Chien Wang's Group

CLIMATE EFFECTS OF ANTHROPOGENIC AEROSOLS:

Human activities have increased tropospheric aerosol abundance through emissions of particulate matter (primary production) or precursors leading to the formation of aerosols (secondary production). The climate effect of these anthropogenic aerosols remains one of the most uncertain factors in current predictions of future climate. We use interactive aerosol-climate models and various observational data to study this effect. Our research effort is specifically aimed towards achieving a better understanding of the climate response to anthropogenic absorbing aerosols (mainly black carbon aerosols). Using our model and observational data, we have found that absorbing aerosols can significantly affect the distribution and strength of tropical precipitation systems, including the Pacific ITCZ and the Indian monsoon.

Figure 1.  Modeled zonal mean changes in convective precipitation caused by black carbon aerosols. Results are derived from 6 runs including BC emissions from whole global (TE) or only from East Asia (EA), Europe (EU), North America (NA), South Asia (SA), or rest of the world outside above major regions (RW), respectively.  SUM equals a summation of the effects of all regional emission runs. Each of these 6 model runs lasts 60 years. All data are the last-20-year means derived from these 60-year long simulations.  The fact that the result of TE run is much smaller than SUM suggests a strong non-linearity in related processes. (Wang, 2009, Ann. Geophys, 27, 3705-3711).

Figure 2. May-June (MJ) average changes in convective precipitation (dm/season) derived from the model runs with: (1) both scattering and absorbing aerosols (COM); (2) only absorbing aerosols (ABS); and (3) only scattering aerosols (SCA) for India and surrounding regions. Also shown is the observed precipitation change (land-only; dm/season) derived from the data of the Climate Research Unit (CRU) at the University of East Anglia. Model results shown are based on year 41-60 mean differences with a reference run that exclude all aerosol effects. CRU results are derived from differences between 20-year means of 1981-2000 and 1946-1965, and based on the version 2.1 dataset with 0.5 degree. Aerosol levels were derived based on present-day emission estimations. From (Wang et al., 2009, Geophys. Res. Lett., 36, L21704).

Selected publications:

Wang, C., 2004, J. Geophys. Res., 109, D03106.

Wang, C. 2007, Geophys. Res. Lett., 34, L05709.

Kim, D., C. Wang, A.M.L. Ekman, M. C. Barth, and P. Rasch, 2008, J. Geophys. Res., 113, D16309.

Wang, C., 2009, Ann. Geophys, 27, 3705-3711.

Wang, C., G.-R. Jeong, and N. Mahowald, 2009, Atmos. Chem. Phys., 9, 3935–3945.

Wang, C., D. Kim, A. M. L. Ekman, M. C. Barth, and P. Rasch, 2009, Geophys. Res. Lett., 36, L21704.

Jeong, G.-R. and C. Wang, 2010, Atmos. Chem. Phys., 10, 8373-8389. 

AEROSOL-CLOUD-PRECIPITATION INTERACTION:

Aerosols are the primary catalyst for liquid and ice cloud particle formation in the atmosphere. Changes in aerosol properties are thus expected to affect clouds and precipitation. Current global models still cannot explicitly resolve certain critical processes involving aerosol-cloud interaction and the influence of such interactions on precipitation. We develop and use a three-dimensional cloud-resolving model coupled with the size- and mixing-dependent aerosol module to study the detailed aerosol-cloud interaction and its impacts on precipitation and radiation. Some of these results have been incorporated in our global scale modeling efforts to improve the aerosol-climate model or to assist data analyses.

Figure 1. Redistributions of various types of aerosols by a modeled deep convective cloud, all from a set of three-dimensional cloud-resolving simulations (based on Ekman et al., 2006, J. Atmos. Sci., 63, 682-696.)

Figure 2. Statistical results of a modeled tropical deep convective cloud in response to the change of prescribed initial profiles of cloud condensation nuclei (CCN). Results were derived from a set of 30 three-dimensional cloud-resolving simulations. (Based on Wang, 2005,J. Geophys. Res., 110, D21211).

Selected publications:

Ekman, A., C. Wang, J. Ström, and J. Wilson, 2004, Atmos. Chem. Phys., 4, 773-791.

Wang, C., 2005, J. Geophys. Res., 110, D21211 and D22204.

Ekman, A., C. Wang, J. Ström, and R. Krejci, 2006, J. Atmos. Sci., 63, 682-696.

Ekman, A. M. L., A. Engström, C. Wang, 2007, Q. J. Roy. Meteor. Soc., 133B, 1439-1452. 

AFFILIATED WITH:

JOINT PROGRAM ON THE SCIENCE AND POLICY OF GLOBAL CHANGE

WEBSITE:

http://web.mit.edu/wangc

http://globalchange.mit.edu/people/all-personnel.php?id=56