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In April 2026 the operational Artificial Intelligence Forecasting System (AIFS) will be upgraded.
IMPORTANT: The AIFS will be upgraded on the same day as IFS Cycle 50r1. Subscribe to forecast_changes-request@lists.ecmwf.int to receive notifications about updates, including when the test data will be available. |
New and changed parameters
Input and Output Parameters
The table below shows all parameters used and output by AIFS Single v2.
- New parameters and levels are highlighted in green.
- Parameters which used to be prognostic but are now diagnostic are highlighted in the blue cells.
| Field | Level type | Input/Output |
|---|---|---|
| Geopotential (Z), horizontal and vertical wind components (U, V), specific humidity (Q), temperature (T) | Pressure level: 10, 50, 100, 150, 200, 250, 300, 400, 500, 600, 700, 850, 925, 1000 | Both ("Prognostic") |
| Vertical velocity (W) | Pressure level: 10, 50, 100, 150, 200, 250, 300, 400, 500, 600, 700, 850, 925, 1000 | Output ("Diagnostic") |
| Specific humidity (Q) | Pressure level: 50 | Output ("Diagnostic") |
Surface pressure (SP), mean sea-level pressure (MSL), sea-surface temperature (SST), skin temperature (SKT), 2m temperature (2T), 2m dewpoint temperature (2D), 10m horizontal wind components (10U, 10V), total column water (TCW), snow depth (SD), mean wave period (MWP), mean wave direction (MWD), coefficient of drag with waves (CDWW), significant wave height (SWH), significant wave height of all waves with periods within the inclusive range from:
| Surface | Both ("Prognostic") |
Volumetric soil moisture (VSW) and Soil temperature (SOT), both at solid depth 1 and 2 | Soil layer | Both ("Prognostic") |
| 100m horizontal wind components (100U, 100V), surface short-wave (solar) radiation downwards (SSRD), surface long-wave (thermal) radiation downwards (STRD), cloud variables (TCC, HCC, MCC, LCC), runoff water equivalent (ROWE) and snow fall (SF), total precipitation (TP), convective precipitation (CP), snow cover (SNOWC) | Surface | Output ("Diagnostic") |
| Standard deviation of sub-gridscale orography (SDOR), Slope of sub-gridscale orography (SLOR), Land-sea mask (LSM), Geopotential (Z), insolation, latitude/longitude, time of day/day of year | Surface | Input ("Forcings") |
New parameters
More detailed information about the new parameters introduced with AIFS Single v2 is provided in the table below.
All parameters are surface level and output in GRIB2 format.
NEW PARAMETERS | |||
|---|---|---|---|
Param ID | Short Name | Name | Units |
h1012 | Significant wave height of all waves with periods within the inclusive range from 10 to 12 seconds | m | |
h1214 | Significant wave height of all waves with periods within the inclusive range from 12 to 14 seconds | m | |
h1417 | Significant wave height of all waves with periods within the inclusive range from 14 to 17 seconds | m | |
h1721 | Significant wave height of all waves with periods within the inclusive range from 17 to 21 seconds | m | |
h2125 | Significant wave height of all waves with periods within the inclusive range from 21 to 25 seconds | m | |
h2530 | Significant wave height of all waves with periods within the inclusive range from 25 to 30 seconds | m | |
swh | Significant wave height | m | |
mwd | Mean wave direction | Degree true | |
mwp | Mean wave period | s | |
cdww | Coefficient of drag with waves | dimensionless | |
sd | Snow depth | kg m-2 | |
snowc | Snow cover | % | |
Technical content
GRIB encoding
All AIFS parameters are produced exclusively in GRIB2 format.
The GRIB model process identification number for AIFS Single v2 will be as follows:
Component | Model identifier | |||||
|---|---|---|---|---|---|---|
v1.1 | v2 | |||||
generatingProcessIdentifier | Atmospheric model |
| 4 | 5 | ||
Encoding of wave parameters
Wave parameters are newly introduced with the implementation of AIFS Single v2.
Users should note that wave parameters in AIFS are encoded differently from those produced by the IFS model. This is to facilitate ECMWF’s migration towardsGRIB2 as the standard output data format.
- AIFS wave parameters use MARS stream 'oper' (
stream=oper). - IFS wave parameters use a dedicated wave stream (
stream=wave).
Resources
Webinar
Coming soon!
References
Let it snow! How machine learning will forecast snow in the AIFS, Raoult, N., Pinnington, E., Arduini, G., Rudiger, C., De Rosnay, P., Chantry M.
- Representing ocean wind waves in ECMWF's AIFS, Hahner, S., Bidlot, J., Kousal, J., Zampieri, L., Lessig, C., Chantry, M.
- Moldovan et al. (2025), An update to ECMWF’s machine-learned weather forecast model AIFS, arXiv:2509.18994.
- Lang et al. (2024), AIFS — ECMWF’s data-driven forecasting system, arXiv:2406.01465.

