Influence of cloud phase composition on climate feedbacks

Abstract

The ratio of liquid water to ice in a cloud, largely controlled by the presence of ice nuclei and cloud temperature, alters cloud radiative effects. This study quantitatively examines how the liquid fraction of clouds influences various climate feedbacks using the NCAR Community Atmosphere Model (CAM). Climate feedback parameters were calculated using equilibrated temperature changes in response to increases in the atmospheric concentration of carbon dioxide in CAM Version 3.0 with a slab ocean model. Two sets of model experiments are designed such that cloud liquid fraction linearly decreases with a decrease in temperature down to À20°C (Experiment "C20") and À40°C (Experiment "C40"). Thus, at the same subzero temperature, C20 yields fewer liquid droplets (and more ice crystals) than C40. Comparison of the results of experiments C20 and C40 reveals that experiment C20 is characterized by stronger cloud and temperature feedbacks in the tropics (30°N-30°S) (by 0.25 and À0.28 W m À2 K À1, respectively) but weaker cloud, temperature, and albedo feedbacks (by À0.20, 0.11, and À0.07 W m À2 K À1) in the extratropics. Compensation of these climate feedback changes leads to a net climate feedback change of~7.28% of that of C40 in the model. These results suggest that adjustment of the cloud phase function affects all types of feedbacks (with the smallest effect on water vapor feedback). Although the net change in total climate feedback is small due to the cancellation of positive and negative individual feedback changes, some of the individual changes are relatively large. This illustrates the importance of the influence of cloud phase partitioning for all major climate feedbacks, and by extension, for future climate change predictions.

Sensitivity Study on the Influence of Cloud Microphysical Parameters on Mixed-Phase Cloud Thermodynamic Phase Partitioning in CAM5

“…3. More details on the methodology of calculating SCFs from CALIOP observations can be found in Choi et al (2010) and Tan et al (2014).…”

“…In addition to the purely radiative effect of liquid droplets and ice crystals alone, various climate feedbacks act to further amplify or damp the radiative forcing effect of cloud phase. This will likely impact the transient climate response (TCR) and has been shown to result in a wide range in equilibrium climate sensitivity (ECS), which precludes accurate projections of future climate change (Mitchell et al 1989;Li and LeTreut 1992;Tsushima et al 2006;Choi et al 2014). Thus, accurately representing phase partitioning in mixed-phase clouds in GCMs is critical for future climate projections.…”

Role of updraft velocity in temporal variability of global cloud hydrometeor number

“…Cloud short-wave albedo also depends on particle size, because more and smaller hydrometeors yield a higher optical depth for the same water path (1). Global climate models (GCMs) predict a diversity of liquid and ice water paths (3), as well as cloud hydrometeor sizes, and the treatment of initial hydrometeor formation, i.e., droplet activation or ice nucleation, contributes to this spread for all cloud types (4,5).…”

Cloud Phase Changes Induced by CO2 Warming—a Powerful yet Poorly Constrained Cloud-Climate Feedback

“…A more recent modeling study presented model simulations that were dedicated specifically to the investigation of the cloud phase feedback and reported a higher climate sensitivity in simulations that had more liquid relative to ice in mixed-phase clouds [24]. However, the difference was more subtle compared to the few previous comparable model experiments [1,3,21].…”