Evaluation of CH4MOD(wetland) and Terrestrial Ecosystem Model (TEM) used to estimate global CH4 emissions from natural wetlands
Wetlands are the largest and most uncertain natural sources of atmospheric methane (CH4). Several process-based models have been developed to quantify the magnitude and estimate spatial and temporal variations in CH4 emissions from global wetlands. Reliable models are required to estimate global wet...
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COPERNICUS GESELLSCHAFT MBH
2020
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ftchiacadscibcas:oai:ir.ibcas.ac.cn:2S10CLM1/18347 2023-05-15T18:40:48+02:00 Evaluation of CH4MOD(wetland) and Terrestrial Ecosystem Model (TEM) used to estimate global CH4 emissions from natural wetlands Li, Tingting Lu, Yanyu Yu, Lingfei Sun, Wenjuan Zhang, Qing Zhang, Wen Wang, Guocheng Qin, Zhangcai Yu, Lijun Li, Hailing Zhang, Ran 2020 http://ir.ibcas.ac.cn/handle/2S10CLM1/18347 https://doi.org/10.5194/gmd-13-3769-2020 英语 eng COPERNICUS GESELLSCHAFT MBH GEOSCIENTIFIC MODEL DEVELOPMENT http://ir.ibcas.ac.cn/handle/2S10CLM1/18347 doi:10.5194/gmd-13-3769-2020 cn.org.cspace.api.content.CopyrightPolicy@29e48b03 Geosciences Multidisciplinary EDDY-COVARIANCE MEASUREMENTS DERIVE METHANE EMISSIONS POLYGONAL TUNDRA CLIMATE-CHANGE TEMPORAL VARIATIONS VEGETATION CONTROLS DATA SET FLUXES CARBON CO2 Geology Article 期刊论文 2020 ftchiacadscibcas https://doi.org/10.5194/gmd-13-3769-2020 2021-11-29T18:05:56Z Wetlands are the largest and most uncertain natural sources of atmospheric methane (CH4). Several process-based models have been developed to quantify the magnitude and estimate spatial and temporal variations in CH4 emissions from global wetlands. Reliable models are required to estimate global wetland CH4 emissions. This study aimed to test two process-based models, CH4 MODwetland and Terrestrial Ecosystem Model (TEM), against the CH4 flux measurements of marsh, swamp, peatland and coastal wetland sites across the world; specifically, model accuracy and generality were evaluated for different wetland types and in different continents, and then the global CH4 emissions from 2000 to 2010 were estimated. Both models showed similar high correlations with the observed seasonal/annual total CH4 emissions, and the regression of the observed versus computed total seasonal/annual CH4 emissions resulted in R-2 values of 0.81 and 0.68 for CH4 MODwetland and ILM, respectively. The CH4MOD(wetland )produced accurate predictions for marshes, peatlands, swamps and coastal wetlands, with model efficiency (EF) values of 0.22, 0.52, 0.13 and 0.72, respectively. TEM produced good predictions for peatlands and swamps, with EF values of 0.69 and 0.74, respectively, but it could not accurately simulate marshes and coastal wetlands (EF < 0). There was a good correlation between the simulated CH4 fluxes and the observed values on most continents. However, CH4MOD(wetland) showed no correlation with the observed values in South America and Africa. TEM showed no correlation with the observations in Europe. The global CH4 emissions for the period 2000-2010 were estimated to be 105.31 +/- 2.72 Tg yr(-1) by CH4 MODwetland and 134.31 +/- 0.84 Tg yr(-1) by MM. Both models simulated a similar spatial distribution of CH4 emissions globally and on different continents. Marshes contribute 36 %-39 % of global CH4 emissions. Lakes/rivers and swamps are the second and third greatest contributors, respectively. Other wetland types account for only approximately 20 % of global emissions. Based on the model applicability, if we use the more accurate model, i.e., the one that performs best as evidenced by a higher model efficiency and a lower model bias, to estimate each continent and wetland type, we obtain a new assessment of 116.99-124.74 Tg yr(-1) for the global CH4 emissions for the period 2000-2010. Our results imply that performance at a global scale may conceal model uncertainty. Efforts should be made to improve model accuracy for different wetland types and regions, particularly hotspot regions, to reduce the uncertainty in global assessments. Article in Journal/Newspaper Tundra Institute of Botany: IBCAS OpenIR (Chinese Academy Of Sciences) Geoscientific Model Development 13 8 3769 3788 |
institution |
Open Polar |
collection |
Institute of Botany: IBCAS OpenIR (Chinese Academy Of Sciences) |
op_collection_id |
ftchiacadscibcas |
language |
English |
topic |
Geosciences Multidisciplinary EDDY-COVARIANCE MEASUREMENTS DERIVE METHANE EMISSIONS POLYGONAL TUNDRA CLIMATE-CHANGE TEMPORAL VARIATIONS VEGETATION CONTROLS DATA SET FLUXES CARBON CO2 Geology |
spellingShingle |
Geosciences Multidisciplinary EDDY-COVARIANCE MEASUREMENTS DERIVE METHANE EMISSIONS POLYGONAL TUNDRA CLIMATE-CHANGE TEMPORAL VARIATIONS VEGETATION CONTROLS DATA SET FLUXES CARBON CO2 Geology Li, Tingting Lu, Yanyu Yu, Lingfei Sun, Wenjuan Zhang, Qing Zhang, Wen Wang, Guocheng Qin, Zhangcai Yu, Lijun Li, Hailing Zhang, Ran Evaluation of CH4MOD(wetland) and Terrestrial Ecosystem Model (TEM) used to estimate global CH4 emissions from natural wetlands |
topic_facet |
Geosciences Multidisciplinary EDDY-COVARIANCE MEASUREMENTS DERIVE METHANE EMISSIONS POLYGONAL TUNDRA CLIMATE-CHANGE TEMPORAL VARIATIONS VEGETATION CONTROLS DATA SET FLUXES CARBON CO2 Geology |
description |
Wetlands are the largest and most uncertain natural sources of atmospheric methane (CH4). Several process-based models have been developed to quantify the magnitude and estimate spatial and temporal variations in CH4 emissions from global wetlands. Reliable models are required to estimate global wetland CH4 emissions. This study aimed to test two process-based models, CH4 MODwetland and Terrestrial Ecosystem Model (TEM), against the CH4 flux measurements of marsh, swamp, peatland and coastal wetland sites across the world; specifically, model accuracy and generality were evaluated for different wetland types and in different continents, and then the global CH4 emissions from 2000 to 2010 were estimated. Both models showed similar high correlations with the observed seasonal/annual total CH4 emissions, and the regression of the observed versus computed total seasonal/annual CH4 emissions resulted in R-2 values of 0.81 and 0.68 for CH4 MODwetland and ILM, respectively. The CH4MOD(wetland )produced accurate predictions for marshes, peatlands, swamps and coastal wetlands, with model efficiency (EF) values of 0.22, 0.52, 0.13 and 0.72, respectively. TEM produced good predictions for peatlands and swamps, with EF values of 0.69 and 0.74, respectively, but it could not accurately simulate marshes and coastal wetlands (EF < 0). There was a good correlation between the simulated CH4 fluxes and the observed values on most continents. However, CH4MOD(wetland) showed no correlation with the observed values in South America and Africa. TEM showed no correlation with the observations in Europe. The global CH4 emissions for the period 2000-2010 were estimated to be 105.31 +/- 2.72 Tg yr(-1) by CH4 MODwetland and 134.31 +/- 0.84 Tg yr(-1) by MM. Both models simulated a similar spatial distribution of CH4 emissions globally and on different continents. Marshes contribute 36 %-39 % of global CH4 emissions. Lakes/rivers and swamps are the second and third greatest contributors, respectively. Other wetland types account for only approximately 20 % of global emissions. Based on the model applicability, if we use the more accurate model, i.e., the one that performs best as evidenced by a higher model efficiency and a lower model bias, to estimate each continent and wetland type, we obtain a new assessment of 116.99-124.74 Tg yr(-1) for the global CH4 emissions for the period 2000-2010. Our results imply that performance at a global scale may conceal model uncertainty. Efforts should be made to improve model accuracy for different wetland types and regions, particularly hotspot regions, to reduce the uncertainty in global assessments. |
format |
Article in Journal/Newspaper |
author |
Li, Tingting Lu, Yanyu Yu, Lingfei Sun, Wenjuan Zhang, Qing Zhang, Wen Wang, Guocheng Qin, Zhangcai Yu, Lijun Li, Hailing Zhang, Ran |
author_facet |
Li, Tingting Lu, Yanyu Yu, Lingfei Sun, Wenjuan Zhang, Qing Zhang, Wen Wang, Guocheng Qin, Zhangcai Yu, Lijun Li, Hailing Zhang, Ran |
author_sort |
Li, Tingting |
title |
Evaluation of CH4MOD(wetland) and Terrestrial Ecosystem Model (TEM) used to estimate global CH4 emissions from natural wetlands |
title_short |
Evaluation of CH4MOD(wetland) and Terrestrial Ecosystem Model (TEM) used to estimate global CH4 emissions from natural wetlands |
title_full |
Evaluation of CH4MOD(wetland) and Terrestrial Ecosystem Model (TEM) used to estimate global CH4 emissions from natural wetlands |
title_fullStr |
Evaluation of CH4MOD(wetland) and Terrestrial Ecosystem Model (TEM) used to estimate global CH4 emissions from natural wetlands |
title_full_unstemmed |
Evaluation of CH4MOD(wetland) and Terrestrial Ecosystem Model (TEM) used to estimate global CH4 emissions from natural wetlands |
title_sort |
evaluation of ch4mod(wetland) and terrestrial ecosystem model (tem) used to estimate global ch4 emissions from natural wetlands |
publisher |
COPERNICUS GESELLSCHAFT MBH |
publishDate |
2020 |
url |
http://ir.ibcas.ac.cn/handle/2S10CLM1/18347 https://doi.org/10.5194/gmd-13-3769-2020 |
genre |
Tundra |
genre_facet |
Tundra |
op_relation |
GEOSCIENTIFIC MODEL DEVELOPMENT http://ir.ibcas.ac.cn/handle/2S10CLM1/18347 doi:10.5194/gmd-13-3769-2020 |
op_rights |
cn.org.cspace.api.content.CopyrightPolicy@29e48b03 |
op_doi |
https://doi.org/10.5194/gmd-13-3769-2020 |
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Geoscientific Model Development |
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13 |
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8 |
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3769 |
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3788 |
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