Satellite methods underestimate indirect climate forcing by aerosols

Abstract

Satellite-based estimates of the aerosol indirect effect (AIE) are consistently smaller than the estimates from global aerosol models, and, partly as a result of these differences, the assessment of this climate forcing includes large uncertainties. Satellite estimates typically use the present-day (PD) relationship between observed cloud drop number concentrations (N(c)) and aerosol optical depths (AODs) to determine the preindustrial (PI) values of N(c). These values are then used to determine the PD and PI cloud albedos and, thus, the effect of anthropogenic aerosols on top of the atmosphere radiative fluxes. Here, we use a model with realistic aerosol and cloud processes to show that empirical relationships for ln(N(c)) versus ln(AOD) derived from PD results do not represent the atmospheric perturbation caused by the addition of anthropogenic aerosols to the preindustrial atmosphere. As a result, the model estimates based on satellite methods of the AIE are between a factor of 3 to more than a factor of 6 smaller than model estimates based on actual PD and PI values for N(c). Using ln(N(c)) versus ln(AI) (Aerosol Index, or the optical depth times angstrom exponent) to estimate preindustrial values for N(c) provides estimates for N(c) and forcing that are closer to the values predicted by the model. Nevertheless, the AIE using ln(N(c)) versus ln(AI) may be substantially incorrect on a regional basis and may underestimate or overestimate the global average forcing by 25 to 35%.

Fig. 1.

Slope of the regression between ln(N_c) and ln(AOD) (Top) and ln(AI) (Bottom) for the PD simulation for all seasons for the 14 regions used in the analysis in ref. . (See Table S1.)

Fig. 2.

Slope computed from the difference in the average values of ln(N_c) and ln(AOD) (Top) and ln(AI) (Bottom) for the PD and PI simulations for all seasons for the regions in ref. .

Fig. 3.

Scatter plot of ln(N_c) versus ln(AOD) and versus ln(AI) for North America in JJA and DJF and for Asia in MAM. The red line shows the best-fit linear regression from PD values, whereas the blue line shows the best fit linear regression for the PI values. The black line shows the fit computed using the difference in the average of the PD and PI values.

Fig. 4.

Shortwave indirect forcing from the true modeled PD and PI values of N_c (Top), from the PI N_c based on the regression between N_c and AOD (Middle), and from the PI N_c based on the regression between N_c and AI (Bottom). The satellite estimates of forcing include only the region from 60 °N to 60 °S. If the true model forcing is restricted to this region, the total forcing is -1.56 Wm^-2.