Global S&T Development Trend Analysis Platform of Resources and Environment
DOI | 10.5194/acp-19-13701-2019 |
Inter-model comparison of global hydroxyl radical (OH) distributions and their impact on atmospheric methane over the 2000-2016 period | |
Zhao, Yuanhong1; 39;Connor, Fiona M.2 | |
2019-11-13 | |
发表期刊 | ATMOSPHERIC CHEMISTRY AND PHYSICS
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ISSN | 1680-7316 |
EISSN | 1680-7324 |
出版年 | 2019 |
卷号 | 19期号:21页码:13701-13723 |
文章类型 | Article |
语种 | 英语 |
国家 | France; England; Australia; USA; Japan; Germany; Canada; Switzerland; New Zealand |
英文摘要 | The modeling study presented here aims to estimate how uncertainties in global hydroxyl radical (OH) distributions, variability, and trends may contribute to resolving discrepancies between simulated and observed methane (CH4) changes since 2000. A multi-model ensemble of 14 OH fields was analyzed and aggregated into 64 scenarios to force the offline atmospheric chemistry transport model LMDz (Laboratoire de Meteorologic Dynamique) with a standard CH4 emission scenario over the period 2000-2016. The multi-model simulated global volume-weighted tropospheric mean OH concentration ([OH]) averaged over 2000-2010 ranges between 8.7 x 10(5) and 12.8 x 10(5) molec cm(-3) . The inter-model differences in tropospheric OH burden and vertical distributions are mainly determined by the differences in the nitrogen oxide (NO) distributions, while the spatial discrepancies between OH fields are mostly due to differences in natural emissions and volatile organic compound (VOC) chemistry. From 2000 to 2010, most simulated OH fields show an increase of 0.1-0.3 x 10(5) molec cm(-3) in the tropospheric mean [OH], with year-to-year variations much smaller than during the historical period 1960-2000. Once ingested into the LMDz model, these OH changes translated into a 5 to 15 ppbv reduction in the CH4 mixing ratio in 2010, which represents 7 %-20 % of the model-simulated CH4 increase due to surface emissions. Between 2010 and 2016, the ensemble of simulations showed that OH changes could lead to a CH4 mixing ratio uncertainty of > +/- 30 ppbv. Over the full 2000-2016 time period, using a common stateof-the-art but nonoptimized emission scenario, the impact of [OH] changes tested here can explain up to 54 % of the gap between model simulations and observations. This result emphasizes the importance of better representing OH abundance and variations in CH4 forward simulations and emission optimizations performed by atmospheric inversions. |
领域 | 地球科学 |
收录类别 | SCI-E |
WOS记录号 | WOS:000497307700001 |
WOS关键词 | BIOMASS BURNING EMISSIONS ; CLIMATE-COMPOSITION MODEL ; TROPOSPHERIC OZONE ; TRANSPORT MODEL ; INTERANNUAL VARIABILITY ; CARBON-MONOXIDE ; CHEMISTRY ; CIRCULATION ; OXIDATION ; CAPACITY |
WOS类目 | Environmental Sciences ; Meteorology & Atmospheric Sciences |
WOS研究方向 | Environmental Sciences & Ecology ; Meteorology & Atmospheric Sciences |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://119.78.100.173/C666/handle/2XK7JSWQ/224052 |
专题 | 环境与发展全球科技态势 |
作者单位 | 1.Univ Paris Saclay, CNRS, CEA, UVSQ,LSCE,IPSL, F-91191 Gif Sur Yvette, France; 2.Univ Reading, Dept Meteorol, Reading, Berks, England; 3.CSIRO Oceans & Atmosphere, Global Carbon Project, Canberra, ACT 2601, Australia; 4.Stanford Univ, Woods Inst Environm, Earth Syst Sci Dept, Stanford, CA 94305 USA; 5.Stanford Univ, Precourt Inst Energy, Stanford, CA 94305 USA; 6.CSIRO Oceans & Atmosphere, Aspendale, Vic 3195, Australia; 7.Univ Cambridge, Dept Chem, Cambridge CB2 1EW, England; 8.Univ Cambridge, NCAS Climate, Cambridge CB2 1EW, England; 9.Univ Paris 06, LATMOS, 4 Pl Jussieu Tour 45,Couloir 45-46, F-75252 Paris 05, France; 10.Meteorol Res Inst, 1-1 Nagamine, Tsukuba, Ibaraki 3050052, Japan; 11.Deutsch Zentrum Luft & Raumfahrt DLR, Inst Phys Atmosphare, Oberpfaffenhofen, Germany; 12.Univ Toulouse, CNRS, Meteo France, Ctr Natl Rech Meteorol, Toulouse, France; 13.Natl Ctr Atmospher Res, Atmospher Chem Observat & Modeling Lab, 3090 Ctr Green Dr, Boulder, CO 80301 USA; 14.Karlsruhe Inst Technol, Steinbuch Ctr Comp, Karlsruhe, Germany; 15.Hadley Ctr, Met Off, Exeter EX1 3PB, Devon, England; 16.Environm & Climate Change Canada, Climate Res Branch, Montreal, PQ, Canada; 17.ETH Zurich ETHZ, Inst Atmospher & Climate Sci, Zurich, Switzerland; 18.Univ Canterbury, Sch Phys & Chem Sci, Christchurch, New Zealand; 19.Phys Meteorol Observ Davos, World Radiat Ctr, Dorfstr 33, CH-7260 Davos, Switzerland; 20.NASA, Goddard Space Flight Ctr, Greenbelt, MD USA; 21.USRA, GESTAR, Columbia, MD USA; 22.NOAA, Earth Syst Res Lab, Global Monitoring Div, Boulder, CO USA; 23.Univ Michigan, Climate & Space Sci & Engn, Ann Arbor, MI 48109 USA |
推荐引用方式 GB/T 7714 | Zhao, Yuanhong,39;Connor, Fiona M.. Inter-model comparison of global hydroxyl radical (OH) distributions and their impact on atmospheric methane over the 2000-2016 period[J]. ATMOSPHERIC CHEMISTRY AND PHYSICS,2019,19(21):13701-13723. |
APA | Zhao, Yuanhong,&39;Connor, Fiona M..(2019).Inter-model comparison of global hydroxyl radical (OH) distributions and their impact on atmospheric methane over the 2000-2016 period.ATMOSPHERIC CHEMISTRY AND PHYSICS,19(21),13701-13723. |
MLA | Zhao, Yuanhong,et al."Inter-model comparison of global hydroxyl radical (OH) distributions and their impact on atmospheric methane over the 2000-2016 period".ATMOSPHERIC CHEMISTRY AND PHYSICS 19.21(2019):13701-13723. |
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