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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eScholarship, University of California
2023
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ftcdlib:oai:escholarship.org:ark:/13030/qt6243x472 2023-11-05T03:45:24+01:00 Upscaling Wetland Methane Emissions From the FLUXNET‐CH4 Eddy Covariance Network (UpCH4 v1.0): Model Development, Network Assessment, and Budget Comparison McNicol, Gavin Fluet‐Chouinard, Etienne Ouyang, Zutao Knox, Sara Zhang, Zhen Aalto, Tuula Bansal, Sheel Chang, Kuang‐Yu Chen, Min Delwiche, Kyle Feron, Sarah Goeckede, Mathias Liu, Jinxun Malhotra, Avni Melton, Joe R Riley, William Vargas, Rodrigo Yuan, Kunxiaojia Ying, Qing Zhu, Qing Alekseychik, Pavel Aurela, Mika Billesbach, David P Campbell, David I Chen, Jiquan Chu, Housen Desai, Ankur R Euskirchen, Eugenie Goodrich, Jordan Griffis, Timothy Helbig, Manuel Hirano, Takashi Iwata, Hiroki Jurasinski, Gerald King, John Koebsch, Franziska Kolka, Randall Krauss, Ken Lohila, Annalea Mammarella, Ivan Nilson, Mats Noormets, Asko Oechel, Walter Peichl, Matthias Sachs, Torsten Sakabe, Ayaka Schulze, Christopher Sonnentag, Oliver Sullivan, Ryan C Tuittila, Eeva‐Stiina Ueyama, Masahito Vesala, Timo Ward, Eric Wille, Christian Wong, Guan Xhuan Zona, Donatella Windham‐Myers, Lisamarie Poulter, Benjamin Jackson, Robert B 2023-10-01 https://escholarship.org/uc/item/6243x472 unknown eScholarship, University of California qt6243x472 https://escholarship.org/uc/item/6243x472 CC-BY AGU Advances, vol 4, iss 5 Earth Sciences Atmospheric Sciences Climate Action Life on Land Climate change science Geology Physical geography and environmental geoscience article 2023 ftcdlib 2023-10-09T18:08:25Z 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 TgCH4y−1 for 2001–2018 which agrees closely with current bottom-up land surface models (102–181 TgCH4y−1) and overlaps with top-down atmospheric inversion models (155–200 TgCH4y−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 University of California: eScholarship |
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Open Polar |
collection |
University of California: eScholarship |
op_collection_id |
ftcdlib |
language |
unknown |
topic |
Earth Sciences Atmospheric Sciences Climate Action Life on Land Climate change science Geology Physical geography and environmental geoscience |
spellingShingle |
Earth Sciences Atmospheric Sciences Climate Action Life on Land Climate change science Geology Physical geography and environmental geoscience McNicol, Gavin Fluet‐Chouinard, Etienne Ouyang, Zutao Knox, Sara Zhang, Zhen Aalto, Tuula Bansal, Sheel Chang, Kuang‐Yu Chen, Min Delwiche, Kyle Feron, Sarah Goeckede, Mathias Liu, Jinxun Malhotra, Avni Melton, Joe R Riley, William Vargas, Rodrigo Yuan, Kunxiaojia Ying, Qing Zhu, Qing Alekseychik, Pavel Aurela, Mika Billesbach, David P Campbell, David I Chen, Jiquan Chu, Housen Desai, Ankur R Euskirchen, Eugenie Goodrich, Jordan Griffis, Timothy Helbig, Manuel Hirano, Takashi Iwata, Hiroki Jurasinski, Gerald King, John Koebsch, Franziska Kolka, Randall Krauss, Ken Lohila, Annalea Mammarella, Ivan Nilson, Mats Noormets, Asko Oechel, Walter Peichl, Matthias Sachs, Torsten Sakabe, Ayaka Schulze, Christopher Sonnentag, Oliver Sullivan, Ryan C Tuittila, Eeva‐Stiina Ueyama, Masahito Vesala, Timo Ward, Eric Wille, Christian Wong, Guan Xhuan Zona, Donatella Windham‐Myers, Lisamarie Poulter, Benjamin Jackson, Robert B Upscaling Wetland Methane Emissions From the FLUXNET‐CH4 Eddy Covariance Network (UpCH4 v1.0): Model Development, Network Assessment, and Budget Comparison |
topic_facet |
Earth Sciences Atmospheric Sciences Climate Action Life on Land Climate change science Geology Physical geography and environmental geoscience |
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 TgCH4y−1 for 2001–2018 which agrees closely with current bottom-up land surface models (102–181 TgCH4y−1) and overlaps with top-down atmospheric inversion models (155–200 TgCH4y−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, Gavin Fluet‐Chouinard, Etienne Ouyang, Zutao Knox, Sara Zhang, Zhen Aalto, Tuula Bansal, Sheel Chang, Kuang‐Yu Chen, Min Delwiche, Kyle Feron, Sarah Goeckede, Mathias Liu, Jinxun Malhotra, Avni Melton, Joe R Riley, William Vargas, Rodrigo Yuan, Kunxiaojia Ying, Qing Zhu, Qing Alekseychik, Pavel Aurela, Mika Billesbach, David P Campbell, David I Chen, Jiquan Chu, Housen Desai, Ankur R Euskirchen, Eugenie Goodrich, Jordan Griffis, Timothy Helbig, Manuel Hirano, Takashi Iwata, Hiroki Jurasinski, Gerald King, John Koebsch, Franziska Kolka, Randall Krauss, Ken Lohila, Annalea Mammarella, Ivan Nilson, Mats Noormets, Asko Oechel, Walter Peichl, Matthias Sachs, Torsten Sakabe, Ayaka Schulze, Christopher Sonnentag, Oliver Sullivan, Ryan C Tuittila, Eeva‐Stiina Ueyama, Masahito Vesala, Timo Ward, Eric Wille, Christian Wong, Guan Xhuan Zona, Donatella Windham‐Myers, Lisamarie Poulter, Benjamin Jackson, Robert B |
author_facet |
McNicol, Gavin Fluet‐Chouinard, Etienne Ouyang, Zutao Knox, Sara Zhang, Zhen Aalto, Tuula Bansal, Sheel Chang, Kuang‐Yu Chen, Min Delwiche, Kyle Feron, Sarah Goeckede, Mathias Liu, Jinxun Malhotra, Avni Melton, Joe R Riley, William Vargas, Rodrigo Yuan, Kunxiaojia Ying, Qing Zhu, Qing Alekseychik, Pavel Aurela, Mika Billesbach, David P Campbell, David I Chen, Jiquan Chu, Housen Desai, Ankur R Euskirchen, Eugenie Goodrich, Jordan Griffis, Timothy Helbig, Manuel Hirano, Takashi Iwata, Hiroki Jurasinski, Gerald King, John Koebsch, Franziska Kolka, Randall Krauss, Ken Lohila, Annalea Mammarella, Ivan Nilson, Mats Noormets, Asko Oechel, Walter Peichl, Matthias Sachs, Torsten Sakabe, Ayaka Schulze, Christopher Sonnentag, Oliver Sullivan, Ryan C Tuittila, Eeva‐Stiina Ueyama, Masahito Vesala, Timo Ward, Eric Wille, Christian Wong, Guan Xhuan Zona, Donatella Windham‐Myers, Lisamarie Poulter, Benjamin Jackson, Robert B |
author_sort |
McNicol, Gavin |
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 |
publisher |
eScholarship, University of California |
publishDate |
2023 |
url |
https://escholarship.org/uc/item/6243x472 |
genre |
Tundra |
genre_facet |
Tundra |
op_source |
AGU Advances, vol 4, iss 5 |
op_relation |
qt6243x472 https://escholarship.org/uc/item/6243x472 |
op_rights |
CC-BY |
_version_ |
1781707591948173312 |