Influences of the Internal Mixing of Anthropogenic Aerosols on Global Aridity Change
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Influences of the mixing treatments of anthropogenic aerosols on their effective radiative forcing (ERF) and global aridity are evaluated by using the BCC_AGCM2.0_CUACE/Aero, an aerosol–climate online coupled model. Simulations show that the negative ERF due to external mixing (EM, a scheme in which all aerosol particles are treated as independent spheres formed by single substance) aerosols is largely reduced by the partial internal mixing (PIM, a scheme in which some of the aerosol particles are formed by one absorptive and one scattering substance) method. Compared to EM, PIM aerosols have much stronger absorptive ability and generally weaker hygroscopicity, which would lead to changes in radiative forcing, hence to climate. For the global mean values, the ERFs due to anthropogenic aerosols since the pre-industrial are–1.02 and–1.68 W m–2 for PIM and EM schemes, respectively. The variables related to aridity such as global mean temperature, net radiation flux at the surface, and the potential evaporation capacity are all decreased by 2.18/1.61 K, 5.06/3.90 W m–2, and 0.21/0.14 mm day–1 since 1850 for EM and PIM schemes, respectively. According to the changes in aridity index, the anthropogenic aerosols have caused general humidification over central Asia, South America, Africa, and Australia, but great aridification over eastern China and the Tibetan Plateau since the pre-industrial in both mixing schemes. However, the aridification is considerably alleviated in China, but intensified in the Arabian Peninsula and East Africa in the PIM scheme.
Key wordsglobal aridity internal mixing anthropogenic aerosols effective radiative forcing
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- Boucher, O., D. Randall, P. Artaxo, et al.,2013: Clouds and aerosols. Climate Change 2013: The Physical Science Basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change, T. F. Stocker et al., Eds., Cambridge University Press, Cambridge and New York, 87 pp.Google Scholar
- Feng, S., and Q. Fu, 2013: Expansion of global drylands under a warming climate. Atmos. Chem. Phys. Discuss., 13, 14,637–14,665, doi: 10.5194/acpd-13-14637-2013.Google Scholar
- IPCC, 2013: Climate Change 2013: The Physical Science Basis. Working Group I Contribution to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change. Stocker, T. F., et al., Eds. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, 1535 pp, doi: 10.1017/CBO9781107415324.Google Scholar
- Jing, X. W., and H. Zhang, 2012: Application and evaluation of McICA cloud–radiation framework in the AGCM of the National Climate Center. Chinese J. Atmos. Sci., 36, 945–958, doi: 10.3878/j.issn.1006-9895.2012.11155. (in Chinese)Google Scholar
- Myhre, G., D. Shindell, F. M. Bréon, et al.,2013: Anthropogenic and natural radiative forcing. Climate Change 2013: The Physical Science Basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change, T. F. Stocker et al., Eds., Cambridge University Press, Cambridge, 82 pp.Google Scholar
- Olivier, J. G. J., J. J. M. Berdowski, J. A. H. W. Peters, et al.,2001: Applications of EDGAR. Including a Description of EDGAR 3.0: Reference Database with Trend Data for 1970–1995. RIVM Report 773301001/NRP Report 410200051, Bilthoven, the Netherlands, RIVM.Google Scholar
- Pósfai, M., R. Simonics, J. Li, et al.,2003: Individual aerosol particles from biomass burning in southern Africa: 1. Compositions and size distributions of carbonaceous particles. J. Geophys. Res. Atmos., 108, 8483, doi: 10.1029/2002JD 002291.Google Scholar
- Zhao, S. Y., X. F. Zhi, H. Zhang, et al.,2014: Primary assessment of the simulated climatic state using a coupled aerosol–climate model BCC_AGCM2.0.1_CAM. Climatic Environ. Res., 19, 265–277, doi: 10.3878/j.issn.1006-9585.2012. 12015. (in Chinese)Google Scholar