Abstract
An idealized model for error growth is used to discuss numerical weather prediction model forecasts of time averages ranging from 0 to 30 days in duration at lags of 0 to 30 days. The idealized model allows a simple assessment of how the initial error, error growth rate and serial correlation, influence a forecast model’s prediction of a time average. The simplified nature of the idealized model also allows an easy demonstration of how various filters applied to the raw numerical predictions can help to improve forecast skill.
DOI: https://doi.org/10.3402/tellusa.v39i5.11775 | Journal eISSN: 3035-9554
Language: English
Page range: 492 - 499
Submitted on: Jun 19, 1986
Accepted on: Dec 11, 1986
Published on: Jan 1, 1987
Published by: Stockholm University Press
In partnership with: Paradigm Publishing Services
© 1987 John O. Roads, published by Stockholm University Press
This work is licensed under the Creative Commons Attribution 4.0 License.