open access

https://doi.org/10.14943/gbhu.85.1

https://hdl.handle.net/2115/84678

The improvement of post-processing with the ensemble spread

日本語

2022-03-26

北海道大学大学院理学研究院

Geophysical bulletin of Hokkaido University

85

1-10

Post-processing is an inevitable procedure to statistically correct systematic errors in a numerical model product. Karman filtering, a post-processing technique, often ameliorated the prediction skill by overlearning due to large random errors. This study conducted an experiment to determine the observation error variance from the ensemble spread, based on an idealised numerical model of Lorenz 96. The results suggested that the overlearning was mitigated in spite of synchronisation of systematic errors and the prediction skill was higher than in previous method.

紀要論文

Version of Record

Creative Commons Attribution-NonCommercial 4.0 International

0439-3503

AN0008976X