Levelmodel
Classweather
Parametersnot in the notes
Contextnot in the notes
Releasednot in the notes
Opennessunknown
Runs onnot in the notes
Statusactive
Benchmark Results
maintainer-run
WeatherBench 2 2domain
Z500 day 10, deterministic, IFS HRES vs Analysismaintainer-run
809
0450900
Score in RMSE m2/s2. Lower is better.
year 2022, 240x121 grid
Z500 day 10, deterministic, IFS HRES vs ERA5maintainer-run
802.7
0450900
Score in RMSE m2/s2. Lower is better.
year 2020, 240x121 grid
Z500 day 5, deterministic, IFS HRES vs Analysismaintainer-run
306.2
0450900
Score in RMSE m2/s2. Lower is better.
year 2022, 240x121 grid
Z500 day 5, deterministic, IFS HRES vs ERA5maintainer-run
305.5
0450900
Score in RMSE m2/s2. Lower is better.
year 2020, 240x121 grid
Z500 day 3, deterministic, IFS HRES vs ERA5maintainer-run
137.2
0450900
Score in RMSE m2/s2. Lower is better.
year 2020, 240x121 grid
Z500 day 3, deterministic, IFS HRES vs Analysismaintainer-run
136.5
0450900
Score in RMSE m2/s2. Lower is better.
year 2022, 240x121 grid
Z500 day 1, deterministic, IFS HRES vs ERA5maintainer-run
47.2
0450900
Score in RMSE m2/s2. Lower is better.
year 2020, 240x121 grid
Z500 day 1, deterministic, IFS HRES vs Analysismaintainer-run
41.2
0450900
Score in RMSE m2/s2. Lower is better.
year 2022, 240x121 grid
T850 day 10, deterministic, IFS HRES vs Analysismaintainer-run
3.626
024
Score in RMSE K. Lower is better.
year 2022, 240x121 grid
T850 day 5, deterministic, IFS HRES vs Analysismaintainer-run
1.841
024
Score in RMSE K. Lower is better.
year 2022, 240x121 grid
Where this comes from
Every score names who ran it: vendor-reported, maintainer-run or independent. A rank is shown with the population it was ranked in (gap rule 3).
Identity
Where this comes from
Developer and dates from the research notes. Release date is the vendor's public announcement; weights date is when open weights were published.
Architecture and Size
- Architecture
- other
- Total parameters
- – sources
- Active parameters
- –
- Checkpoint parameters
- –
- Context length
- not in the notes
- Input
- sensor
- Output
- sensor
Where this comes from
Parameter counts as the developer states them. Where the checkpoint holds a different total, both are shown (register A16).
Openness and Access
- Openness
- unknown
- Licence
- not in the notes sources
- Access routes
- not in the notes
Where this comes from
The licence file governs over registry tags and aggregator labels.
Deployment
- Runs on
- not in the notes
- Footprint
- not in the notes
- Runtimes
- not in the notes
Where this comes from
Deployment tiers and runtimes as named in the notes. Footprint is the notes' figure, not a measurement by AURION.
Indonesia
- Indonesian support
- not stated
- Regional languages
- not in the notes
- Jakarta hosting
- unknown
- Languages
- not in the notes
Where this comes from
Indonesia fields are carried on every model; unknown is an allowed value.
Lineage
The notes record no lineage for this model.
Industry Use Cases
No industry use case links this model.
Links
DeveloperECMWFgovernment, UK
ECMWFgovernment, UKModelIFS HRESECMWF, weather
IFS HRESECMWF, weatherUse CasesWeather ForecastingAgricultureUse cases of models in the same R&D topic; none is recorded for this model itself.
Who Runs It
Badan Meteorologi, Klimatologi, dan Geofisika (BMKG)Contract signed, 5 Feb 2026Badan Meteorologi, Klimatologi, dan Geofisika (BMKG)In production, 23 Sep 2025Deployments of these use cases; none names this model.
Badan Meteorologi, Klimatologi, dan Geofisika (BMKG)Contract signed, 5 Feb 2026Badan Meteorologi, Klimatologi, dan Geofisika (BMKG)In production, 23 Sep 2025Deployments of these use cases; none names this model.Organisations 1
Sources
- Dash researchsites.withgoogle.com https://researchsites.withgoogle.com/weatherbench/deterministic/
To cite this page: Project AURION, AI Use-Cases Research & Innovation, "IFS HRES", https://aurion.semai.id/models/ecmwf-ifs-hres/, records of October 2026.