Data coverage
This product provides gridded probabilistic weather forecasts. The grid resolution is approximately 2km and covers the UK and parts of Western Europe. It is produced by the Met Office IMPROVER Blended Probabilistic Forecast system. It is available in NetCDF format. Blended Probabilistic Forecast data is derived from the Met Office's operational NWP (Numerical Weather Prediction) ensembles and nowcasts. To give more reliable predictions, these are then blended and calibrated using the IMPROVER pipeline, and verified using spread–skill and reliability checks. This is 1 of 8 Blended Probabilistic Forecast products published by the Met Office on the Registry of Open Data on AWS. Data is available for the Global and UK domains, as gridded and spot (site-specific), and represented as percentiles and probabilities. This info is correct as of April 2026, but some things (like the number of sites, parameters and timesteps) may change in future. How probabilities work Ensemble forecasts show a range of possible weather outcomes. However, some users may find it more useful to see ensemble forecasts presented as probabilities, particularly when they're interested in specific thresholds. Probabilities are generated from an ensemble forecast by counting how many members of that ensemble exceed a particular threshold value. For example, if the threshold for screen temperature is 5°C, and 9 out of 18 ensemble members show a screen temperature above 5°C, there is a 50% chance of temperatures exceeding 5°C. About the grid The grid resolution is approximately 2km and covers the UK and parts of Western Europe. Numerical weather prediction (NWP) models generate forecasts for each grid point within a geographical area of interest. Each of these gridded forecasts corresponds to a particular diagnostic (e.g. precipitation rate) at a particular time. IMPROVER then takes an ensemble of these gridded forecasts and applies post-processing techniques to enhance them and represent them probabilistically. The resulting grid of values represents probabilities of exceeding or falling below a particular threshold. | Aspect | Values | | --- | --- | | Projection | Lambert Azimuthal Equal Area | | Longitude of Prime Meridian | 0.0° W | | Reference datum | ETRS89 - uses the GRS80 as a reference ellipsoid. | | Nominal resolution | 2 km | | Extreme West | -1158 km | | Extreme East | 924 km | | Extreme North | 902 km | | Extreme South | -1036 km | | Northwest Corner (Long, Lat) | -24.5099247, 61.31885886 | | Northeast Corner (Long, Lat) | 15.27976922, 61.9206868 | | Southwest Corner (Long, Lat) | -17.11712928, 44.51715281 | | Southeast Corner (Long, Lat) | 9.21255933, 44.899873 | | Semi Major Axis | 6378.137 km | | Semi MinorAxis | 6356.75231414036 km | | Longitude of Projection Origin | 2.5° W | | Latitude of Projection Origin | 54.9° N | | False Eastings | 0.0 km | | False Northings | 0.0 km | | East-West points | 1042 | | North-South points | 970 | | Grid type | Arakawa A | Parameters and timesteps There are 44 weather parameters available including: - Cloud - Temperature - Pressure - Humidity - Visibility - Precipitation rate and accumulations - Wind For most parameters, the following timesteps are available: - Every hour from 0 to 120 hours - Every 3 hours from 123 to 186 hours However, timesteps vary significantly for some parameters. Check the parameter documentation for more details. Latency Data is made available shortly after the model blend time. Archive length Data is available for the past 30 days. Business needs This product supports risk-based decision-making by providing uncertainty ranges rather than single deterministic values. Typical uses include: - assessing uncertainty for operational planning - evaluating weather-related risk thresholds - deriving deterministic products (e.g. 50th percentile) from probabilistic outputs Gridded forecasts show how a diagnostic varies spatially across a domain at a given time. By using a time series of gridded fields, you can determine how a weather diagnostic is expected to evolve across a geographic area. If you need a forecast for a specific location, a spot forecast may suit your needs better than gridded data. Spot Blended Probabilistic Forecasts are also available as percentiles and probabilities for both the UK and Global domains.
Access & permitted use
Review the publisher’s documentation for availability, eligibility and permitted uses, including commercial analysis, model training and redistribution.
This product is licensed under CC BY-SA
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