On May 8th 2018 the Bureau’s forecast for cumulative rainfall in Melbourne over the following five days was between 35mm and 144mm. The actual received was 39mm. This was, of course, within that wide band but towards the lower end. The mean of the range was 89.5mm so on that basis, the forecast error was quite large. That may have been disappointing for farmers but a relief for emergency services planners. The largest forecast error for any of those days was for the Friday: the forecast was for 25 to 80, but only 8.4 was received.
It would be helpful for planners to have a probability distribution. For example, was the upper limit of the five day forecast (144mm) a one in 100 chance or a one in ten chance?
This forecasting error might be understandable if it was an isolated incident. Melbourne is a difficult location to forecast due to high variability. But this was not an isolated incident.
Only a few months earlier, in December 2017, an unprecedented rainfall event was predicted but did not materialise. In January 2015, another such prediction was made and did not materialise.
These seem to be systematic failures rather than random errors, suggesting that the Bureaus models are not sensitive to an important driving force.
What is that driving force? Find out in my book “Forecasting: the essential skills”. It describes these incidents in more detail and contains my suggestion as to what the Factor X is. The book also reviews forecasting skill in economic forecasting and political forecasting as well as weather and climate forecasting.