Upscaling Wetland Methane Emissions From the FLUXNET‐CH4 Eddy Covariance Network (UpCH4 v1.0): Model Development, Network Assessment, and Budget Comparison

Wetlands are responsible for 20%–31% of global methane (CH4) emissions and account for a large source of uncertainty in the global CH4 budget. Data-driven upscaling of CH4 fluxes from eddy covariance measurements can provide new and independent bottom-up estimates of wetland CH4 emissions. Here, we...

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Published in:AGU Advances
Main Authors: McNicol, G., Fluet‐Chouinard, E., Ouyang, Z., Knox, S., Zhang, Z., Aalto, T., Bansal, S., Chang, K., Chen, M., Delwiche, K., Feron, S., Goeckede, M., Liu, J., Malhotra, A., Melton, J., Riley, W., Vargas, R., Yuan, K., Ying, Q., Zhu, Q., Alekseychik, P., Aurela, M., Billesbach, D., Campbell, D., Chen, J., Chu, H., Desai, A., Euskirchen, E., Goodrich, J., Griffis, T., Helbig, M., Hirano, T., Iwata, H., Jurasinski, G., King, J., Koebsch, F., Kolka, R., Krauss, K., Lohila, A., Mammarella, I., Nilson, M., Noormets, A., Oechel, W., Peichl, M., Sachs, T., Sakabe, A., Schulze, C., Sonnentag, O., Sullivan, R., Tuittila, E., Ueyama, M., Vesala, T., Ward, E., Wille, C., Wong, G., Zona, D., Windham‐Myers, L., Poulter, B., Jackson, R.
Format: Article in Journal/Newspaper
Language:unknown
Published: 2023
Subjects:
Online Access:https://gfzpublic.gfz-potsdam.de/pubman/item/item_5022587
https://gfzpublic.gfz-potsdam.de/pubman/item/item_5022587_1/component/file_5022613/5022587.pdf
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spelling ftgfzpotsdam:oai:gfzpublic.gfz-potsdam.de:item_5022587 2023-10-09T21:56:20+02:00 Upscaling Wetland Methane Emissions From the FLUXNET‐CH4 Eddy Covariance Network (UpCH4 v1.0): Model Development, Network Assessment, and Budget Comparison McNicol, G. Fluet‐Chouinard, E. Ouyang, Z. Knox, S. Zhang, Z. Aalto, T. Bansal, S. Chang, K. Chen, M. Delwiche, K. Feron, S. Goeckede, M. Liu, J. Malhotra, A. Melton, J. Riley, W. Vargas, R. Yuan, K. Ying, Q. Zhu, Q. Alekseychik, P. Aurela, M. Billesbach, D. Campbell, D. Chen, J. Chu, H. Desai, A. Euskirchen, E. Goodrich, J. Griffis, T. Helbig, M. Hirano, T. Iwata, H. Jurasinski, G. King, J. Koebsch, F. Kolka, R. Krauss, K. Lohila, A. Mammarella, I. Nilson, M. Noormets, A. Oechel, W. Peichl, M. Sachs, T. Sakabe, A. Schulze, C. Sonnentag, O. Sullivan, R. Tuittila, E. Ueyama, M. Vesala, T. Ward, E. Wille, C. Wong, G. Zona, D. Windham‐Myers, L. Poulter, B. Jackson, R. 2023 application/pdf https://gfzpublic.gfz-potsdam.de/pubman/item/item_5022587 https://gfzpublic.gfz-potsdam.de/pubman/item/item_5022587_1/component/file_5022613/5022587.pdf unknown info:eu-repo/semantics/altIdentifier/doi/10.1029/2023AV000956 https://gfzpublic.gfz-potsdam.de/pubman/item/item_5022587 https://gfzpublic.gfz-potsdam.de/pubman/item/item_5022587_1/component/file_5022613/5022587.pdf info:eu-repo/semantics/openAccess https://creativecommons.org/licenses/by/4.0/ AGU Advances info:eu-repo/semantics/article 2023 ftgfzpotsdam https://doi.org/10.1029/2023AV000956 2023-09-10T23:43:22Z Wetlands are responsible for 20%–31% of global methane (CH4) emissions and account for a large source of uncertainty in the global CH4 budget. Data-driven upscaling of CH4 fluxes from eddy covariance measurements can provide new and independent bottom-up estimates of wetland CH4 emissions. Here, we develop a six-predictor random forest upscaling model (UpCH4), trained on 119 site-years of eddy covariance CH4 flux data from 43 freshwater wetland sites in the FLUXNET-CH4 Community Product. Network patterns in site-level annual means and mean seasonal cycles of CH4 fluxes were reproduced accurately in tundra, boreal, and temperate regions (Nash-Sutcliffe Efficiency ∼0.52–0.63 and 0.53). UpCH4 estimated annual global wetland CH4 emissions of 146 ± 43 TgCH4 y−1 for 2001–2018 which agrees closely with current bottom-up land surface models (102–181 TgCH4 y−1) and overlaps with top-down atmospheric inversion models (155–200 TgCH4 y−1). However, UpCH4 diverged from both types of models in the spatial pattern and seasonal dynamics of tropical wetland emissions. We conclude that upscaling of eddy covariance CH4 fluxes has the potential to produce realistic extra-tropical wetland CH4 emissions estimates which will improve with more flux data. To reduce uncertainty in upscaled estimates, researchers could prioritize new wetland flux sites along humid-to-arid tropical climate gradients, from major rainforest basins (Congo, Amazon, and SE Asia), into monsoon (Bangladesh and India) and savannah regions (African Sahel) and be paired with improved knowledge of wetland extent seasonal dynamics in these regions. The monthly wetland methane products gridded at 0.25° from UpCH4 are available via ORNL DAAC (https://doi.org/10.3334/ORNLDAAC/2253). Article in Journal/Newspaper Tundra GFZpublic (German Research Centre for Geosciences, Helmholtz-Zentrum Potsdam) Nash ENVELOPE(-62.350,-62.350,-74.233,-74.233) Sutcliffe ENVELOPE(-81.383,-81.383,50.683,50.683) AGU Advances 4 5
institution Open Polar
collection GFZpublic (German Research Centre for Geosciences, Helmholtz-Zentrum Potsdam)
op_collection_id ftgfzpotsdam
language unknown
description Wetlands are responsible for 20%–31% of global methane (CH4) emissions and account for a large source of uncertainty in the global CH4 budget. Data-driven upscaling of CH4 fluxes from eddy covariance measurements can provide new and independent bottom-up estimates of wetland CH4 emissions. Here, we develop a six-predictor random forest upscaling model (UpCH4), trained on 119 site-years of eddy covariance CH4 flux data from 43 freshwater wetland sites in the FLUXNET-CH4 Community Product. Network patterns in site-level annual means and mean seasonal cycles of CH4 fluxes were reproduced accurately in tundra, boreal, and temperate regions (Nash-Sutcliffe Efficiency ∼0.52–0.63 and 0.53). UpCH4 estimated annual global wetland CH4 emissions of 146 ± 43 TgCH4 y−1 for 2001–2018 which agrees closely with current bottom-up land surface models (102–181 TgCH4 y−1) and overlaps with top-down atmospheric inversion models (155–200 TgCH4 y−1). However, UpCH4 diverged from both types of models in the spatial pattern and seasonal dynamics of tropical wetland emissions. We conclude that upscaling of eddy covariance CH4 fluxes has the potential to produce realistic extra-tropical wetland CH4 emissions estimates which will improve with more flux data. To reduce uncertainty in upscaled estimates, researchers could prioritize new wetland flux sites along humid-to-arid tropical climate gradients, from major rainforest basins (Congo, Amazon, and SE Asia), into monsoon (Bangladesh and India) and savannah regions (African Sahel) and be paired with improved knowledge of wetland extent seasonal dynamics in these regions. The monthly wetland methane products gridded at 0.25° from UpCH4 are available via ORNL DAAC (https://doi.org/10.3334/ORNLDAAC/2253).
format Article in Journal/Newspaper
author McNicol, G.
Fluet‐Chouinard, E.
Ouyang, Z.
Knox, S.
Zhang, Z.
Aalto, T.
Bansal, S.
Chang, K.
Chen, M.
Delwiche, K.
Feron, S.
Goeckede, M.
Liu, J.
Malhotra, A.
Melton, J.
Riley, W.
Vargas, R.
Yuan, K.
Ying, Q.
Zhu, Q.
Alekseychik, P.
Aurela, M.
Billesbach, D.
Campbell, D.
Chen, J.
Chu, H.
Desai, A.
Euskirchen, E.
Goodrich, J.
Griffis, T.
Helbig, M.
Hirano, T.
Iwata, H.
Jurasinski, G.
King, J.
Koebsch, F.
Kolka, R.
Krauss, K.
Lohila, A.
Mammarella, I.
Nilson, M.
Noormets, A.
Oechel, W.
Peichl, M.
Sachs, T.
Sakabe, A.
Schulze, C.
Sonnentag, O.
Sullivan, R.
Tuittila, E.
Ueyama, M.
Vesala, T.
Ward, E.
Wille, C.
Wong, G.
Zona, D.
Windham‐Myers, L.
Poulter, B.
Jackson, R.
spellingShingle McNicol, G.
Fluet‐Chouinard, E.
Ouyang, Z.
Knox, S.
Zhang, Z.
Aalto, T.
Bansal, S.
Chang, K.
Chen, M.
Delwiche, K.
Feron, S.
Goeckede, M.
Liu, J.
Malhotra, A.
Melton, J.
Riley, W.
Vargas, R.
Yuan, K.
Ying, Q.
Zhu, Q.
Alekseychik, P.
Aurela, M.
Billesbach, D.
Campbell, D.
Chen, J.
Chu, H.
Desai, A.
Euskirchen, E.
Goodrich, J.
Griffis, T.
Helbig, M.
Hirano, T.
Iwata, H.
Jurasinski, G.
King, J.
Koebsch, F.
Kolka, R.
Krauss, K.
Lohila, A.
Mammarella, I.
Nilson, M.
Noormets, A.
Oechel, W.
Peichl, M.
Sachs, T.
Sakabe, A.
Schulze, C.
Sonnentag, O.
Sullivan, R.
Tuittila, E.
Ueyama, M.
Vesala, T.
Ward, E.
Wille, C.
Wong, G.
Zona, D.
Windham‐Myers, L.
Poulter, B.
Jackson, R.
Upscaling Wetland Methane Emissions From the FLUXNET‐CH4 Eddy Covariance Network (UpCH4 v1.0): Model Development, Network Assessment, and Budget Comparison
author_facet McNicol, G.
Fluet‐Chouinard, E.
Ouyang, Z.
Knox, S.
Zhang, Z.
Aalto, T.
Bansal, S.
Chang, K.
Chen, M.
Delwiche, K.
Feron, S.
Goeckede, M.
Liu, J.
Malhotra, A.
Melton, J.
Riley, W.
Vargas, R.
Yuan, K.
Ying, Q.
Zhu, Q.
Alekseychik, P.
Aurela, M.
Billesbach, D.
Campbell, D.
Chen, J.
Chu, H.
Desai, A.
Euskirchen, E.
Goodrich, J.
Griffis, T.
Helbig, M.
Hirano, T.
Iwata, H.
Jurasinski, G.
King, J.
Koebsch, F.
Kolka, R.
Krauss, K.
Lohila, A.
Mammarella, I.
Nilson, M.
Noormets, A.
Oechel, W.
Peichl, M.
Sachs, T.
Sakabe, A.
Schulze, C.
Sonnentag, O.
Sullivan, R.
Tuittila, E.
Ueyama, M.
Vesala, T.
Ward, E.
Wille, C.
Wong, G.
Zona, D.
Windham‐Myers, L.
Poulter, B.
Jackson, R.
author_sort McNicol, G.
title Upscaling Wetland Methane Emissions From the FLUXNET‐CH4 Eddy Covariance Network (UpCH4 v1.0): Model Development, Network Assessment, and Budget Comparison
title_short Upscaling Wetland Methane Emissions From the FLUXNET‐CH4 Eddy Covariance Network (UpCH4 v1.0): Model Development, Network Assessment, and Budget Comparison
title_full Upscaling Wetland Methane Emissions From the FLUXNET‐CH4 Eddy Covariance Network (UpCH4 v1.0): Model Development, Network Assessment, and Budget Comparison
title_fullStr Upscaling Wetland Methane Emissions From the FLUXNET‐CH4 Eddy Covariance Network (UpCH4 v1.0): Model Development, Network Assessment, and Budget Comparison
title_full_unstemmed Upscaling Wetland Methane Emissions From the FLUXNET‐CH4 Eddy Covariance Network (UpCH4 v1.0): Model Development, Network Assessment, and Budget Comparison
title_sort upscaling wetland methane emissions from the fluxnet‐ch4 eddy covariance network (upch4 v1.0): model development, network assessment, and budget comparison
publishDate 2023
url https://gfzpublic.gfz-potsdam.de/pubman/item/item_5022587
https://gfzpublic.gfz-potsdam.de/pubman/item/item_5022587_1/component/file_5022613/5022587.pdf
long_lat ENVELOPE(-62.350,-62.350,-74.233,-74.233)
ENVELOPE(-81.383,-81.383,50.683,50.683)
geographic Nash
Sutcliffe
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Sutcliffe
genre Tundra
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op_source AGU Advances
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https://gfzpublic.gfz-potsdam.de/pubman/item/item_5022587
https://gfzpublic.gfz-potsdam.de/pubman/item/item_5022587_1/component/file_5022613/5022587.pdf
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https://creativecommons.org/licenses/by/4.0/
op_doi https://doi.org/10.1029/2023AV000956
container_title AGU Advances
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