Page History

The Anomaly Correlation Coefficient (ACC) is one of the most widely used measures in the verification of spatial fields.   It is the spatial correlation between a forecast anomaly relative to climatology, and a verifying analysis anomaly relative to climatology.  ACC represents is a measure of how well the forecast anomalies have represented the observed anomalies and .  It shows how well the predicted values from a forecast model "fit" with the real-life data.  When ACC is calculated for a sequence of forecasts, say at  ACC for a series of forecast lead-times , it is a measure of how well trends in the predicted anomalies follow trends in actual anomalies.

...

 Fig6.2.2-2: Anomaly Correlation Coefficients for 500hPa Geopotential.  HRES in Red, Ensemble control (CTRL) in Purple, Ensemble mean (EM) in Green, An individual ensemble member (PF) in Cyan.    Note the The ACC for ensemble control and HRES are very similar, but the EM .  However, ensemble mean clearly out-performs them and is almost 2 days better than any individual ENS member (e,g, ACC .  ACC of a perturbed member (PF) at Day7 is still being attained by ensemble mean at Day9).  In these graphs HRES has 9Km resolution, the medium range ensemble has 18Km resolution.  

...

The diagrams above show how the Anomaly Correlation Coefficients vary with forecast lead-time.  The ACC scores have steadily improved over the years at all lead-times, reflecting .  This reflects the improvement of input data, analysis techniques and IFS model formulation (See Fig6.2.2-3).

...