451: Forecast Series

Tables of the forecasts for individual gridpoints/stations/series and a graph of the historical and current forecast(s) are shown. The table shows the years for which the forecasts apply, some information about the definitions of the categories, and the forecasts themselves, presented in different formats.

In the thresholds box (top left) the climatological period is first indicated, and defines the data used to define the categories. The thresholds dividing the categories are then given in the units of the original data, possibly standardised depending on the standardisation option. For example, if the original data are in mm, and the anomaly standardisation is selected, the thresholds will be in mm anomalies from the climatological average. The climatological probabilities, below, show the proportion of years in the climatological period that were in each category. By default these probabilities will be 33% (assuming there are no ties, in which case the probabilities may deviate from 33% somewhat), but the actual probabilities will depend upon the threshold settings. The climatological odds are equal to the probability that the category in question was observed, divided by the probability that it was not observed. For example, if the climatological probability of "above-normal" is 33% the odds will be 0.5 ("above-normal" occurs half as often as "normal" and "below-normal" combined, i.e., it occurs half as of often as it does not occur).

The forecasts box presents the forecast in different formats. Probabilistic forecasts and odds are presented first. If the climatological probabilities are equiprobable and the forecast probability for the "normal" category is the lower than for the outer categories, it may be worth transforming the Y data so that they are normally disrtibuted. Applying the transformation will require CPT to reset . The probabilities are derived from the best-guess forecast (listed as "Forecast" under "Forecast ranges") by assuming that the errors in the best-guess forecast will be normally distributed (or, more strictly, follow a Student's t distribution), with the variance of the errors defined by the variance of the errors in the cross-validated predictions (alternative error variances can be set using Options ~ Forecast Settings ). If the Y data have been transformed it is assumed that the forecast errors of the transformed data will be normally distributed. From the best-guess forecast and the assumed error variance and distribution the probabilities of exceeding the various thresholds can be calculated. Prediction intervals can also be calculated for a given level of confidence. The prediction intervals are shown as the upper and lower limits under "Forecast ranges". The default is to define the intervals as one standard error from the best guess, which translates to a confidence level of about 68%. The default can be adjusted using Options ~ Forecast Settings .

The graph shows the history of the cross-validated forecasts (green line) and observations (red line), and the current forecast(s) shown by green crosses. The prediction intervals for the forecasts can be added by right-clicking on the graph, and following the "Customise" option. The vertical coloured divisions show the three categories. Note that when calculating the cross-validated forecasts, the threshold defintions will have fluctuated slightly, and so the current categorisation fo the forecasts and observations may not exactly match the cross-validated classification. This fluctuation is the reason for any apparent discrepancies between the graph and the contingency tables .

The forecasts can be saved by selecting the Forecasts tab from the File _Output Results ) menu. The graph itself can be exported as a graphics file by right-clicking anywhere in the child window and selecting Export from the pop-up menu. A default name is given to the graphics file, but this name can be changed using the browse button. The image quality for all the graphics formats can be improved by increasing the size of the image (see Options ~ Graphics ~ Graph Scaling ). The graphic title can be set using the Customise option upon right-clicking in the child window.

The y-axis limits can be set by right-clicking on the image and then selecting the Customise ~ Y-Axis Limits option. The maximum and minimum values on the y-axis are indicated and can be reset. Resetting these axis limits will in turn automatically reset the tick-mark interval and number of tick marks. Greater flexibility for setting the tick marks is planned for future releases. Further options for customising the graph, including adjusting the size of the fonts, and the size of the images, are available from Options ~ Graphics .