Variability, timescales, and nonlinearity in climate responses to black carbon emissions

Black carbon (BC) particles exert a potentially large warming influence on the Earth system. Reductions in BC emissions have attracted attention as a possible means to moderate near-term temperature changes. For the first time, we evaluate regional climate responses, nonlinearity, and short-term tra...

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Bibliographic Details
Published in:Atmospheric Chemistry and Physics
Main Authors: Yang, Yang, Smith, Steven J., Wang, Hailong, Mills, Catrin M., Rasch, Philip J.
Format: Text
Language:English
Published: 2019
Subjects:
Online Access:https://doi.org/10.5194/acp-19-2405-2019
https://www.atmos-chem-phys.net/19/2405/2019/
Description
Summary:Black carbon (BC) particles exert a potentially large warming influence on the Earth system. Reductions in BC emissions have attracted attention as a possible means to moderate near-term temperature changes. For the first time, we evaluate regional climate responses, nonlinearity, and short-term transient responses to BC emission perturbations in the Arctic, midlatitudes, and globally based on a comprehensive set of emission-driven experiments using the Community Earth System Model (CESM). Surface temperature responses to BC emissions are complex, with surface warming over land from midlatitude BC perturbations partially offset by ocean cooling. Climate responses do not scale linearly with emissions. While stronger BC emission perturbations have a higher burden efficiency, their temperature sensitivity is lower. BC impacts temperature much faster than greenhouse gas forcing, with transient temperature responses in the Arctic and midlatitudes approaching a quasi-equilibrium state with a timescale of 2–3 years. We find large variability in BC-induced climate changes due to background model noise. As a result, removing present-day BC emissions results in discernible surface temperature changes for only limited regions of the globe. In order to better understand the climatic impacts of BC emissions, both the drivers of nonlinear responses and response variability need to be assessed across climate models.