The discrete brier and ranked probability skill scores

By A. Weigel, Markus Liniger, C. Appenzeller. 2007

256 citations recorded by the source corpus.

Subfields: Atmospheric Science, Global and Planetary Change

View Paper: https://www.semanticscholar.org/paper/014f1caaaf7112d70d774365560cc4b0d3cb6a71

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In Atmospheric Science

In Global and Planetary Change

Citations in the corpus

Bridging the gap between weather and seasonal forecasting: intraseasonal forecasting for Australia (2011, unknown): “137: 673–689 (2011) 676 D. Hudson et al. (Mason and Stephenson, 2008; Weigel et al., 2007).”
Assessment of representations of model uncertainty in monthly and seasonal forecast ensembles (2011, background): “However, all these statistical measures strongly depend on the size of the ensemble system [see Doblas‐Reyes et al., 2010] even though some attempts were discussed to de‐bias the BSS [Muller et al., 2005; Weigel et al., 2007 ].”
Description and validation of a two-step analogue/regression downscaling method (2013, methodology): “Daily precipitation simulated by numerical models generally has very high MAE in comparison with other variables (Hamill 1999; McBride and Ebert 2000), thus some authors use verification methods such as Ranked Probability Scores (Hersbach 2000; Weigel et al. 2006).”
Generalization of the Ignorance Score: Continuous Ranked Version and Its Decomposition (2012, methodology): “Weijs et al. (2010a) refined the IGN score as relative entropy between the forecasted f and observed o distribution (calling it divergence score).”
Application of machine learning to construction injury prediction (2016, background): “(2), the Rank Probability Score (RPS, [71]) measures the squared error between the cumulative probabilitymass function of a given forecast and that of a given observation.”
Forecast verification: current status and future directions (2008, background): “This issue was also discussed by Weigel et al. (2007) in the context of the rank probability skill score and small ensemble sizes.”
Can multi‐model combination really enhance the prediction skill of probabilistic ensemble forecasts? (2007, methodology): “The debiased ranked probability skill score, RPSSD , (Weigel et al., 2007) is used to verify the forecasts.”
Skill of Multimodel ENSO Probability Forecasts (2008, background): “Although Weigel et al. (2007) use a different set of assumptions, their debiased RPSS agrees to leading order with the result here.”