Upscaling Methane Flux From Plot Level to Eddy Covariance Tower Domains in Five Alaskan Tundra Ecosystems
Spatial heterogeneity in methane (CH 4 ) flux requires a reliable upscaling approach to reach accurate regional CH 4 budgets in the Arctic tundra. In this study, we combined the CLM-Microbe model with three footprint algorithms to scale up CH 4 flux from a plot level to eddy covariance (EC) tower do...
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Online Access: | http://www.osti.gov/servlets/purl/1876265 https://www.osti.gov/biblio/1876265 https://doi.org/10.3389/fenvs.2022.939238 |
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ftosti:oai:osti.gov:1876265 2023-07-30T03:55:36+02:00 Upscaling Methane Flux From Plot Level to Eddy Covariance Tower Domains in Five Alaskan Tundra Ecosystems Wang, Yihui Yuan, Fengming Arndt, Kyle A. Liu, Jianzhao He, Liyuan Zuo, Yunjiang Zona, Donatella Lipson, David A. Oechel, Walter C. Ricciuto, Daniel M. Wullschleger, Stan D. Thornton, Peter E. Xu, Xiaofeng 2022-09-07 application/pdf http://www.osti.gov/servlets/purl/1876265 https://www.osti.gov/biblio/1876265 https://doi.org/10.3389/fenvs.2022.939238 unknown http://www.osti.gov/servlets/purl/1876265 https://www.osti.gov/biblio/1876265 https://doi.org/10.3389/fenvs.2022.939238 doi:10.3389/fenvs.2022.939238 54 ENVIRONMENTAL SCIENCES 2022 ftosti https://doi.org/10.3389/fenvs.2022.939238 2023-07-11T10:13:27Z Spatial heterogeneity in methane (CH 4 ) flux requires a reliable upscaling approach to reach accurate regional CH 4 budgets in the Arctic tundra. In this study, we combined the CLM-Microbe model with three footprint algorithms to scale up CH 4 flux from a plot level to eddy covariance (EC) tower domains (200 m × 200 m) in the Alaska North Slope, for three sites in Utqiagvik (US-Beo, US-Bes, and US-Brw), one in Atqasuk (US-Atq) and one in Ivotuk (US-Ivo), for a period of 2013–2015. Three footprint algorithms were the homogenous footprint (HF) that assumes even contribution of all grid cells, the gradient footprint (GF) that assumes gradually declining contribution from center grid cells to edges, and the dynamic footprint (DF) that considers the impacts of wind and heterogeneity of land surface. Simulated annual CH 4 flux was highly consistent with the EC measurements at US-Beo and US-Bes. In contrast, flux was overestimated at US-Brw, US-Atq, and US-Ivo due to the higher simulated CH 4 flux in early growing seasons. The simulated monthly CH 4 flux was consistent with EC measurements but with different accuracies among footprint algorithms. At US-Bes in September 2013, RMSE and NNSE were 0.002 μmol m -2 s -1 and 0.782 using the DF algorithm, but 0.007 μmol m -2 s -1 and 0.758 using HF and 0.007 μmol m -2 s -1 and 0.765 using GF, respectively. DF algorithm performed better than the HF and GF algorithms in capturing the temporal variation in daily CH 4 flux each month, while the model accuracy was similar among the three algorithms due to flat landscapes. Temporal variations in CH 4 flux during 2013–2015 were predominately explained by air temperature (67–74%), followed by precipitation (22–36%). Spatial heterogeneities in vegetation fraction and elevation dominated the spatial variations in CH 4 flux for all five tower domains despite relatively weak differences in simulated CH 4 flux among three footprint algorithms. The CLM-Microbe model can simulate CH 4 flux at both plot and landscape scales at a high ... Other/Unknown Material Alaska North Slope Arctic north slope Tundra Alaska SciTec Connect (Office of Scientific and Technical Information - OSTI, U.S. Department of Energy) Arctic Frontiers in Environmental Science 10 |
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Open Polar |
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SciTec Connect (Office of Scientific and Technical Information - OSTI, U.S. Department of Energy) |
op_collection_id |
ftosti |
language |
unknown |
topic |
54 ENVIRONMENTAL SCIENCES |
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54 ENVIRONMENTAL SCIENCES Wang, Yihui Yuan, Fengming Arndt, Kyle A. Liu, Jianzhao He, Liyuan Zuo, Yunjiang Zona, Donatella Lipson, David A. Oechel, Walter C. Ricciuto, Daniel M. Wullschleger, Stan D. Thornton, Peter E. Xu, Xiaofeng Upscaling Methane Flux From Plot Level to Eddy Covariance Tower Domains in Five Alaskan Tundra Ecosystems |
topic_facet |
54 ENVIRONMENTAL SCIENCES |
description |
Spatial heterogeneity in methane (CH 4 ) flux requires a reliable upscaling approach to reach accurate regional CH 4 budgets in the Arctic tundra. In this study, we combined the CLM-Microbe model with three footprint algorithms to scale up CH 4 flux from a plot level to eddy covariance (EC) tower domains (200 m × 200 m) in the Alaska North Slope, for three sites in Utqiagvik (US-Beo, US-Bes, and US-Brw), one in Atqasuk (US-Atq) and one in Ivotuk (US-Ivo), for a period of 2013–2015. Three footprint algorithms were the homogenous footprint (HF) that assumes even contribution of all grid cells, the gradient footprint (GF) that assumes gradually declining contribution from center grid cells to edges, and the dynamic footprint (DF) that considers the impacts of wind and heterogeneity of land surface. Simulated annual CH 4 flux was highly consistent with the EC measurements at US-Beo and US-Bes. In contrast, flux was overestimated at US-Brw, US-Atq, and US-Ivo due to the higher simulated CH 4 flux in early growing seasons. The simulated monthly CH 4 flux was consistent with EC measurements but with different accuracies among footprint algorithms. At US-Bes in September 2013, RMSE and NNSE were 0.002 μmol m -2 s -1 and 0.782 using the DF algorithm, but 0.007 μmol m -2 s -1 and 0.758 using HF and 0.007 μmol m -2 s -1 and 0.765 using GF, respectively. DF algorithm performed better than the HF and GF algorithms in capturing the temporal variation in daily CH 4 flux each month, while the model accuracy was similar among the three algorithms due to flat landscapes. Temporal variations in CH 4 flux during 2013–2015 were predominately explained by air temperature (67–74%), followed by precipitation (22–36%). Spatial heterogeneities in vegetation fraction and elevation dominated the spatial variations in CH 4 flux for all five tower domains despite relatively weak differences in simulated CH 4 flux among three footprint algorithms. The CLM-Microbe model can simulate CH 4 flux at both plot and landscape scales at a high ... |
author |
Wang, Yihui Yuan, Fengming Arndt, Kyle A. Liu, Jianzhao He, Liyuan Zuo, Yunjiang Zona, Donatella Lipson, David A. Oechel, Walter C. Ricciuto, Daniel M. Wullschleger, Stan D. Thornton, Peter E. Xu, Xiaofeng |
author_facet |
Wang, Yihui Yuan, Fengming Arndt, Kyle A. Liu, Jianzhao He, Liyuan Zuo, Yunjiang Zona, Donatella Lipson, David A. Oechel, Walter C. Ricciuto, Daniel M. Wullschleger, Stan D. Thornton, Peter E. Xu, Xiaofeng |
author_sort |
Wang, Yihui |
title |
Upscaling Methane Flux From Plot Level to Eddy Covariance Tower Domains in Five Alaskan Tundra Ecosystems |
title_short |
Upscaling Methane Flux From Plot Level to Eddy Covariance Tower Domains in Five Alaskan Tundra Ecosystems |
title_full |
Upscaling Methane Flux From Plot Level to Eddy Covariance Tower Domains in Five Alaskan Tundra Ecosystems |
title_fullStr |
Upscaling Methane Flux From Plot Level to Eddy Covariance Tower Domains in Five Alaskan Tundra Ecosystems |
title_full_unstemmed |
Upscaling Methane Flux From Plot Level to Eddy Covariance Tower Domains in Five Alaskan Tundra Ecosystems |
title_sort |
upscaling methane flux from plot level to eddy covariance tower domains in five alaskan tundra ecosystems |
publishDate |
2022 |
url |
http://www.osti.gov/servlets/purl/1876265 https://www.osti.gov/biblio/1876265 https://doi.org/10.3389/fenvs.2022.939238 |
geographic |
Arctic |
geographic_facet |
Arctic |
genre |
Alaska North Slope Arctic north slope Tundra Alaska |
genre_facet |
Alaska North Slope Arctic north slope Tundra Alaska |
op_relation |
http://www.osti.gov/servlets/purl/1876265 https://www.osti.gov/biblio/1876265 https://doi.org/10.3389/fenvs.2022.939238 doi:10.3389/fenvs.2022.939238 |
op_doi |
https://doi.org/10.3389/fenvs.2022.939238 |
container_title |
Frontiers in Environmental Science |
container_volume |
10 |
_version_ |
1772820330469916672 |