The Potential Impact of Using Persistence as a Reference Forecast on Perceived Forecast Skill

Abstract

Skill is defined as actual forecast performance relative to the performance of a reference forecast. It is shown that the choice of reference (e.g., random or persistence) can affect the perceived performance of the forecast system. Two scores, the equitable threat score (ETS) and the odds ratio benefit skill score (ORBSS), were chosen to show the impact of using a persistence forecast, first using some simple hypothetical scenarios and second for actual forecasts from the Met Office Unified Model (UM) of precipitation, total cloud cover, and visibility during 2006. Overall persistence offers a sterner test of true forecast added value and accuracy, but using a more realistic reference may come at a cost. Using persistence introduces an additional degree of freedom to the skill assessment, which may be rather variable for ?weather parameters.? Ultimately, the aim of any forecasting system should be to achieve a substantive separation between the inherent skill of the reference (which represents basic predictability) and the actual forecast.