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. 2018 Nov 16;45(21):12023-12031.
doi: 10.1029/2018GL079826. Epub 2018 Nov 8.

Understanding Rapid Adjustments to Diverse Forcing Agents

Affiliations

Understanding Rapid Adjustments to Diverse Forcing Agents

C J Smith et al. Geophys Res Lett. .

Abstract

Rapid adjustments are responses to forcing agents that cause a perturbation to the top of atmosphere energy budget but are uncoupled to changes in surface warming. Different mechanisms are responsible for these adjustments for a variety of climate drivers. These remain to be quantified in detail. It is shown that rapid adjustments reduce the effective radiative forcing (ERF) of black carbon by half of the instantaneous forcing, but for CO2 forcing, rapid adjustments increase ERF. Competing tropospheric adjustments for CO2 forcing are individually significant but sum to zero, such that the ERF equals the stratospherically adjusted radiative forcing, but this is not true for other forcing agents. Additional experiments of increase in the solar constant and increase in CH4 are used to show that a key factor of the rapid adjustment for an individual climate driver is changes in temperature in the upper troposphere and lower stratosphere.

Keywords: PDRMIP; kernels; radiative forcing; rapid adjustments.

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Figures

Figure 1
Figure 1
Instantaneous radiative forcing, effective radiative forcing, and rapid adjustments for five different climate change drivers. Each bar represents a multimodel mean and each model is given equal weight with up to six different methods of calculating each adjustment for each model (Figure S3 in the supporting information). The error bars are the 95% confidence range weighting each method and model sample equally.
Figure 2
Figure 2
Effective radiative forcing, rapid adjustments, and residuals in models where instantaneous radiative forcing is known to be exactly 0. Each point is a multikernel mean for each model and outlined bars show the multimodel means from this subset of models.
Figure 3
Figure 3
Rapid adjustments decomposed by mechanism. The bars represent multimodel means. The error bars are the 95% confidence range weighting each method and model sample equally (see Figure S3 for individual model and kernel responses).
Figure 4
Figure 4
Cloud adjustments in each model using the Monthly Mean Partial Radiative Perturbation method. National Center for Atmospheric Research‐Community Earth System Model version 1‐Community Atmospheric Model version 5 (NCAR‐CESM1‐CAM5) is excluded as not all required diagnostics are present.

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