Symposium on Linkages among Societal Benefits, Prediction Systems and Process Studies for 1-14 day Weather Forecasts

3.1

Does society benefit from very long range day-to-day weather forecasts?

Harvey Stern, Bureau of Meteorology, Melbourne, Vic., Australia

A "real-time" trial of a methodology utilised to generate Day-1 to Day-7 forecasts, by mechanically integrating judgmental (human) and automated predictions, has been ongoing since 20 August 2005. It has been found that the sets of combined forecasts are not only more accurate, but also are more consistent from one day to the next, than either individual set of forecasts.

Since 20 August 2006, forecasts have also been generated for beyond Day-7 (Day-8 to Day-10) by mechanically integrating automated predictions with climate normals. After 285 days, to 31 May 2007, overall, Day-8 forecasts explained 11.0% of the variance, Day-9 forecasts explained 6.3% of the variance, and Day-10 forecasts explained 3.0% of the variance.

However, for these very long range day-to-day forecasts, the variance explained was mainly for the temperature components. Specifically:

o For Day-8, Quantitative Precipitation Forecasts (QPFs) explained 1.9% of the observed variance, Descriptive Forecasts of key Weather Elements (DFWEs) explained 4.4% of the observed variance, whilst Minimum Temperature Forecasts (MINFs) explained 19.7% of the observed variance and Maximum Temperature Forecasts (MAXFs) explained 17.9% of the observed variance.

o For Day-9, QPFs explained 1.0% of the observed variance, DFWEs explained 4.3% of the observed variance, whilst MINFs explained 9.8% of the observed variance and MAXFs explained 10.3% of the observed variance.

o For Day-10, QPFs explained less than 0.1% of the observed variance, DFWEs explained 0.2% of the observed variance, whilst MINFs explained 7.4% of the observed variance and MAXFs explained 4.5% of the observed variance.

The following question arises from the relatively low level of skill that very long range day-to-day forecasts display:

Does society gain any benefit from very long range day-to-day forecasts, and might it even be suggested that society actually suffers loss from them being issued, on account of false expectations about their accuracy being raised?

A reply to the first part of the question, as to what is the benefit that society gains from very long range forecasts, may be established from the theoretical "fair value" prices of option contracts (weather derivatives) that one is required to purchase in order to protect against the eventuality that the forecasts might prove to be incorrect.

A reply to the second part of the question, as to whether society actually might even suffer loss from very long range forecasts, may be responded to in the negative, provided users of these forecasts are provided with suitable verification statistics about their accuracy.

extended abstract  Extended Abstract (464K)

wrf recording  Recorded presentation

Supplementary URL: http://www.bom.gov.au

Session 3, Providing forecasts to support user decisions
Wednesday, 23 January 2008, 4:00 PM-5:30 PM, 214

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