The Met Office Global and Regional Ensemble Prediction System (MOGREPS) is an ensemble system that produces uncertainty information, primarily for short-range forecasts. It focuses on aiding the forecasting of rapid storm development, wind, rain, snow and fog.
The global ensemble produces forecasts for the whole globe up to a week ahead. The regional ensemble produces forecasts for an area covering the UK for the next 36 hours (shown by the green area in the above image).
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 33 km.
There are several sources of uncertainty in weather forecasting which can cause errors in the forecast, including:
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 11 of those perturbations, plus the unperturbed analysis, as starting conditions for an ensemble of 12 different forecasts.
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 weather forecast models page contains further details on the model configurations used for ensemble forecasts.
Last updated: 15 August 2014