Sponsor
The authors would like to acknowledge the financial support provided by NOAA-MAPP grant NA11OAR4310140 and also NOAACSTAR grant NA11NWS4680002.
Published In
Water Resources Research
Document Type
Article
Publication Date
6-2015
Subjects
Hydrologic models, Uncertainty -- Mathematical models
Abstract
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.
DOI
10.1002/2014WR016617
Persistent Identifier
http://archives.pdx.edu/ds/psu/16580
Citation Details
DeChant, C. M., and H. Moradkhani (2015), On the Assessment of Reliability in Probabilistic Hydrometeorological Event Forecasting, Water Resour. Res., 51, 3867–3883.
Included in
Civil Engineering Commons, Environmental Engineering Commons, Hydraulic Engineering Commons
Description
This is the publisher's final pdf. Originally published in Water Resources Research and is copyrighted by American Geophysical Union (http://www.agu.org/). The article is available at: http://dx.doi.org/10.1002/2014WR016617