What is an ensemble forecast?

Instead of running just a single forecast, the computer model is run a number of times from slightly different starting conditions.

A forecast is an estimate of the future state of the atmosphere. It is created by estimating the current state of the atmosphere using observations, and then calculating how this state will evolve in time using a numerical weather prediction computer model. As the atmosphere is a chaotic system, very small errors in its initial state can lead to large errors in the forecast.

This means that we can never create a perfect forecast system because we can never observe every detail of the atmosphere's initial state. Tiny errors in the initial state will be amplified, so there is always a limit to how far ahead we can predict any detail.

To test how these small differences in the initial conditions may affect the outcome of the forecast, an ensemble system can be used to produce many forecasts.

How we do ensemble forecasts

Instead of running just a single forecast, the computer model is run a number of times from slightly different starting conditions. The complete set of forecasts is referred to as the ensemble, and individual forecasts within it as ensemble members.

Ensemble forecast systems are designed so that each member should be equally likely. The initial differences between the ensemble members are small, and consistent with uncertainties in the observations. But when we look several days ahead the forecasts can be quite different.

A schematic illustration of an ensemble forecast

An ensemble samples the uncertainty of the forecast, assuming that the forecast model is perfect. If the starting conditions were known accurately, and the model was perfect, then an accurate forecast could, in theory, be produced. However, because it is not possible to know the exact starting conditions we use our best guess and generate a forecast which can sometimes be inaccurate (shown in red in the schematic above). By sampling the uncertainty in the starting conditions, and running several ensemble members forward with the model (shown in blue in the schematic above), we produce an estimate of the forecast uncertainty and an indication of which weather events may occur.

How ensembles help weather forecasters

The ensemble forecasts give the forecaster a much better idea of what weather events may occur at a particular time. By comparing these different forecasts the forecaster can decide how likely a particular weather event will be. If the forecasts vary a lot then the forecaster knows that there is a lot of uncertainty about what the weather will actually do, but if the forecasts are all very similar they will have more confidence in predicting a particular event.

The ensemble forecasting system developed by the Met Office to produce these forecasts is called the Met Office Global and Regional Ensemble Prediction System (MOGREPS).