Evaluating Seasonal Forecasts

Seasonal forecasts provide a long-range outlook of changes in the Earth system over periods of a few weeks or months, as a result of predictable changes in some of the slow-varying components of the system -Copernicus

Using Copernicus Climate Change Service information - 2023

Seasonal Forecasts

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.

ECMWF forecast
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UKMO forecast
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DWD forecast
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METEO forecast
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CMCC forecast
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NCEP forecast
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JMA forecast
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ECCC CanCM4i forecast
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ECCC GEM5-NEMO forecast
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Hindcast Skill

For each model the skill is calculated by comparing the modelled hindcasts with the observed values for the same region and season using Gridded Climate Data. For the current set of models the Skill is calculated using the hindcast values from 1993-2016.

  • For the Chance of Above the Median forecasts the skill is determined by using a Hit Score (Percent correct) where a forecasts can be either Right or Wrong (categorical)
  • For the Anomaly Mean and Tercile forecasts the skill is calculated using the Mean Absolute Error (MAE) / Root Mean Square Error (RMSE).

* Please note that there are many different skills testing algorithms which can be used in this framework

ECMWF skill
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UKMO skill
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DWD skill
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METEO skill
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CMCC skill
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NCEP skill
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JMA skill
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ECCC CanCM4i skill
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ECCC GEM5-NEMO skill
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