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Emission or atmospheric processes? An attempt to attribute the source of large bias of aerosols in eastern China simulated by global climate models

机译:发射或大气过程?试图归因于全球气候模型模拟的东部地区气溶胶大偏见的源泉

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摘要

Global climate models often underestimate aerosol loadings in China, andthese biases can have significant implications for anthropogenic aerosolradiative forcing and climate effects. The biases may be caused by either theemission inventory or the treatment of aerosol processes in the models, orboth, but so far no consensus has been reached. In this study, a relativelynew emission inventory based on energy statistics and technology,Multi-resolution Emission Inventory for China (MEIC), is used to drive theCommunity Atmosphere Model version 5 (CAM5) to evaluate aerosol distributionand radiative effects against observations in China. The model results arecompared with the model simulations with the widely used IntergovernmentalPanel on Climate Change Fifth Assessment Report (IPCC AR5) emissioninventory. We find that the new MEIC emission improves the aerosol opticaldepth (AOD) simulations in eastern China and explains 22–28 % of the AODlow bias simulated with the AR5 emission. However, AOD is still biased low ineastern China. Seasonal variation of the MEIC emission leads to a betteragreement with the observed seasonal variation of primary aerosols than theAR5 emission, but the concentrations are still underestimated. This impliesthat the atmospheric loadings of primary aerosols are closely related to theemission, which may still be underestimated over eastern China. In contrast,the seasonal variations of secondary aerosols depend more on aerosolprocesses (e.g., gas- and aqueous-phase production from precursor gases) thatare associated with meteorological conditions and to a lesser extent on theemission. It indicates that the emissions of precursor gases for thesecondary aerosols alone cannot explain the low bias in the model.Aerosol secondary production processes in CAM5should also be revisited. The simulation using MEIC estimates theannual-average aerosol direct radiative effects (ADREs) at the top of theatmosphere (TOA), at the surface, and in the atmosphere to be −5.02,−18.47, and 13.45 W m−2, respectively, over eastern China, which areenhanced by −0.91, −3.48, and 2.57 W m−2 compared with the AR5emission. The differences of ADREs by using MEIC and AR5 emissions are largerthan the decadal changes of the modeled ADREs, indicating the uncertainty ofthe emission inventories. This study highlights the importance of improvingboth the emission and aerosol secondary production processes in modeling theatmospheric aerosols and their radiative effects. Yet, if the estimations ofMEIC emissions in trace gases do not suffer similar biases to those in theAOD, our findings will help affirm a fundamental error in the conversion fromprecursor gases to secondary aerosols as hinted in other recent studiesfollowing different approaches.
机译:全球气候模型往往低估了中国的气溶胶载荷,这些偏差可能对人为气溶胶具有显着影响辐射迫使和气候效应。偏差可能是由排放库存或模型中的气溶胶过程的处理,或两者,但到目前为止没有达成共识。在这项研究中,相对基于能源统计和技术的新排放库存,中国(MEIC)的多分辨率排放库存,用于推动社区氛围型号5(CAM5)评估气溶胶分配以及对中国观察的辐射影响。模型结果是与具有广泛使用的政府间数据模拟模拟相比气候变化小组第五次评估报告(IPCC AR5)排放存货。我们发现新的Meic排放改善了气溶胶光学中国东部的深度(AOD)模拟,解释了22-28%的AOD用AR5发射模拟低偏差。但是,AOD仍然偏见中国东部。 MEIC排放的季节变化导致更好与观察到的原发性气溶胶季节变化同意AR5排放,但浓度仍低于低估。这意味着原发性气溶胶的大气负荷与之密切相关排放,仍可能低估了中国东部。相比之下,二次气溶胶的季节变异依赖于气溶胶方法(例如,来自前体气体的气体和水相产生)与气象条件相关,并在较小程度上排放。它表明前体气体的排放仅继发气溶胶不能解释模型中的低偏差。CAM5中的气溶胶二次生产过程也应该重新审视。使用MEIC的仿真估计年平均气溶胶直接辐射效应(Adres)在顶部气氛(TOA),表面,在大气中为-5.02,在中国东部分别为-18.47和13.45wm-2,这是与AR5相比增强-0.91,-3.48和2.57WM-2排放。使用MEIC和AR5排放的ADRES的差异更大比建模的Adres的二等变化,表明不确定性排放库存。本研究突出了改善的重要性在建模中发射和气溶胶二次生产过程大气气溶胶及其辐射效果。然而,如果估计痕量气体中的MEIC排放不会对那些人遭受类似的偏见AOD,我们的调查结果将有助于确认转换中的根本误差在其他最近研究中暗示的二次气溶胶前体气体遵循不同的方法。

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