Declining aerosols in RCP4.5

Posted by on Sep 1, 2015 in Abstracts, Abstracts 2014

Assessing the effects of declining aerosols in RCP4.5


All the Representative Concentration Pathways (RCPs) include declining aerosol emissions during the 21st century, but the effects of these declines on climate projections have had little attention.

We compare two projections for 2006−2100 using the CSIRO-Mk3.6 model. One (RCP45) follows the usual RCP4.5; the other (RCP45A2005) has identical forcing, except that anthropogenic aerosols are fixed at 2005 levels. The global-mean surface warming in RCP45 is 2.3°C per 95 years, of which almost half (1.1°C) is caused by declining aerosols. The warming due to declining aerosols is almost twice as strong in the Northern Hemisphere (NH) as in the Southern Hemisphere (SH). This warming contrast alters the Hadley circulation, with a trend of increasing ascent (subsidence) in the NH (SH).

For precipitation changes, the effects of declining aerosols are larger than those of increasing greenhouse gases due to decreasing atmospheric absorption by black carbon: 63% of the projected global-mean precipitation increase of 0.16 mm per day is caused by declining aerosols.

The global-mean aerosol effective radiative forcing (ERF, including indirect effects) in CSIRO-Mk3.6 is −1.4 W m−2 in 2000 relative to 1850. This is stronger than the average of other CMIP5 models, which raises the question of whether the effects of declining aerosols are also substantial in other models.
Comparing 13 CMIP5 models, we find a correlation of −0.54 (significant at 5%) between aerosol ERF in 2000 and projected global-mean surface warming in RCP4.5; thus, models that have more negative aerosol ERF in the present climate tend to project stronger warming during 2006−2100.

These results suggest that aerosol forcing substantially modulates projected climate response in RCP4.5. Further, single-forcing simulations, which are most often used for detection and attribution of historical climate change, can be a valuable tool for understanding climate projections.