While there are a number of leading forecast producing centres around the world they all have a varying degree of skill depending on the location and time of the year. Here we will evaluate some of the worlds leading seasonal forecasts to enable users to see if there is any consensus any/or how each model have performed in the past for this time of year.
For each model the skill is calculated by comparing the modelled hindcasts with the observed values for the same region and season using the the Australian Gridded Climate Data. For the current set of models the Skill is calculated using the hindcast values from 1993-2016.
Revised “LEPS” Scores for Assessing Climate Model Simulations and Long-Range Forecasts - J. M. Potts; C. K. Folland; I. T. Jolliffe; D. Sexton J. Climate (1996) 9 (1): 34–53.
* Please note that there are many different skills testing algorithms which can be used in this framework
As some models perform better (or worse) in some regions and at certain times of the year it is not always appropriate to simply combine all the models (either by averaging or combining all ensembles).
By combining all the available models (shown above) we have selected the output with the highest hindcast skill for each region (grid point) and time of year and combined them into a multi-model forecast (prototype product).