DOI: 10.1016/j.atmosenv.2020.117545
论文题名: Monte Carlo analyses of the uncertainties in the predictions from global tropospheric ozone models: Tropospheric burdens and seasonal cycles
作者: Derwent R.G.
刊名: Atmospheric Environment
ISSN: 1352-2310
出版年: 2020
卷: 231 语种: 英语
学科: Global models
; Monte Carlo uncertainty analysis
; Tropospheric burdens
; Tropospheric ozone
中文摘要: Because ozone is a highly reactive trace gas, estimates of its contribution to climate forcing must rely on global chemistry-transport models. These models employ many uncertain input parameters representing the sources and sinks for tropospheric ozone. Ten thousand quasi-randomly Monte Carlo sampled model runs employing a zonally-averaged global ozone model were completed and the output uncertainties were estimated in the burdens and turnovers of methane, carbon monoxide and ozone, together with the uncertainties in the ozone seasonal cycles. Multiple regression was then used to attribute the uncertainty in each output metric to each of the 183 uncertain input parameters which represented emission source sectors, chemical and photochemical rate coefficients, dry deposition velocities and biases in temperature and water vapour concentrations. We have tentatively identified sixteen chemical and photochemical rate coefficients, eight emission source sectors, ozone dry deposition and biases in temperature and water vapour as contributing most to the uncertainties in our chosen output metrics. Ten out of the sixteen chemical processes turned out to be the most important processes in the fast, photochemical balance of the troposphere. Emissions from NOx, methane, carbon monoxide and isoprene had the potential to contribute in a major way to model output uncertainties. There are, however, many limitations to our study, not the least being our use of a two-dimensional (altitude-latitude) ozone model. We have not been able to resolve the apparent conflicts between our model and the observations of ozone seasonal cycles and these must await a more rigorous treatment of tropospheric ozone sources and sinks before they can be resolved. © 2020 Elsevier Ltd Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/160335
Appears in Collections: 气候变化与战略
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作者单位: Rdscientific, Newbury, United Kingdom
Recommended Citation:
Derwent R.G.. Monte Carlo analyses of the uncertainties in the predictions from global tropospheric ozone models: Tropospheric burdens and seasonal cycles[J]. Atmospheric Environment,2020-01-01,231