyone at risk, in languages and formats they can use, including people with disabilities.
- 04
Response capability
People who understand the warning, trust it and can act on it.
03Geography
Hazards now worldwide.
Flood water, active fires and rain across the world, from NASA GIBS. Each layer carries its own date.
The interactive map needs JavaScript; the layer list and sources are below.
Layers 3
Hazards now, for this page
About this layer
- Evidence
- Observed (clouds leave gaps)
- Source
- VIIRS Global Flood Product (NASA LANCE)
- Provider
- NASA LANCE
- Licence
- NASA open data
- Vintage
- daily; Satellite detection; clouds leave gaps
- Newest at build
- 2026-10-14
- Resolution
- about 250 m grid
- Uncertainty
- Satellite detection; clouds leave gaps. Satellite or model raster as the provider publishes it. Clouds, swath gaps and retrieval error leave gaps and noise; values are indicators, not measurements at a place.
- Reached through
- gibs.earthdata.nasa.gov, only after you allow the live map
About this layer
- Evidence
- Observed (clouds and overpass timing leave gaps)
- Source
- VIIRS NOAA-20 375 m (FIRMS) (NASA LANCE FIRMS)
- Provider
- NASA LANCE FIRMS
- Licence
- NASA open data
- Vintage
- daily; Satellite detection; clouds and overpass timing leave gaps
- Newest at build
- 2026-10-13
- Resolution
- about 500 m grid
- Uncertainty
- Satellite hot-spot detections for the day shown, including gas flares and industrial heat; not a confirmed fire, an incident report or a warning.
- Reached through
- gibs.earthdata.nasa.gov, only after you allow the live map
About this layer
- Evidence
- Estimated
- Source
- GPM IMERG (NASA GES DISC)
- Provider
- NASA GES DISC
- Licence
- NASA open data
- Vintage
- daily; Satellite estimate, near real time
- Newest at build
- 2026-10-12
- Resolution
- about 2 km grid
- Uncertainty
- Satellite estimate, near real time. Satellite or model raster as the provider publishes it. Clouds, swath gaps and retrieval error leave gaps and noise; values are indicators, not measurements at a place.
- Reached through
- gibs.earthdata.nasa.gov, only after you allow the live map
About this layer
- Evidence
- Observed
- Source
- VIIRS NOAA-20 corrected reflectance (NASA LANCE)
- Provider
- NASA LANCE
- Licence
- NASA open data
- Vintage
- daily; Satellite image
- Newest at build
- 2026-10-14
- Resolution
- about 250 m grid
- Uncertainty
- Satellite image. Satellite or model raster as the provider publishes it. Clouds, swath gaps and retrieval error leave gaps and noise; values are indicators, not measurements at a place.
- Reached through
- gibs.earthdata.nasa.gov, only after you allow the live map
About this layer
- Evidence
- Estimated
- Source
- Gridded Population of the World v4.11 (NASA SEDAC (CIESIN, Columbia University))
- Provider
- NASA SEDAC (CIESIN, Columbia University)
- Licence
- CC BY 4.0
- Vintage
- null; Census-based estimate, static (2020)
- Resolution
- about 1 km grid
- Uncertainty
- Census-based estimate of people per square kilometre in 2020, shown as exposure context; not a count of people affected by any hazard.
- Reached through
- gibs.earthdata.nasa.gov, only after you allow the live map
About this layer
- Evidence
- Modelled (latest year GIBS publishes)
- Source
- MODIS Terra and Aqua land cover (MCD12Q1) (NASA LP DAAC)
- Provider
- NASA LP DAAC
- Licence
- NASA open data
- Vintage
- yearly; Satellite classification; latest year GIBS publishes
- Newest at build
- 2024-01-01
- Resolution
- about 500 m grid
- Uncertainty
- Satellite land cover classes for the year shown, including croplands; a classification with known errors, not a farm register.
- Reached through
- gibs.earthdata.nasa.gov, only after you allow the live map
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.
Hazards now, framed on the world.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 JPL OPERA DIST-ALERTSources 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
- 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
- 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
- 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
- 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 JPL OPERA DIST-ALERT (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
- Active fires and thermal anomalies: VIIRS NOAA-20 375 m (FIRMS), NASA LANCE FIRMS · 13 Oct 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
- Population density, 2020: Population: CIESIN, Columbia University, Gridded Population of the World v4.11 (2018), NASA SEDAC, CC BY 4.0 · static
- Land cover type (IGBP), yearly: MODIS Terra and Aqua land cover (MCD12Q1), NASA LP DAAC · 2024
04Forecast verification
The scores used to judge a forecast or a warning, and what each rewards.
| Score | What it measures | Range and reading |
|---|---|---|
| Probability of detection (hit rate) | Share of observed events that were warned | Zero to one; higher is better |
| False alarm ratio | Share of warnings not followed by the event | Zero to one; lower is better, and trust erodes as it rises |
| Brier score | Mean squared error of probability forecasts for a binary event | Zero to one; lower is better; decomposes into reliability, resolution and uncertainty |
| Continuous ranked probability score | Error of a whole forecast distribution against the outcome | In the units of the variable; lower is better; a proper score (Gneiting and Raftery, 2007) |
| Lead time | Time between warning and impact | Hours or days; must be long enough for the action it is meant to trigger |
A score is only meaningful against a reference, such as climatology or persistence, and over enough events to be stable. Rare extremes rarely give that, which is why verification of high-impact warnings is reported with wide uncertainty.
05The global frame in 2026
Early Warnings for All, and what the monitoring shows.
The UN Secretary-General’s Early Warnings for All initiative, with its Executive Action Plan for 2023 to 2027, aims for everyone on Earth to be protected by early warning systems by the end of 2027. It is organised around the four pillars of risk knowledge, detection and forecasting, warning dissemination, and preparedness to respond, led respectively by UNDRR, WMO, ITU and IFRC. The annual Global Status of Multi-Hazard Early Warning Systems, from UNDRR and WMO, tracks progress through Sendai Framework target G. Coverage has grown. Gaps remain largest in least developed countries and small island developing states.
WMO’s guidelines on impact-based forecasting (WMO-No. 1150) mark the shift from describing the weather to describing what it will do to people and services. That needs exposure and vulnerability data the meteorological service does not hold alone.
06GCRI’s part
Research and capability for the agencies that hold the warning mandate.
GCRI studies verification, impact-based methods and last-mile communication, and supports national agencies with technical assistance through early warning capability. It issues no warnings, runs no alerting channel and never sends a simulated warning to a live audience. Verification studies are designed for the Methods and Technical series and evaluations of warning chains for the Evidence Brief series. Agencies can contribute verification archives; communities can contribute accounts of how a warning reached them, or did not.
07Research questions
What GCRI studies.
Research focuses on the links where warnings most often fail, and on evidence that agencies can use to improve their own systems.
Verification
How good are forecasts?
Measuring forecast skill, false alarms and missed events against observations.
Communication
Do messages work?
How wording, channel and trust affect whether people act.
Last mile
Who is missed?
Groups and places that warnings do not reach, and why.
08Public authority
Only authorised agencies issue warnings.
Authorised national and local agencies issue warnings. GCRI does not. In exercises, simulated warnings never reach live audiences. The Foundry system for forecast verification and warning support: NXS-EWS (multi-hazard monitoring and warning). Capability building for agencies: early warning capability.
The Consortium is not an emergency service. In immediate danger, contact your local emergency services and follow your authorities’ instructions.
09Related
Connected challenges and counterparts.
See disaster resilience and climate and hazards. The Global Risks Forum (GRF) examines institutional arrangements under disaster and crisis governance.
10Sources
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.
- Early Warnings for All, Executive Action Plan 2023–2027 (WMO with UNDRR, ITU and IFRC, 2022)
- Global Status of Multi-Hazard Early Warning Systems 2024 (UNDRR and WMO, 2024)
- WMO Guidelines on Multi-hazard Impact-based Forecast and Warning Services (WMO-No. 1150, 2015, with Part II, 2021)
- Gneiting and Raftery, Strictly proper scoring rules, prediction and estimation, Journal of the American Statistical Association 102 (2007)
- Sendai Framework for Disaster Risk Reduction 2015–2030 (UNDRR, 2015)
- NS-11, Verification and monitoring, a proposed standard
11Questions
Questions and answers.
Can I receive warnings from GCRI?
No. GCRI does not issue warnings. Use the authority channels of your national meteorological, hydrological or civil protection agency.
How does GCRI work with warning agencies?
Through agreed source and methods interfaces, research collaboration and technical assistance. The agency keeps its authority and its data ownership.
What is forecast verification?
The comparison of forecasts with what was observed, to measure skill, bias, false alarms and missed events. It shows where forecasts can be trusted and where they cannot.
Why is the last mile so hard?
Because reaching everyone requires reliable channels, local languages, accessible formats, trust and the means to act. Gaps often follow existing inequalities.
Does GCRI support anticipatory action?
GCRI studies trigger evaluation and preparedness, supported by the AAP system in Foundry. Triggers never release funds or dispatch resources automatically; those decisions stay with the responsible institutions.
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