Discussions on Cloud Feedbacks and Model Variability in CMIP6 Models

Author: ORCID icon orcid.org/0000-0002-8154-2236
Kelleher, Mitchell, Environmental Sciences - Graduate School of Arts and Sciences, University of Virginia
Grise, Kevin, AS-Environmental Sciences (ENVS), University of Virginia

While global climate models have improved over recent model generations, large uncertainty still remains that prevents confidence in future projections of climate change. Two such sources of uncertainty that remain include the role of clouds and their radiative feedbacks on climate and the role of internal variability. This dissertation examines selected aspects of these two sources in order to better understand the future projections of the models.
Changes in midlatitude clouds as a result of shifts in general circulation patterns are widely thought to be a potential source of radiative feedbacks onto the climate system. Previous work has suggested that two general circulation shifts anticipated to occur in a warming climate, poleward shifts in the midlatitude jet streams and a poleward expansion of the Hadley circulation, are associated with differing effects on midlatitude clouds. My study on this topic finds that, due to incorrectly placed dynamical features, models do not capture the observed cloud radiative effects for these circulation shifts, even when the observed sensitivities of clouds to dynamics are used in place of the models’ sensitivities.
Climate change is expected to alter mean and extreme temperature and precipitation over the twenty-first century. However, regional changes in these fields remain difficult to project. By examining the range of possible trends in North American mean and extreme temperature and precipitation, I constructed storylines of plausible trends in these fields, and find that the majority of variance in the temperature trends is due to model-to-model differences the while precipitation trends vary largely due to internal variability. Furthermore, changes in the statistical moments of the winter temperature distribution are largely related to the degree of Arctic amplification present in the model, while changes in the summer temperature distribution can largely be described by shifts in the mean alone.

PHD (Doctor of Philosophy)
Cloud Feedbacks, Internal Variability
Issued Date: