Why Do General Circulation Models Overestimate the Aerosol Cloud Lifetime Effect?

Penner, J. E., University of Michigan

Cloud-Aerosol-Precipitation Interactions

Cloud Life Cycle, Cloud-Aerosol-Precipitation Interactions

Zhou C and J Penner. 2017. "Why do general circulation models overestimate the aerosol cloud lifetime effect? A case study comparing CAM5 and a CRM." Atmospheric Chemistry and Physics, 17(1), 10.5194/acp-17-21-2017.


LWP is shown for the GCE (left) and CAM (right) simulations for increasing surface aerosol concentrations.


This figure shows the normalized LWP as a function of surface aerosol concentration from CAM (red curves) and GCE (blue curves). A case for CAM using an autoconversion rate proportional to Nd-0.6 (CAM, auto06), as well as a case in which autoconversion is independent of Nd (CAM, auto00), are shown. The GCE model was run with a horizontal grid resolution of 50m (default case) and 100 km.


LWP is shown for the GCE (left) and CAM (right) simulations for increasing surface aerosol concentrations.

This figure shows the normalized LWP as a function of surface aerosol concentration from CAM (red curves) and GCE (blue curves). A case for CAM using an autoconversion rate proportional to Nd-0.6 (CAM, auto06), as well as a case in which autoconversion is independent of Nd (CAM, auto00), are shown. The GCE model was run with a horizontal grid resolution of 50m (default case) and 100 km.

Science

Traditionally, aerosols have been thought to lengthen cloud lifetime by increasing droplet number and reducing droplet size, thereby delaying and reducing the formation of rain in clouds. These longer-lived clouds would then increase cloud cover and reflect more sunlight. Yet observational evidence for these lifetime effects is limited and contradictory. Moreover, observations of ship tracks show that the liquid water path (LWP) in marine boundary-layer clouds can either increase (increasing reflection) or decrease with increasing aerosol particles. Yet most GCM studies have determined that LWP generally increases. Previous studies have “fixed” this by tuning the autoconversion rates within GCMs.

We compared a cloud-resolving model (the Goddard Cumulus Ensemble (GCE)) with a single-column version of the CAM5.3 to study cloud formation over the Atmospheric Radiation Measurement (ARM) Climate Research Facility Southern Great Plains (SGP) site. We find that the response of the autoconversion rate to aerosols is not the primary cause of the differences between GCMs and more highly resolved GCE.

Impact

One critical deficiency of CAM for this case is that the effect from increased mixing of drier air from above the cloud layer through enhanced entrainment caused by increased aerosol numbers is missing. First, CAM is not able to simulate the growth of the cloud top due to its coarse vertical resolution. However, even if the CAM vertical resolution were high enough to capture the growth of the cloud top, since the moist turbulence scheme and the evaporation of cloud condensate in the cloud macrophysics parameterization at the cloud top are not related to the cloud droplet number, aerosol number will not have a direct impact on the cloud top mixing or the LWP.

Summary

One unique aspect of the current study is that the response of the LWP over the lifetime of the cloud is negative in the CRM while it is positive in the CAM for the same forcing conditions. To examine this, we looked at the column integrated LWP source and sink terms in both models. The source term for LWP only includes the net condensation term (Conden–Evap) while the loss terms include autoconversion and accretion. When we increase the aerosol numbers from 250 to 1000 cm-3, the LWP increase is relatively small in GCE and substantially larger in CAM. Both models show decreased AutoC+Accre, which acts to increase the LWP. This is expected as increased aerosol numbers increase the cloud droplet number, which decreases the autoconversion rate. But CAM shows much larger changes, especially before 13:00. This is mainly due to the fact that the two models use different schemes to parameterize the autoconversion and accretion processes, though the processes decrease with aerosol number in both schemes. In addition, in GCE, the decreased autoconversion is largely offset or even outweighed by increased evaporation. The increased evaporation near the cloud top suggests that higher aerosol number concentrations lead to smaller cloud droplet sizes and enhanced evaporation at the cloud top, which can then decrease the temperature slope near the cloud top and promote the sinking of entrained air into the cloud layer.