Estimating forecast model bias in coupled global and limited-area models

Matthew Kretschmer; Brian R. Hunt; Edward Ott

doi:10.3402/tellusa.v67.28040

Estimating forecast model bias in coupled global and limited-area models

Tellus

Volume 67 (2015): Issue 1

By: Matthew Kretschmer, Brian R. Hunt and Edward Ott

Open Access

|Dec 2015

Abstract

Idealised perfect model experiments suggest that performing data assimilation on a ‘composite’ state vector, constructed from global and limited-area model states, can be beneficial to both model states. Here, an illustrative scheme is implemented to account for systematic forecast errors attributed to the imperfect model dynamics. Results from numerical experiments suggest that even simple bias correction schemes can correct forecast errors in composite states.

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Articles in this issue

DOI: https://doi.org/10.3402/tellusa.v67.28040 | Journal eISSN: 3035-9554

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Language: English

Page range: 28040 - 28040

Submitted on: Mar 31, 2015

Accepted on: Nov 2, 2015

Published on: Dec 1, 2015

Published by: Stockholm University Press

In partnership with: Paradigm Publishing Services

Keywords:

ensemble Kalman Filter,

limited-area models,

composite state,

bias correction

© 2015 Matthew Kretschmer, Brian R. Hunt, Edward Ott, published by Stockholm University Press
This work is licensed under the Creative Commons Attribution 4.0 License.

Volume 67 (2015): Issue 1