Climate Change Data Portal
DOI | 10.1016/j.atmosenv.2014.12.003 |
Feedbacks between air pollution and weather, Part 1: Effects on weather | |
Makar, P. A.1; Gong, W.1; Milbrandt, J.2; Hogrefe, C.3; Zhang, Y.4; Curci, G.5; Zabkar, R.6,7; Im, U.8; Balzarini, A.9; Baro, R.10; Bianconi, R.11; Cheung, P.1; Forkel, R.12; Gravel, S.13; Hirtl, M.14; Honzak, L.7; Hou, A.1; Jimenez-Guerrero, R.11; Langer, M.14; Moran, M. D.1; Pabla, B.1; Perez, J. L.15; Pirovano, G.9; San Jose, R.15; Tuccella, P.16; Werhahn, J.12; Zhang, J.1; Galmarini, S.8 | |
发表日期 | 2015-08-01 |
ISSN | 1352-2310 |
卷号 | 115页码:442-469 |
英文摘要 | The meteorological predictions of fully coupled air-quality models running in "feedback" versus "no-feedback" simulations were compared against each other and observations as part of Phase 2 of the Air Quality Model Evaluation International Initiative. In the "no-feedback" mode, the aerosol direct and indirect effects were disabled, with the models reverting to either climatologies of aerosol properties, or a no-aerosol weather simulation. In the "feedback" mode, the model-generated aerosols were allowed to modify the radiative transfer and/or cloud formation parameterizations of the respective models. Annual simulations with and without feedbacks were conducted on domains over North America for the years 2006 and 2010, and over Europe for the year 2010. The incorporation of feedbacks was found to result in systematic changes to forecast predictions of meteorological variables, both in time and space, with the largest impacts occurring in the summer and near large sources of pollution. Models incorporating only the aerosol direct effect predicted feedback-induced reductions in temperature, surface downward and upward shortwave radiation, precipitation and PBL height, and increased upward shortwave radiation, in both Europe and North America. The feedback response of models incorporating both the aerosol direct and indirect effects varied across models, suggesting the details of implementation of the indirect effect have a large impact on model results, and hence should be a focus for future research. The feedback response of models incorporating both direct and indirect effects was also consistently larger in magnitude to that of models incorporating the direct effect alone, implying that the indirect effect may be the dominant process. Comparisons across modelling platforms suggested that direct and indirect effect feedbacks may often act in competition: the sign of residual changes associated with feedbacks often changed between those models incorporating the direct effect alone versus those incorporating both feedback processes. Model comparisons to observations for no-feedback and feedback implementations of the same model showed that differences in performance between models were larger than the performance changes associated with implementing feedbacks within a given model. However, feedback implementation was shown to result in improved forecasts of meteorological parameters such as the 2 m surface temperature and precipitation. These findings suggest that meteorological forecasts may be improved through the use of fully coupled feedback models, or through incorporation of improved climatologies of aerosol properties, the latter designed to include spatial, temporal and aerosol size and/or speciation variations. Crown Copyright (C) 2014 Published by Elsevier Ltd. All rights reserved. |
英文关键词 | Feedbacks;Air pollution forecasting;Weather forecasting;Air Quality Model Evaluation International;Initiative;Ozone;PM2.5;Direct effect;Indirect effect;Aerosol |
语种 | 英语 |
WOS记录号 | WOS:000358809600044 |
来源期刊 | ATMOSPHERIC ENVIRONMENT |
来源机构 | 美国环保署 |
文献类型 | 期刊论文 |
条目标识符 | http://gcip.llas.ac.cn/handle/2XKMVOVA/61885 |
作者单位 | 1.Environm Canada, Air Qual Res Div, Toronto, ON, Canada; 2.Environm Canada, Meteorol Res Div, Montreal, PQ, Canada; 3.US EPA, Atmospher Modeling & Anal Div, Res Triangle Pk, NC 27711 USA; 4.N Carolina State Univ, Dept Marine Earth & Atmospher Sci, Raleigh, NC 27695 USA; 5.Univ Aquila, I-67100 Laquila, Italy; 6.Univ Ljubljana, Ljubljana, Slovenia; 7.Ctr Excellence SPACE SI, Ljubljana, Slovenia; 8.Commiss European Communities, Joint Res Ctr, I-21020 Ispra, Italy; 9.RSE, Milan, Italy; 10.Univ Murcia, MAR UMU, E-30001 Murcia, Spain; 11.Enviroware, Milan, Italy; 12.Karlsruhe Inst Technol, IMK IFU, Garmisch Partenkirchen, Germany; 13.Environm Canada, Air Qual Res Div, Montreal, PQ, Canada; 14.ZAMG, Vienna, Austria; 15.UPM, Tech Univ Madrid, ESMG, Madrid, Spain; 16.Univ Aquila, CETEMPS, I-67100 Laquila, Italy |
推荐引用方式 GB/T 7714 | Makar, P. A.,Gong, W.,Milbrandt, J.,et al. Feedbacks between air pollution and weather, Part 1: Effects on weather[J]. 美国环保署,2015,115:442-469. |
APA | Makar, P. A..,Gong, W..,Milbrandt, J..,Hogrefe, C..,Zhang, Y..,...&Galmarini, S..(2015).Feedbacks between air pollution and weather, Part 1: Effects on weather.ATMOSPHERIC ENVIRONMENT,115,442-469. |
MLA | Makar, P. A.,et al."Feedbacks between air pollution and weather, Part 1: Effects on weather".ATMOSPHERIC ENVIRONMENT 115(2015):442-469. |
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