Open AccessForecast verification: current status and future directions
Author(s) -
Casati B.,
Wilson L. J.,
Stephenson D. B.,
Nurmi P.,
Ghelli A.,
Pocernich M.,
Damrath U.,
Ebert E. E.,
Brown B. G.,
Mason S.
Publication year - 2008
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.52
Subject(s) - computer science , forecast verification , event (particle physics) , process (computing) , functional verification , data verification , verification and validation of computer simulation models , software verification , data science , operations research , formal verification , data mining , software , forecast skill , software development , geography , meteorology , statistics , physics , mathematics , engineering , software construction , algorithm , quantum mechanics , programming language , operating system
Research and development of new verification strategies and reassessment of traditional forecast verification methods has received a great deal of attention from the scientific community in the last decade. This scientific effort has arisen from the need to respond to changes encompassing several aspects of the verification process, such as the evolution of forecasting systems, or the desire for more meaningful verification approaches that address specific forecast user requirements. Verification techniques that account for the spatial structure and the presence of features in forecast fields, and which are designed specifically for high‐resolution forecasts have been developed. The advent of ensemble forecasts has motivated the re‐evaluation of some of the traditional scores and the development of new verification methods for probability forecasts. The expected climatological increase of extreme events and their potential socio‐economical impacts have revitalized research studies addressing the challenges concerning extreme event verification. Verification issues encountered in the operational forecasting environment have been widely discussed, verification needs for different user communities have been identified, and models to assess the forecast value for specific users have been proposed. Proper verification practice and correct interpretation of verification statistics has been extensively promoted with recent publications and books, tutorials and workshops, and the development of open‐source software and verification tools. This paper addresses some of the current issues in forecast verification, reviews some of the most recently developed verification techniques, and provides recommendations for future research. Copyright © 2008 Royal Meteorological Society and Crown in the right of Canada.