Ensemble forecast interpretation
Ensemble weather and flood forecasts are summarised as probabilities of exceeding thresholds, so users see the chance of a hazard rather than a single scenario.
GCRI · Climate and Hazards
Forecasting for hazards
Forecasting and time-series analysis supply the predictive side of hazard evidence: weather and flood forecasts, seasonal outlooks and statistical predictions. In this field the emphasis is on probabilistic forecasts and on verifying them honestly against what happened.
01Register
Forecasting for hazards on the record.
Method recordSTEM method
- MethodForecasting and time-series analysis
- StewardClimate and Hazards
- Applied inClimate and Hazards
- Data4 inputs
- Checks3 validation steps
- Canonical pageSTEM Commons
02Application
What forecasting and time-series analysis does here.
Forecasting and time-series analysis predict future values of variables from past observations and explanatory information. They support early warning and planning across hazards, markets and health. In climate and hazards and disaster and crisis, forecasts trigger early action and anticipatory finance before shocks materialise. Probabilistic forecasts allow decisions to account for uncertainty across connected systems. The canonical description is on the STEM Commons.
Seasonal outlook use
Seasonal forecasts from several centres are combined, and their skill for the region and season is shown beside every outlook so users know when to trust it.
Forecast verification
Forecasts are scored against observations with proper scoring rules and compared with reference forecasts such as climatology.
03Geography
Climate signals worldwide.
Rain, daytime surface heat and flood water 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
Climate signals, for this page
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 (persistent cloud still leaves gaps)
- Source
- VIIRS NOAA-20 Level 3, 8-day (NASA LANCE)
- Provider
- NASA LANCE
- Licence
- NASA open data
- Vintage
- 8-day; Satellite 8-day composite; persistent cloud still leaves gaps
- Newest at build
- 2026-09-14
- Resolution
- about 1 km grid
- Uncertainty
- Satellite skin temperature of the ground over the 8 days ending on the date shown, a heat exposure indicator; not air temperature, heat index or a heat warning.
- Reached through
- gibs.earthdata.nasa.gov, only after you allow the live map
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
- 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
- Observed
- Source
- GHRSST MUR25 (NASA JPL PO.DAAC)
- Provider
- NASA JPL PO.DAAC
- Licence
- NASA open data
- Vintage
- daily; Satellite analysis
- Newest at build
- 2026-10-12
- Resolution
- about 2 km grid
- Uncertainty
- Satellite analysis of how far sea temperature departs from its usual value for the date shown; a marine heat indicator, not a coral bleaching alert.
- 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.
Climate signals, 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 · NASA JPL OPERA DIST-ALERT · NASA AIRSSources 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
- 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
- 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
- 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
- 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.
- 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).
- Observed (EO): NASA AIRS. 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
- Precipitation rate, daily mean: GPM IMERG, NASA GES DISC · 12 Oct 2026
- Land surface temperature, day, 8-day composite: VIIRS NOAA-20 Level 3, 8-day, NASA LANCE · 14 Sep 2026
- Flood water, 3-day composite: VIIRS Global Flood Product, NASA LANCE · 14 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
- Land cover type (IGBP), yearly: MODIS Terra and Aqua land cover (MCD12Q1), NASA LP DAAC · 2024
04Data
What the method consumes.
Datasets and records used by forecasting and time-series analysis on this platform, with the role each plays and the label its values carry. Sources are listed in the source register.
| Data | Role | Label |
|---|---|---|
| ECMWF and other centres’ ensemble forecasts | Probabilistic predictions | FORECAST |
| Copernicus C3S multi-system seasonal forecasts | Seasonal outlooks | FORECAST |
| Station and gauge observations | Verification | OBSERVED |
| Reforecast archives | Skill estimation | MODELLED |
05Twin and cascade simulator
Model forecasting for hazards as a system. Run the cascade.
Assembled from the Nexus Standards area profile Climate risk 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
- Sea-level rise
- Coastal flood (set off downstream)
- Storm surge (set off downstream)
- High-tide flooding (set off downstream)
- Coastal erosion (set off downstream)
- Saltwater intrusion (set off downstream)
- Estuary flood (set off downstream)
- Coastal habitat squeeze (set off downstream)
- Wetland loss (set off downstream)
- Mangrove loss (set off downstream)
- Groundwater flood (set off downstream)
- Climate-driven migration and relocation (set off downstream)
- Mass displacement (set off downstream)
Systems and couplings
Controls
NS-0Constitution and principlesNS-1The UNI and the artefact catalogue (grammar v0.2: domain, sector, region and environment segments)NS-3Risk record UNIs (grammar, legacy crosswalk, allocation authority)NS-3bDataset and product metadata profile (STAC, DCAT, PROV-O)NS-9Contextual UNIs (deployments, instances, programme instances)NS-11Verification and monitoring (evidence, attestations, zero-trust conformance observation)NS-14Conformance and crosswalk to external standardsNRS-H65Hazard family: Planetary boundary transgressions (NHS-1 planet.boundary)NRS-H62Hazard family: Compound and multi-hazard events (NHS-1 sys.compound)NRS-H71Hazard family: Deep-time and cosmic catastrophes (NHS-1 planet.deep-time)NRS-H79Hazard family: Mental health crises (NHS-1 health.mental)NRS-H75Hazard family: Climate-sensitive illness (NHS-1 health.climate-sensitive)NRS-H7Hazard family: Large-scale circulation anomalies (NHS-1 atmo.climate-mode)
Observation
- ERA5 reanalysis (Copernicus Climate Data Store) (listed for reference)
- CMIP6 climate projections (Copernicus Climate Data Store) (listed for reference)
- NGFS Scenario Explorer (listed for reference)
- INFORM Risk Index (listed for reference)
- Number of deaths, missing persons and directly affected persons attributed to disasters per 100,000 population
- Total greenhouse gas emissions per year
- Direct economic loss attributed to disasters in relation to global GDP
Example geography
- Pacific Island states: 150 hexagonal cells
- Night lights tonight, outages (VIIRS Day/Night Band), NASA GIBS
- Surface water through cloud, 30 m (OPERA DSWx-S1 radar), NASA GIBS
- Rain rate, last half hour (IMERG), NASA GIBS
- Vegetation disturbance alerts, 30 m (OPERA DIST-ALERT), NASA GIBS
06Validation
How results are checked.
Forecasts are evaluated out of sample with proper scoring rules and reliability diagrams. Rolling-origin evaluation tests performance over time.
| Check | How it is done |
|---|---|
| Proper scoring rules | Forecasts are scored with measures such as the continuous ranked probability score that reward honest probabilities |
| Reliability diagrams | Forecast probabilities are compared with observed frequencies |
| Reference comparison | Skill is always stated against a reference such as climatology or persistence |
Structural breaks and regime changes undermine models trained on the past. Forecast skill typically declines rapidly with lead time.
07Methods and evidence
How forecasting for hazards 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 forecasting for hazards 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
FAIR guiding principles · GO FAIR and FORCE11W3C PROV · World Wide Web ConsortiumGuidance on consistent treatment of uncertainties · IPCCCEOS Analysis Ready Data · Committee on Earth Observation Satellites
08Connections
Topics that rely on this method.
09Process
How the process runs.
Process
Forecasting for hazards: Flood forecasting and warning chain
The WMO flood forecasting manual and Early Warnings for All describe the chain from forecast to action, across EW4All’s four pillars.
01 Forecast
- 01Rainfall forecastSourceNumerical weather prediction and nowcasts supply rainfall input. Ensembles can apply to weather prediction and hydrological models.
- 02Hydrological modelModel · Geological surveyA hydrological model turns rainfall into runoff and discharge. The manual covers model choice, parameters and calibration.
- 03Hydraulic modelModelA hydraulic model routes the discharge to water levels along the river and floodplain. The place is set by the page.
- 04Inundation mapsDatasetInundation forecasting combines a level-and-flow model with a digital flood plain surface, the manual’s most sophisticated public service.
02 Warning
- 05ThresholdsGateForecasts are compared with thresholds agreed in advance, as in a threshold-based alert service. Impact-based guidance was not read.
- 06Warning decisionDecision · Geological surveyThe agency responsible for forecasts and warnings decides on the warning. It should understand the roles of the other agencies concerned.
- 07Warning disseminationStepWarnings are communicated through the channels people use. This is EW4All pillar 3, warning dissemination and communication.
03 Response
- 08Early actionStepPeople and institutions act on the warning. This is EW4All pillar 4, preparedness and response capabilities.
- 09Forecast verificationStepForecasts are verified using hits, misses and false alarms. The manual lists probability of detection, false alarm rate and threat score.
Neutral outline of a published external standard or method, from its issuing body. Not a record of operation. Nexus does not perform, certify or approve any step shown. A gate or decision belongs to the party the source names.
10Stewardship
Who maintains the method.
Climate and Hazards stewards forecasting and time-series analysis for the Consortium and reviews how it is applied across platforms.
11Questions
Questions and answers.
What are the limits of forecasting and time-series analysis in this field?
Structural breaks and regime changes undermine models trained on the past. Forecast skill typically declines rapidly with lead time.
How are results checked?
Forecasts are evaluated out of sample with proper scoring rules and reliability diagrams. Rolling-origin evaluation tests performance over time.
Are the values on this page real?
The data names, roles and checks are real descriptions of practice. The canvas shows a design of the method’s use, not a run; no result is reported here.
Where else is this method applied?
The canonical method page lists every platform that applies it.
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