U.S. Department of Energy Office of Biological and Environmental Research

BER Research Highlights

Why Do General Circulation Models Overestimate the Aerosol Cloud Lifetime Effect?
Published: January 02, 2017
Posted: May 10, 2017

Detailed cloud modeling study identifies deficiency in climate model treatment of aerosol-cloud interactions

The Science  
One of the largest sources of uncertainties in current climate models is how much cloud properties that impact the climate, such as the amount they reflect sunlight, will change due to changes in the number of aerosol particles in the atmosphere. 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.  Longer-lived clouds then increase cloud cover and reflect more sunlight. However, observations of ship tracks show that the liquid water path in marine boundary-layer clouds can either increase (increasing reflection of sunlight) or decrease with increasing numbers of aerosol particles, depending on the environmental conditions. Studies using general circulation models (also known as global climate models or GCMs) have shown that liquid water path generally increases in the model when aerosol concentration is increased. Previous studies have “fixed” this issue in the models by adjusting a parameter known as the autoconversion rate, which controls how fast cloud droplets collide and combine to form droplets large enough to precipitate out of the cloud.  This study compares a more detailed model called a cloud-resolving model (CRM) with a single column version of a GCM to study cloud formation over the Atmospheric Radiation Measurement (ARM) Climate Research Facility Southern Great Plains (SGP) site.

The Impact
This study finds that the response of the autoconversion rate to aerosols is not the primary cause of the differences between GCMs and the more detailed CRM.  Instead, the researchers find a critical deficiency in the GCM used in this study, which is called the Community Atmosphere Model (CAM).  In CAM, the effect from increased mixing of drier air from above the cloud layer 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 vertical resolution were high enough to capture the growth of the cloud top, since the moist turbulence scheme and the evaporation of cloud water at the cloud top are not related to the cloud droplet number in the model, changes in aerosol number will not have a direct impact on the cloud top mixing or the liquid water path.  The results suggest that climate models need to include the dependence of cloud top growth and the evaporation/condensation process on cloud droplet number concentrations in order to more accurately simulate clouds and their interactions with aerosol particles.  Improved treatment of aerosol-cloud interactions in climate models will provide more accurate simulations of current and future climate.

One unique aspect of the current study is that the response of the liquid water path over the lifetime of the cloud is negative in the CRM while it is positive in CAM for the same forcing conditions. To examine this, we looked at the column integrated liquid water path source and sink terms in both models. The source term for liquid water path only includes droplet growth through condensation of water vapor while the loss terms include autoconversion and accretion of cloud droplets by rain. When we increase the aerosol numbers from 250 to 1000 cm-3, the liquid water path increase is relatively small in the CRM and substantially larger in CAM. Both models show decreased autoconversion and accretion, which act to increase the liquid water path. 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 on the simulated day. 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 the CRM, 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.

Contacts (BER PM)

Ashley Williamson
ASR Program Manager

Shaima Nasiri
ASR Program Manager

Sally McFarlane
ARM Program Manager

 (PI Contact)
Joyce Penner
University of Michigan

This work was supported by the DOE under the grant number DOE DE-SC0008486.  We acknowledge high performance computing support from National Energy Research Scientific Computing Center (NERSC).  Model forcing data were provided by the Atmospheric Radiation Measurement (ARM) Climate Research Facility.

Zhou, C. and Penner, J. E.: Why do general circulation models overestimate the aerosol cloud lifetime effect? A case study comparing CAM5 and a CRM, Atmos. Chem. Phys., 17, 21-29, doi:10.5194/acp-17-21-2017, 2017. (Reference link)

Topic Areas:

  • Research Area: Atmospheric System Research
  • Facility: DOE ARM User Facility

Division: SC-23.1 Climate and Environmental Sciences Division, BER


BER supports basic research and scientific user facilities to advance DOE missions in energy and environment. More about BER

Recent Highlights

May 10, 2019
Quantifying Decision Uncertainty in Water Management via a Coupled Agent-Based Model
Considering risk perception can improve the representation of human decision-making processes in age [more...]

May 09, 2019
Projecting Global Urban Area Growth Through 2100 Based on Historical Time Series Data and Future Scenarios
Study provides country-specific urban area growth models and the first dataset on country-level urba [more...]

May 05, 2019
Calibrating Building Energy Demand Models to Refine Long-Term Energy Planning
A new, flexible calibration approach improved model accuracy in capturing year-to-year changes in bu [more...]

May 03, 2019
Calibration and Uncertainty Analysis of Demeter for Better Downscaling of Global Land Use and Land Cover Projections
Researchers improved the Demeter model’s performance by calibrating key parameters and establi [more...]

Apr 22, 2019
Representation of U.S. Warm Temperature Extremes in Global Climate Model Ensembles
Representation of warm temperature events varies considerably among global climate models, which has [more...]

List all highlights (possible long download time)