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.
...
- For medium range forecasts the anomaly correlation coefficient is evaluated between:
- the mean of the anomaly of the forecast product relative to the medium range model climate (M-climate) and
- the mean of the anomaly of the verifying CTRL analysis relative to the medium range model climate (M-climate).
- For extended range products the correlation is evaluated between:
- the mean of the anomaly of the forecast product measured relative to the extended range model climate (ER-M-climate) and
- the mean of the anomaly of the verifying the CTRL analysis relative to the extended range model climate (ER-M-climate).
- For seasonal products the correlation is evaluated between:
- the mean of the anomaly of the forecast product relative to the a model climatology based on the ERA-interim re-analysis (based on the period 1993-2016) and
- the mean of the anomaly of the verifying observations or reanalysis relative to the seasonal model climate (S-M-Climate).
The The medium range model climatemodel climate (M-climate) and and extended range model climate (ER-M-climate) are are based on reon re-forecasts spanning the last 20 years, which used the ERA5 reanalysis for their initialisation
...
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).
...