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On the assessment of reliability in probabilistic hydrometeorological event forecasting
Author(s) -
DeChant Caleb M.,
Moradkhani Hamid
Publication year - 2015
Publication title -
water resources research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.863
H-Index - 217
eISSN - 1944-7973
pISSN - 0043-1397
DOI - 10.1002/2014wr016617
Subject(s) - hydrometeorology , probabilistic logic , reliability (semiconductor) , event (particle physics) , brier score , binomial distribution , poisson distribution , computer science , probabilistic forecasting , scoring rule , statistics , econometrics , forecast verification , reliability engineering , mathematics , forecast skill , meteorology , engineering , geography , precipitation , power (physics) , physics , quantum mechanics
Probabilistic forecasts are commonly used to communicate uncertainty in the occurrence of hydrometeorological events. Although probabilistic forecasting is common, conventional methods for assessing the reliability of these forecasts are approximate. Among the most common methods for assessing reliability, the decomposed Brier Score and Reliability Diagram treat an observed string of events as samples from multiple Binomial distributions, but this is an approximation of the forecast reliability, leading to unnecessary loss of information. This article suggests testing the hypothesis of reliability via the Poisson‐Binomial distribution, which is a generalized solution to the Binomial distribution, providing a more accurate model of the probabilistic event forecast verification setting. Further, a two‐stage approach to reliability assessment is suggested to identify errors in the forecast related to both bias and overly/insufficiently sharp forecasts. Such a methodology is shown to more effectively distinguish between reliable and unreliable forecasts, leading to more robust probabilistic forecast verification.