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On the Assessment of Reliability in Probabilistic Hydrometeorological Event Forecasting

Description: 
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.
Record Format: 
application/pdf
2015-06-01T07:00:00Z
Subject: 
Hydrologic models
Uncertainty -- Mathematical models
Civil Engineering
Environmental Engineering
Hydraulic Engineering
Type: 
text
Raw Url: 
http://pdxscholar.library.pdx.edu/do/oai/?metadataPrefix=&verb=GetRecord&identifier=oai:pdxscholar.library.pdx.edu:cengin_fac-1307
Source: 
Civil and Environmental Engineering Faculty Publications and Presentations
Repository Record Id: 
oai:pdxscholar.library.pdx.edu:cengin_fac-1307
SetSpec: 
publication:communities
publication:mcecs
publication:cengin_fac
publication:cengin
Record Title: 
On the Assessment of Reliability in Probabilistic Hydrometeorological Event Forecasting
https://pdxscholar.library.pdx.edu/cengin_fac/294
info:doi/10.1002/2014WR016617
https://pdxscholar.library.pdx.edu/context/cengin_fac/article/1307/viewcontent/DeChant_et_al_2015_Water_Resources_Research.pdf
Database: 
Resource OE Format: 
randomness