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The IFS models the dynamics of the atmosphere and the physical processes that occur, and also other processes that influence the weather e.g. atmospheric composition, surface energy fluxes, the marine environment and processes at the atmosphere/surface interface (scroll down to soil/surface section). Several configurations of the atmospheric model are used, each tailored towards a specific aim:
- Medium Range ensemble to investigate detail and uncertainty in the forecast during the first 15 days.
- Sub-seasonal ensemble to give probability of general conditions to 46 days ahead.
- Seasonal ensemble to give probability of general conditions at longer ranges.
There are some slight differences, but generally the same model structure is used in each of the different model configurations. The relative skill of the models and their strengths have been investigated.
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Some major model changes and additions were made to the IFS with the introduction of Cy50r1 in May 2026. These are:
Observations
Upper air observations
Major model changes
Assimilation:
New ocean and sea ice ensemble analysis system.
Many more T2m observations than in previous cycles.
Coupled ocean-atmosphere assimilation of microwave imagers and geostationary infrared data giving increments to ocean and sea-ice as well as upper air.
Scale-selective EDA re-centring to address issues with tropical cyclone initialisation.
Introduction of stratospheric humidity assimilation from radiosondes up to 60hPa.
Upgrade of Radiative Transfer for TOVS (RTTOV) model improving simulation of satellite radiances for assimilation.
Increased number of wave observations.
- More satellite data with higher density in time and space. Window channels - frequency bands where the atmosphere is relatively transparent - have been included in the assimilation.
Observations:
Atmospheric observations
Shorter time slots allowing more accurate comparison between model and
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observations.
Wind tracing with ozone-
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sensitive data.
Include specific humidity increments above the tropopause.
Ocean observations
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In situ temperature/salinity profiles
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.
IFS Model
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Model
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:
New ocean and sea ice modelbased on NEMO-
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SI3, with updates including:
Improved numerical schemes and physical parametrisation.
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Introduction of multi-category sea
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ice model with
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forecast salinity and melt pond dynamics
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.
The more advanced
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sea ice model SI3 replaces LIM2
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.
Albedo diagnosed by sea ice model SI3 replaces climatological sea
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ice albedo.
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Turbulence scheme for better vertical mixing processes.
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Extension of ORCA grid
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area further towards the South Pole
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.
New ensemble analysis system for ocean and sea
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ice based on
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ORAS6 reanalysis. This is used for initialising both the forecasts and the re-forecasts.
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The updates include:
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More accurate representation of short-term variability
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(e.g. diurnal cycle of sea surface temperature
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)
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.
Wave model:
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New waves and sea ice interaction. Waves penetrate through open ice areas.
Revised wave model bathymetry.
- Surface currents
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Atmospheric analysis:
- EDA resolution reduction and scale-selective re-centring addresses issues with tropical cyclone initialisation. Helps avoid analysis of unrealistic 'double-centred' pattern.
Snow and land-ice:
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- introduced into wave model with less smoothing and choppier seas.
New glacier parametrisation scheme in ecLand. Uses fractional ice coverage in grid square and a four-layer land-ice scheme.
New snow parametrisation scheme for sea ice. Uses fractional ice coverage in grid square and a single-layer snow scheme. Reduces the warm bias seen in winter over the ice surface, especially in cloud free situations.
Modified Stochastically Perturbed Parametrisation (SPP) configuration to reduce
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10metre wind spread in the ensemble, and also related misalignment of wind speed and wave height in perturbed members.
Model physics:
Convection and microphysics changes to improve the propagation of precipitation from ocean across land.
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Updates in ordering of aerosol climatology, convection, and physics to improve tropical upper-air forecasts.
Reduced vertical diffusion in stable conditions in the stratosphere.
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Coupling:
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Coupling of
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snow
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depth and sea
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ice
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thickness from the sea
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ice model to the atmosphere. Allows snow cover on sea ice and variable ice thickness to be represented in the atmospheric forecast model.
Fully coupled ocean-atmosphere forecasts. The model atmosphere
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uses sea surface temperatures (SSTs) directly from the ocean
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Meteorological impact
Medium Range
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model
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Sub-seasonal range
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.
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(FUG Associated associated with Cy50r1)
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