J1.18 Changes in the vertical temperature structure associated with carbonaceous aerosols

Thursday, 18 January 2001: 1:58 PM
Yang Zhang, University of Michigan, Ann Arbor, MI; and J. E. Penner, C. C. Chuang, B. D. Santer, and K. Taylor

Carbonaceous aerosols can affect climate through absorption and scattering of solar radiation and also trapping of longwave radiation. In this study, we calculated the effect of fossil fuel black carbon and biomass carbon aerosols on the local temperature vertical profile.

Two simulations are carried out, one with the aerosols interacting with the radiation field and the other without. The simulation where aerosols do not affect the radiation field is considered to be the control run. The temperature difference between the surface and lower troposphere is correlated with the column burden of absorbing aerosols. If aerosols change the temperature profile by reducing the surface temperature and increasing the temperature of the mid-tropospheric layer due to absorption of solar ratiation and reduction of solar radiation at the ground, a negative correlation rsults.

Our analysis shows that biomass aerosols appear to cool the surface relative to mid-troposphere temperature. The average surface temperature change is -0.3 K for biomass carbon. A warming effect on the upper troposphere is also detected for biomass aerosol. For fossil fuel black carbon a slightly warming effect at the surface relative to the lower and mid troposphere is detected in the model results. The correlation analysis of temperature difference and aerosol column burden shows there is an increased negative correlation for biomass carbon and increased positive correlation for fossil fuel black carbon, compared to the control case. To judge whether such a change in the correlation between absorbing aerosols and temperature change is significant, we develop a distribution of correlation coefficients for the control simulation. The significance of the magnitude of the correlation coefficient can be calculated from the distribution of correlation coefficients for the control run. The results of this significance analysis will be presented.

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