Quantifying Terrestrial and Aquatic Ecosystem Methane Emissions with Process-based Biogeochemistry and Atmospheric Transport and Chemistry Models
To improve the quantification of methane emissions from Arctic wetlands and lakes, an integrated modeling framework was developed. It includes a newly developed process-based lake biogeochemical model and a widely used 4-D VAR inversion algorithm implemented with the nested grid high-resolution GEOS...
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ftpurdueuniv:oai:docs.lib.purdue.edu:open_access_dissertations-2706 2023-07-02T03:31:09+02:00 Quantifying Terrestrial and Aquatic Ecosystem Methane Emissions with Process-based Biogeochemistry and Atmospheric Transport and Chemistry Models Tan, Zeli 2015-01-01T08:00:00Z application/pdf https://docs.lib.purdue.edu/open_access_dissertations/1490 https://docs.lib.purdue.edu/context/open_access_dissertations/article/2706/viewcontent/Tan_purdue_0183D_19336.pdf unknown Purdue University https://docs.lib.purdue.edu/open_access_dissertations/1490 https://docs.lib.purdue.edu/context/open_access_dissertations/article/2706/viewcontent/Tan_purdue_0183D_19336.pdf Open Access Dissertations arctic lakes atmospheric inverse modeling biogeochemical models methane emissions text 2015 ftpurdueuniv 2023-06-12T21:16:33Z To improve the quantification of methane emissions from Arctic wetlands and lakes, an integrated modeling framework was developed. It includes a newly developed process-based lake biogeochemical model and a widely used 4-D VAR inversion algorithm implemented with the nested grid high-resolution GEOS-Chem Adjoint model. Text Arctic Purdue University: e-Pubs Arctic |
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Purdue University: e-Pubs |
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ftpurdueuniv |
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topic |
arctic lakes atmospheric inverse modeling biogeochemical models methane emissions |
spellingShingle |
arctic lakes atmospheric inverse modeling biogeochemical models methane emissions Tan, Zeli Quantifying Terrestrial and Aquatic Ecosystem Methane Emissions with Process-based Biogeochemistry and Atmospheric Transport and Chemistry Models |
topic_facet |
arctic lakes atmospheric inverse modeling biogeochemical models methane emissions |
description |
To improve the quantification of methane emissions from Arctic wetlands and lakes, an integrated modeling framework was developed. It includes a newly developed process-based lake biogeochemical model and a widely used 4-D VAR inversion algorithm implemented with the nested grid high-resolution GEOS-Chem Adjoint model. |
format |
Text |
author |
Tan, Zeli |
author_facet |
Tan, Zeli |
author_sort |
Tan, Zeli |
title |
Quantifying Terrestrial and Aquatic Ecosystem Methane Emissions with Process-based Biogeochemistry and Atmospheric Transport and Chemistry Models |
title_short |
Quantifying Terrestrial and Aquatic Ecosystem Methane Emissions with Process-based Biogeochemistry and Atmospheric Transport and Chemistry Models |
title_full |
Quantifying Terrestrial and Aquatic Ecosystem Methane Emissions with Process-based Biogeochemistry and Atmospheric Transport and Chemistry Models |
title_fullStr |
Quantifying Terrestrial and Aquatic Ecosystem Methane Emissions with Process-based Biogeochemistry and Atmospheric Transport and Chemistry Models |
title_full_unstemmed |
Quantifying Terrestrial and Aquatic Ecosystem Methane Emissions with Process-based Biogeochemistry and Atmospheric Transport and Chemistry Models |
title_sort |
quantifying terrestrial and aquatic ecosystem methane emissions with process-based biogeochemistry and atmospheric transport and chemistry models |
publisher |
Purdue University |
publishDate |
2015 |
url |
https://docs.lib.purdue.edu/open_access_dissertations/1490 https://docs.lib.purdue.edu/context/open_access_dissertations/article/2706/viewcontent/Tan_purdue_0183D_19336.pdf |
geographic |
Arctic |
geographic_facet |
Arctic |
genre |
Arctic |
genre_facet |
Arctic |
op_source |
Open Access Dissertations |
op_relation |
https://docs.lib.purdue.edu/open_access_dissertations/1490 https://docs.lib.purdue.edu/context/open_access_dissertations/article/2706/viewcontent/Tan_purdue_0183D_19336.pdf |
_version_ |
1770275417858506752 |