Nature research paper: Global seasonal forecasts of marine heatwaves
, including it is non-degenerate, meaning that it does not trend towards a meaningless limit as event rarity increases, it is base-rate independent, meaning that it is not influenced by changes in the frequency of events, and it is equitable, meaning its expected value is the same for random forecasts, regardless of what method is used to generate the random forecasts$${\rm{SEDI}}=\frac{{\rm{\log }}F-{\rm{\log }}H-{\rm{loglog}}\left+{\rm{\log }}}{{\rm{\log }}F+{\rm{\log...
For completeness, we also calculate two additional forecast skill metrics: the Brier skill score and forecast accuracy. The Brier score is an estimate of the mean square error of the probabilistic forecast:is the total number of forecasts being evaluated,is the observed probability, which is either zero or one . The Brier skill score normalizes the Brier score relative to the skill of a reference forecast :Here the reference forecast is simply the climatological rate of MHW occurrence .
Forecast accuracy is included as a common and easily understandable skill metric; it is simply the fraction of forecasts that are correct:For events that occur on average 10% of the time, the forecast accuracy for random forecasts is 0.82. Thus, MHW forecast accuracy above 0.82 indicates skill better than random chance.
Significance of forecast skill metrics is quantified using a Monte Carlo simulation with block bootstrapping. Specifically, for a given grid cell we calculate the MHW decorrelation time scale,from the observed MHW time series and concatenate them to create a forecast of length 360 months . This process is repeated to create 1,000 random forecasts, and forecast skill is calculated for each one.
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