Science · R&D · Innovation

Science that turns weather into measurable readiness.

Our research focuses on three questions: how to process weather data without losing its source, how to bring preparedness forward for weather-driven disasters, and how to measure risk as the climate changes.

  • 7named source institutions: ECMWF, NOAA, DWD, AEMET, Météo-France, EUMETSAT, Copernicus
  • T+6 … T+48lead-time steps in the verification design
  • 5,376samples in the 14-day verification matrix (design)
  • 9capabilities with a public maturity status
Photo: Pixabay / Pexels

Our goals

Three areas, measurable goals.

Each goal is listed with how its progress will be measured.

01 · Data processing

Every number traceable to its source.

Processing multi-source meteorological data while preserving its meaning and origin.

  • Every input is stored with its institution, product, run time and content identity
  • Incompatible sources are not silently blended or resampled
  • A product not checked against real observations is never called “verified”

Criterion · share of outputs without a source record · open verification reports

02 · Natural disasters

Shortening the time from warning to action.

Floods and flash floods, storms, strong wind, heatwaves, snow and ice, coastal events.

  • Make the chain official warning → awareness → acknowledgement → readiness measurable
  • Rehearse the real event in advance with scenario-based exercises
  • Connect after-action learning to the next threshold review

Criterion · time from warning to the first preparation action · in exercise and event records

03 · Climate change and adaptation

Making shifting thresholds visible.

Translating climate-scale change into the language of local operating thresholds.

  • Track how often local thresholds — hot days, intense-rain hours, frost nights — are crossed, using reanalysis data
  • Produce inputs for municipal and sector adaptation plans
  • Keep climate-scale and weather-scale decisions apart

Criterion · trends in local threshold frequency · decisions that become adaptation plans

Our scientific model

A shared core. Activity-specific meaning.

Weather information is only the beginning. The model has four layers: each inherits the previous layer’s output together with its origin, and no layer silently changes the evidence that came before it.

Calculation, rules and language each keep their role

Numerical model

calculates

Produces the values, ranges and verification metrics for your point from forecast fields.

Every number you see on screen comes only from here.

Rule engine

applies

Applies your thresholds and the sector pack’s rules deterministically.

Every trigger shows which rule ran, with which value.

Language model

explains

Translates the result into the language of your work and writes briefing and checklist text.

It explains. Numbers and thresholds come from the layers above.

Public scientific architecture

  1. 01

    Source processing

    Forecast fields, official warnings, station observations and satellite products are taken in with their name, time and content identity.

    Source evidenceVerification

    Evidence
  2. 02

    Local probabilistic model

    Multi-model evidence for your point is ordered by lead time. The model range is shown openly; calibration comes only after verification.

    Hazard

    Uncertainty
  3. 03

    Impact model

    Your thresholds and exposure meet the weather evidence: which job, at what time, how much it may be affected.

    ExposureImpactRiskTiming

    Impact
  4. 04

    Decision and evidence

    Recommendation, checklist, decision record and exercise. Every step can be traced back to its source.

    PreparationActionOutcomeLearning

    Decision

We explain openly how the layers work. Threshold calibration, sector rule sets and the order in which evidence is combined remain part of the product.

Public scientific principles

Seven rules every layer obeys.

How trust is kept
  1. 01

    Source remains source.

    A provider’s record is never re-labelled as ours.

  2. 02

    Missing stays missing.

    A missing value stays missing; it never becomes “no rain” or “low risk”.

  3. 03

    Agreement is shown as a range.

    Similar model output is never presented as a probability.

  4. 04

    Severity and confidence stay apart.

    How strong an event could be says nothing about how sure we are.

  5. 05

    Official warnings stay separate.

    The issuing authority’s warning keeps its own lane; our output never takes its place.

  6. 06

    No silent data fusion.

    Sources are combined only by documented rules, and the combination stays visible.

  7. 07

    No public claim without evidence.

    A capability is described at the stage its published evidence supports.

Numerical analysis

Forecast meets observation.

Verification is done on the forecast’s own grid and at the exact valid time. The error definition, the metrics and the matching rule are public: an academic should be able to reproduce the same result.

Point sampling

The value is taken from the model’s own grid and the sampling method is recorded. No height correction is applied silently.

Lead-time steps

The same valid time is viewed from the T+6, T+12, T+24 and T+48 runs, so you see how forecast skill changes with lead time.

Time alignment

Forecast and observation are matched at the exact valid time. Unmatched samples are left out, with the reason recorded.

Uncertainty

The range between models is shown openly, never as a probability.

Metrics

Mean error, mean absolute error and root-mean-square error, by lead time, station and model. Missing data stays missing.

No ranking

Models are ranked only after a verification campaign is complete and published.

Error and metric definitions

e = F − O
forecast minus observation
Bias = (1/n) Σ e
mean error
MAE = (1/n) Σ |e|
mean absolute error
RMSE = √[(1/n) Σ e²]
root-mean-square error

Temperatures are handled in kelvin. Observations come from official national station networks: AEMET in Spain, Météo-France in France.

Verification campaign · 2 m air temperature

8stations4lead times3models56runs

5,376expected samples · 14 days

The campaign uses a selected set of stations and does not represent a whole country. Results will be published when it is complete.

Verification and maturity

We state plainly where we are.

Every scientific capability stands on one of five steps. A step is climbed only when its evidence is published. No capability is at the “in production” step today.

Source: public capability manifest

Maturity of scientific capabilities, from the public capability manifest
Capability1Code present2Locally verified3Verified with a live source4Calibrated5In production
2 m air temperatureStandard variable · kelvinCurrent stage: Verified with a live sourcereachedreachedcurrent stagenot reachednot reached
Forecast–observation matching2 m air temperature onlyCurrent stage: Verified with a live sourcereachedreachedcurrent stagenot reachednot reached
Temperature verification metricsBias, MAE and RMSE · 2 mCurrent stage: Locally verifiedreachedcurrent stagenot reachednot reachednot reached
Heavy precipitation evidenceNot calibratedCurrent stage: Verified with a live sourcereachedreachedcurrent stagenot reachednot reached
Wind hazard evidenceNot calibratedCurrent stage: Verified with a live sourcereachedreachedcurrent stagenot reachednot reached
Confidence engineNo scored confidenceCurrent stage: Code presentcurrent stagenot reachednot reachednot reachednot reached
Impact risk modelNot publishedCurrent stage: Code presentcurrent stagenot reachednot reachednot reachednot reached
FloodHazard evidenceCurrent stage: In developmentnot reachednot reachednot reachednot reachednot reached
Climatological anomalyNeeded for the climate goalCurrent stage: In developmentnot reachednot reachednot reachednot reachednot reached

Forecasts, sources and official warnings are shown separately. Combined probability, confidence and impact scores are in development.

Research areas

Each status shows the current stage of the work.

  • Official warning connectivityLIVE
  • Source provenanceLIVE
  • Forecast verificationIN VALIDATION
  • Prospective reference-skill researchIN VALIDATION
  • Operational impact modellingIN DEVELOPMENT
  • Calibration researchIN RESEARCH
  • Outcome learningPLANNED

Preparedness research

From warning to readiness

Official warnings remain authoritative. MetOry preparation and advisory outputs are decision support. The two lanes stay parallel and are never merged.

Lane 1

Official warning — authoritative

Issued by the national authority and shown unchanged, with attribution.

Lane 2

MetOry preparation / advisory — decision support

A separate reading for your activity, alongside official warnings.

  1. 1

    Detect

    Weather evidence or an official warning becomes relevant.

  2. 2

    Reach

    The information reaches the responsible person or team.

  3. 3

    Acknowledge

    Receipt and awareness can be recorded.

  4. 4

    Assess

    Operational relevance is reviewed in context.

  5. 5

    Prepare

    Preparation steps are reviewed, assigned and tracked.

  6. 6

    Exercise / act

    A drill, a preparation action or a real response can be recorded.

  7. 7

    Review

    Outcome and lessons are captured for next time.

Preparedness Evidence Trail

Organisations can record a trail of warning, delivery, acknowledgement, assignment, action, exercise and review. Some steps are still in development.

  • Warning receivedLIVE
  • Notification deliveredIN DEVELOPMENT
  • Warning viewedIN DEVELOPMENT
  • Warning acknowledgedIN DEVELOPMENT
  • Responsible person or team assignedIN DEVELOPMENT
  • Preparation startedIN RESEARCH
  • Preparation completedIN RESEARCH
  • Exercise completedPLANNED
  • Outcome reviewedPLANNED
SYNTHETIC / EXAMPLE

Exercise: heavy rain warning at a logistics facility

Example scenario with sample values.

  1. 01Heavy rain warning
  2. 02Logistics facility
  3. 03Drainage inspection
  4. 04Outdoor stock protection
  5. 05Route review
  6. 06Manager acknowledgement
  7. 07Post-exercise review

Results such as avoided damage or savings are claimed only when independently measured.

Research & Applied Science

Five programmes, one evidence chain.

Each programme shows its current status.

01LIVE

Multi-source meteorological evidence

Forecast, observation, satellite / Earth-observation and official-warning evidence, retained with source, product, time and provenance.

02IN VALIDATION

Forecast verification

Where suitable observations exist, forecast evidence can be tested against real observations. Historical and prospective verification methods are under active research.

03IN DEVELOPMENT

Weather-to-impact modelling

How weather hazards interact with location, exposure and operational context.

04IN RESEARCH

Warning & preparedness behaviour

Studying whether warning information reaches the right person, is acknowledged in time and results in preparation.

05PLANNED

Exercises, outcomes & learning

Evaluating preparedness procedures through exercises, records and post-event learning.

Partner on a programme

Get in touch

Collaboration

Become a research partner.

We welcome joint verification campaigns, exercise research and adaptation studies with universities, meteorological services, municipalities and civil-protection bodies — and dialogue on responsible data use, verification and interoperability.

Mentions of the European Union, EUMETSAT or meteorological authorities do not imply affiliation, endorsement or funding.

Sources are named for attribution. Official warnings come from national weather services.