Open AccessInformation gain as a score for probabilistic forecasts
Author(s) -
Peirolo Riccardo
Publication year - 2011
Publication title -
meteorological applications
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.672
H-Index - 59
eISSN - 1469-8080
pISSN - 1350-4827
DOI - 10.1002/met.188
Subject(s) - probabilistic logic , geopotential height , measure (data warehouse) , information gain , geopotential , econometrics , ignorance , computer science , meteorology , environmental science , statistics , climatology , mathematics , data mining , geography , geology , precipitation , political science , law
A measure of the information added by a probabilistic forecast to that contained in the climatological distribution is presented in this paper. This measure, called information gain, is mathematically closely related to the traditional ignorance score, but is more intuitive. Its advantages over other scores for probabilistic forecasts are also shown. The information gain score is tested on ECMWF ensemble forecasts of 500 hPa geopotential and 850 hPa temperature. The trends observed are in good agreement with those seen in other verification measures applied to the same data. In particular, the information gain decays with increasing lead time and increases over the years, in agreement with the improvement of the model. Copyright © 2010 Royal Meteorological Society