Understanding climate feedbacks with idealized models
Date: 10 January 2022
University of Exeter
PhD in Mathematics
The global mean surface air temperature change in response to global warming, namely climate sensitivity, plays a central role in climate change studies, and the estimates of climate sensitivity depend critically on the climate feedbacks, the processes that can either amplify or dampen the responses of the climate system to external ...
The global mean surface air temperature change in response to global warming, namely climate sensitivity, plays a central role in climate change studies, and the estimates of climate sensitivity depend critically on the climate feedbacks, the processes that can either amplify or dampen the responses of the climate system to external perturbations. The goal of this thesis is to understand climate feedbacks through idealized climate models. The first part explores the roles of climate feedbacks in polar amplification of surface temperature change. By running idealized aquaplanet simulations with a hierarchy of radiation schemes (without sea ice and clouds), and by decomposing the total surface temperature responses into different components through the radiative kernel method, we find the poleward heat transport, the lapse rate and Planck feedbacks contribute to amplified surface temperature changes in the polar region, while the forcing and water vapor feedback dominates the tropical temperature change. The second part investigates the underlying causes of cloud feedback uncertainty with a simple cloud scheme. The scheme diagnoses the cloud fraction from relative humidity and other variables such as inversion strength, and its optical properties such as effective radius and cloud water content are prescribed as simple functions of temperature. The simulations show this scheme can capture the basic feature of cloud climatology. Through a series of perturbed parameter ensemble global warming simulations, part of the inter-model spread of cloud feedbacks among general circulation models can be reproduced. In addition, the low cloud amount feedback, especially over the low-latitude subsidence regions, is the largest contributor to the net cloud feedback uncertainty. The cloud controlling factor analysis suggests that the sea surface temperature (SST) and estimated inversion strength (EIS) have opposite impacts on marine low cloud amounts, but their responses to SST rather than EIS seem to bring larger uncertainty. Finally, the equilibrium climate sensitivity and cloud feedback over tropical subsidence regimes show a robust linear relationship, implying a possible constraint for climate sensitivity.
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