Implementation and testing of a simple data assimilation algorithm in the regional air pollution forecast model, DEOM
A simple data assimilation algorithm based on statistical interpolation has been developed and coupled to a long-range chemistry transport model, the Danish Eulerian Operational Model (DEOM), applied for air pollution forecasting at the National Environmental Research Institute (NERI), Denmark. In t...
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ftdoajarticles:oai:doaj.org/article:18bcec8c62d24e4082168317595d5b39 2023-05-15T17:14:17+02:00 Implementation and testing of a simple data assimilation algorithm in the regional air pollution forecast model, DEOM J. Frydendall J. Brandt J. H. Christensen 2009-08-01T00:00:00Z https://doaj.org/article/18bcec8c62d24e4082168317595d5b39 EN eng Copernicus Publications http://www.atmos-chem-phys.net/9/5475/2009/acp-9-5475-2009.pdf https://doaj.org/toc/1680-7316 https://doaj.org/toc/1680-7324 1680-7316 1680-7324 https://doaj.org/article/18bcec8c62d24e4082168317595d5b39 Atmospheric Chemistry and Physics, Vol 9, Iss 15, Pp 5475-5488 (2009) Physics QC1-999 Chemistry QD1-999 article 2009 ftdoajarticles 2022-12-31T11:56:27Z A simple data assimilation algorithm based on statistical interpolation has been developed and coupled to a long-range chemistry transport model, the Danish Eulerian Operational Model (DEOM), applied for air pollution forecasting at the National Environmental Research Institute (NERI), Denmark. In this paper, the algorithm and the results from experiments designed to find the optimal setup of the algorithm are described. The algorithm has been developed and optimized via eight different experiments where the results from different model setups have been tested against measurements from the EMEP (European Monitoring and Evaluation Programme) network covering a half-year period, April–September 1999. The best performing setup of the data assimilation algorithm for surface ozone concentrations has been found, including the combination of determining the covariances using the Hollingsworth method, varying the correlation length according to the number of adjacent observation stations and applying the assimilation routine at three successive hours during the morning. Improvements in the correlation coefficient in the range of 0.1 to 0.21 between the results from the reference and the optimal configuration of the data assimilation algorithm, were found. The data assimilation algorithm will in the future be used in the operational THOR integrated air pollution forecast system, which includes the DEOM. Article in Journal/Newspaper National Environmental Research Institute Directory of Open Access Journals: DOAJ Articles Hollingsworth ENVELOPE(50.367,50.367,-67.250,-67.250) Neri ENVELOPE(156.206,156.206,61.801,61.801) |
institution |
Open Polar |
collection |
Directory of Open Access Journals: DOAJ Articles |
op_collection_id |
ftdoajarticles |
language |
English |
topic |
Physics QC1-999 Chemistry QD1-999 |
spellingShingle |
Physics QC1-999 Chemistry QD1-999 J. Frydendall J. Brandt J. H. Christensen Implementation and testing of a simple data assimilation algorithm in the regional air pollution forecast model, DEOM |
topic_facet |
Physics QC1-999 Chemistry QD1-999 |
description |
A simple data assimilation algorithm based on statistical interpolation has been developed and coupled to a long-range chemistry transport model, the Danish Eulerian Operational Model (DEOM), applied for air pollution forecasting at the National Environmental Research Institute (NERI), Denmark. In this paper, the algorithm and the results from experiments designed to find the optimal setup of the algorithm are described. The algorithm has been developed and optimized via eight different experiments where the results from different model setups have been tested against measurements from the EMEP (European Monitoring and Evaluation Programme) network covering a half-year period, April–September 1999. The best performing setup of the data assimilation algorithm for surface ozone concentrations has been found, including the combination of determining the covariances using the Hollingsworth method, varying the correlation length according to the number of adjacent observation stations and applying the assimilation routine at three successive hours during the morning. Improvements in the correlation coefficient in the range of 0.1 to 0.21 between the results from the reference and the optimal configuration of the data assimilation algorithm, were found. The data assimilation algorithm will in the future be used in the operational THOR integrated air pollution forecast system, which includes the DEOM. |
format |
Article in Journal/Newspaper |
author |
J. Frydendall J. Brandt J. H. Christensen |
author_facet |
J. Frydendall J. Brandt J. H. Christensen |
author_sort |
J. Frydendall |
title |
Implementation and testing of a simple data assimilation algorithm in the regional air pollution forecast model, DEOM |
title_short |
Implementation and testing of a simple data assimilation algorithm in the regional air pollution forecast model, DEOM |
title_full |
Implementation and testing of a simple data assimilation algorithm in the regional air pollution forecast model, DEOM |
title_fullStr |
Implementation and testing of a simple data assimilation algorithm in the regional air pollution forecast model, DEOM |
title_full_unstemmed |
Implementation and testing of a simple data assimilation algorithm in the regional air pollution forecast model, DEOM |
title_sort |
implementation and testing of a simple data assimilation algorithm in the regional air pollution forecast model, deom |
publisher |
Copernicus Publications |
publishDate |
2009 |
url |
https://doaj.org/article/18bcec8c62d24e4082168317595d5b39 |
long_lat |
ENVELOPE(50.367,50.367,-67.250,-67.250) ENVELOPE(156.206,156.206,61.801,61.801) |
geographic |
Hollingsworth Neri |
geographic_facet |
Hollingsworth Neri |
genre |
National Environmental Research Institute |
genre_facet |
National Environmental Research Institute |
op_source |
Atmospheric Chemistry and Physics, Vol 9, Iss 15, Pp 5475-5488 (2009) |
op_relation |
http://www.atmos-chem-phys.net/9/5475/2009/acp-9-5475-2009.pdf https://doaj.org/toc/1680-7316 https://doaj.org/toc/1680-7324 1680-7316 1680-7324 https://doaj.org/article/18bcec8c62d24e4082168317595d5b39 |
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1766071583571443712 |