Chang-Eui Park

Influence of cloud phase composition on climate feedbacks

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 −20°C (Experiment “C20”) and −40°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 −0.28 W m−2 K−1, respectively) but weaker cloud, temperature, and albedo feedbacks (by −0.20, 0.11, and −0.07 W m−2 K−1) 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.

Regional Variations in Potential Plant Habitat Changes in Response to Multiple Global Warming Scenarios

AbstractThis study examines the impacts of global warming on the timing of plant habitat changes in the twenty-first century using climate scenarios from multiple global climate models (GCMs). The plant habitat changes are predicted by driving the bioclimate rule in a dynamic global vegetation model using the climate projections from 16 coupled GCMs. The timing of plant habitat changes is estimated by the first occurrence of specified fractional changes (10%, 20%, and 30%). All future projections are categorized into three groups by the magnitude of the projected global-mean land surface temperature changes: low ( 3.5 K) warming. During the course of the twenty-first century, dominant plant habitat changes are projected in ecologically transitional (i.e., from tropical to temperate and temperate to boreal) regions. The timing of plant habitat changes varies substantially according to regions. In the low-warming group, habitat changes of 10% in southern Africa occur i...