The Met Office ensemble system

MOGREPS is primarily designed to aid the forecasting of rapid storm development, wind, rain, snow and fog.

Global and UK ensembles

The global ensemble (MOGREPS-G) produces forecasts for the whole globe up to a week ahead. The regional ensemble (MOGREPS-UK) produces forecasts for an area covering the UK for the next five days.

In the UK ensemble the model parameters (temperature, pressure, wind, humidity, etc.) are forecast at grid points separated by about 2.2 km, and the model has 70 vertical levels.

The UK ensemble covers a limited area, so the global ensemble provides information on the weather entering the UK model domain through the boundaries. Because the global ensemble covers a much larger area it has to be run at a lower resolution, so the parameters are forecast at grid points separated by about 20 km.

Accounting for errors

There are several sources of uncertainty in weather forecasting which can cause errors in the forecast, including:

  • the starting conditions
  • the forecast model

The starting conditions

The future evolution of the atmosphere is very sensitive to small errors in the analysis that we use to start the forecast. To start an ensemble forecast we first make a set of small changes (or perturbations) to the analysis, which are consistent with the uncertainties in the starting conditions.

Each time we run an ensemble forecast, we use 17 of those perturbations, plus the unperturbed analysis, as starting conditions for an ensemble of 18 different forecasts.

The forecast model

The model tries to replicate the complex dynamics of the atmosphere and it does this by including many equations and approximations. These approximations will not always adequately represent the processes taking place and this can lead to errors in the forecast.

To account for as many different causes of forecast error as possible, MOGREPS makes small random variations to the forecast model itself, as well as changes to the initial state.

The numerical weather prediction models page contains further details on the model configurations used for ensemble forecasts.