Verification Tutorial

Notice : A new user-customized APCC seasonal prediction (MME) and verification services based on platform technology has been opened as beta service (Refer to current APCC CLIK service : https://clik.apcc21.org). Please leave your any questions and feedbacks about the new service to APCC Help Desk.

Lead Month
Year / Month
Skills
Variable
Models


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Success Rate(SR)

SR is the fraction or percentage of success among a number of attempts. CLIK provides a simple success rate as the DMME verification score.

  •       ~ 0.33 : Poor skill region
  • 0.33 ~ 0.66 : Reasonable skill region
  • 0.66 ~       : High skill region
  • Anomaly Correlation Coefficient(ACC)

    ACC is one of the most widely used measures in the verification of spatial fields and is the correlation between anomalies of forecasts and those of verifying values with the reference values, such as climatological values.

    Heidke Skill Score(HSS)

    HSS is commonly used skill score for the verification of categorical probabilistic forecast. Measuring the fractional improvement of the forecast over random forecast.

    Relative Operating Characteristics(ROC) Curve

    The ROC curve indicates the degree of correct probabilistic discrimination in a set of forecasts. Discrimination is the ability to distinguish one categorical outcome from another even if the forecast probabilities have biases or calibration problems.