Datasets

These charts show areas where anomalous CAPE Shear are likely to occur.

This chart aims to highlight areas where unusually anomalous 2 metre temperatures are ...

These charts aim to provide pointers to areas where anomalous precipitation amounts are likely to occur during the 24 hour, 2 day, 5 day or 10 day period previous to the selected validity time...

This chart aims to highlight areas where unusually anomalous precipitation is likely to ...

These charts show areas where anomalous significant wave heights are likely to occur. These charts are based on the ECMWF ense ...

These charts show areas where anomalous snow fall is likely to occur. These charts are based on the ECMWF ensemble for ...

These charts aim to provide pointers to areas where anomalous values of water vapour flux are likely to occur based on the ECMWF en ...

These charts show areas where anomalous 10 m wind gusts are likely to occur. These charts are based on the ECMWF ensemble fore ...

These charts show areas where anomalous 10 m wind speeds are likely to occur. These charts are based on the ECMWF ensemble for ...

Cumulative Density Functions (CDF) describes the distribution of the values of a variable (e.g.temperature) as forecast by the ENS ensemble members. The CDF curve shows the proportion (in %) of ENS members...

Meteograms show a probabilistic interpretation of the ENS forecasts for specific locations using a box and whisker plot. It shows the time evolution of the distribution of several meteorological parameters on a single diagram...

This dataset is from an ensemble forecast initiated on 3 October 2023 at 0 UTC. Key details: IFS cycle 48r1,TCo1279 (9km), 137 levels, 450s (7.5 min) timestep, 48h run, 10+1 members, EDA initial conditions (no singular vector perturbations), no model uncertainty, 1 hourly archiving 0-24h, 3 hourly archiving 24-48h.

Ensemble Mean Sea Level Pressure (MSLP) is the mean MSLP of the ensemble members (in hPa) and detail is smoothed out. These charts show surface pressure patterns...

Spread usually, but not always, increases with forecast range. Spread refers to the uncertainty of the values of a parameter but it does not necessarily refer to the flow patterns...

The ensemble mean is the mean value derived from all the 50 ensemble members plus the control member. This value attempts to capture the general picture while smoothing out spurious detail...

The ensemble spread is a measure of the differences between the 50 ensemble members plus the control member and is represented by the standard deviation with respect to the ensemble mean...

These charts show the mean and variation in the latest ECMWF ensemble forecast (ENS). ...

These charts show the mean and variation in the latest ECMWF ensemble forecast (ENS). ...

These charts show the mean and variation in the latest ECMWF ensemble forecast (ENS). ...

Spread refers to the uncertainty of the values of a parameter but it does not necessarily refer to the flow patterns...

These charts show the mean and variation in the latest ECMWF ensemble forecast (ENS). ...

One model cycle of ECMWF ensemble prediction system set up to explore data information content in the scope of a ESoWC project. Perturbed and control forecast of temperature on 91 model levels are archived. The data is encoded as IEEE single-precision (32-bit floats) circumventing any other lossy compression. This is in contrast to the default 16- or 24-bit linear packing used in the ECMWF data archive. The volume of the full experiment is 1 TB.

Examples

These diagrams aim to show the time evolution of regimes which are indicative of the likely weather in and around Europe.The winds across the Atlantic can usefully be classified into four regimes ...

The EU-funded  ENSEMBLES project intends to develop an ensemble prediction system for climate change based on the principal state-of-the-art, high resolution, global and regional Earth System models developed in Europe, validated against quality controlled, high resolution gridded datasets for Europe, to produce for the first time, an objective probabilistic estimate of uncertainty in future climate at the seasonal to decadal and longer timescales.