The properties of sensitive area predictions based on the ensemble transform Kalman filter (ETKF)

Abstract The spatial characteristics of ensemble transform Kalman filter (ETKF) sensitive area predictions (SAPs) are explored using ensemble forecasts from the European Centre for Medium‐Range Weather Forecasts for the period of the 2003 North Atlantic THORPEX Regional Campaign. The ensemble size n...

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Published in:Quarterly Journal of the Royal Meteorological Society
Main Authors: Petersen, G. N., Majumdar, S. J., Thorpe, A. J.
Format: Article in Journal/Newspaper
Language:English
Published: Wiley 2007
Subjects:
Online Access:http://dx.doi.org/10.1002/qj.61
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spelling crwiley:10.1002/qj.61 2024-06-02T08:11:28+00:00 The properties of sensitive area predictions based on the ensemble transform Kalman filter (ETKF) Petersen, G. N. Majumdar, S. J. Thorpe, A. J. 2007 http://dx.doi.org/10.1002/qj.61 https://api.wiley.com/onlinelibrary/tdm/v1/articles/10.1002%2Fqj.61 https://rmets.onlinelibrary.wiley.com/doi/pdf/10.1002/qj.61 en eng Wiley http://onlinelibrary.wiley.com/termsAndConditions#vor Quarterly Journal of the Royal Meteorological Society volume 133, issue 624, page 697-710 ISSN 0035-9009 1477-870X journal-article 2007 crwiley https://doi.org/10.1002/qj.61 2024-05-03T10:57:22Z Abstract The spatial characteristics of ensemble transform Kalman filter (ETKF) sensitive area predictions (SAPs) are explored using ensemble forecasts from the European Centre for Medium‐Range Weather Forecasts for the period of the 2003 North Atlantic THORPEX Regional Campaign. The ensemble size necessary for a robust sensitive area prediction is found to be surprisingly small: a 10‐member ensemble is capable of replicating approximately the same sensitive area structure as a 50‐member ensemble. This result is corroborated by the fact that the leading eigenvector of the ensemble perturbations explains over 70% of the ensemble variance and possesses a nearly identical spatial structure regardless of the ensemble size. The structures of the SAPs were found to vary with the lead‐time between the ensemble initialization and the adaptive observing time, indicating the necessity of using as recent an ensemble as possible in ensemble‐based sensitive area predictions. The ETKF SAPs exhibit similar structures at different levels in the atmosphere and there is no indication of a vertical tilt. A relationship is found between the SAPs and the zonal wind, horizontal temperature gradient and the Eady index, indicating that the ETKF identifies regions with significant gradients in the mass‐momentum field as regions of large initial error or large error growth. Copyright © 2007 Royal Meteorological Society Article in Journal/Newspaper North Atlantic Wiley Online Library Quarterly Journal of the Royal Meteorological Society 133 624 697 710
institution Open Polar
collection Wiley Online Library
op_collection_id crwiley
language English
description Abstract The spatial characteristics of ensemble transform Kalman filter (ETKF) sensitive area predictions (SAPs) are explored using ensemble forecasts from the European Centre for Medium‐Range Weather Forecasts for the period of the 2003 North Atlantic THORPEX Regional Campaign. The ensemble size necessary for a robust sensitive area prediction is found to be surprisingly small: a 10‐member ensemble is capable of replicating approximately the same sensitive area structure as a 50‐member ensemble. This result is corroborated by the fact that the leading eigenvector of the ensemble perturbations explains over 70% of the ensemble variance and possesses a nearly identical spatial structure regardless of the ensemble size. The structures of the SAPs were found to vary with the lead‐time between the ensemble initialization and the adaptive observing time, indicating the necessity of using as recent an ensemble as possible in ensemble‐based sensitive area predictions. The ETKF SAPs exhibit similar structures at different levels in the atmosphere and there is no indication of a vertical tilt. A relationship is found between the SAPs and the zonal wind, horizontal temperature gradient and the Eady index, indicating that the ETKF identifies regions with significant gradients in the mass‐momentum field as regions of large initial error or large error growth. Copyright © 2007 Royal Meteorological Society
format Article in Journal/Newspaper
author Petersen, G. N.
Majumdar, S. J.
Thorpe, A. J.
spellingShingle Petersen, G. N.
Majumdar, S. J.
Thorpe, A. J.
The properties of sensitive area predictions based on the ensemble transform Kalman filter (ETKF)
author_facet Petersen, G. N.
Majumdar, S. J.
Thorpe, A. J.
author_sort Petersen, G. N.
title The properties of sensitive area predictions based on the ensemble transform Kalman filter (ETKF)
title_short The properties of sensitive area predictions based on the ensemble transform Kalman filter (ETKF)
title_full The properties of sensitive area predictions based on the ensemble transform Kalman filter (ETKF)
title_fullStr The properties of sensitive area predictions based on the ensemble transform Kalman filter (ETKF)
title_full_unstemmed The properties of sensitive area predictions based on the ensemble transform Kalman filter (ETKF)
title_sort properties of sensitive area predictions based on the ensemble transform kalman filter (etkf)
publisher Wiley
publishDate 2007
url http://dx.doi.org/10.1002/qj.61
https://api.wiley.com/onlinelibrary/tdm/v1/articles/10.1002%2Fqj.61
https://rmets.onlinelibrary.wiley.com/doi/pdf/10.1002/qj.61
genre North Atlantic
genre_facet North Atlantic
op_source Quarterly Journal of the Royal Meteorological Society
volume 133, issue 624, page 697-710
ISSN 0035-9009 1477-870X
op_rights http://onlinelibrary.wiley.com/termsAndConditions#vor
op_doi https://doi.org/10.1002/qj.61
container_title Quarterly Journal of the Royal Meteorological Society
container_volume 133
container_issue 624
container_start_page 697
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