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The influence of extratropical cloud phase and amount feedbacks on climate sensitivity

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Abstract

Global coupled climate models have large long-standing cloud and radiation biases, calling into question their ability to simulate climate and climate change. This study assesses the impact of reducing shortwave radiation biases on climate sensitivity within the Community Earth System Model (CESM). The model is modified by increasing supercooled cloud liquid to better match absorbed shortwave radiation observations over the Southern Ocean while tuning to reduce a compensating tropical shortwave bias. With a thermodynamic mixed-layer ocean, equilibrium warming in response to doubled CO2 increases from 4.1 K in the control to 5.6 K in the modified model. This 1.5 K increase in equilibrium climate sensitivity is caused by changes in two extratropical shortwave cloud feedbacks. First, reduced conversion of cloud ice to liquid at high southern latitudes decreases the magnitude of a negative cloud phase feedback. Second, warming is amplified in the mid-latitudes by a larger positive shortwave cloud feedback. The positive cloud feedback, usually associated with the subtropics, arises when sea surface warming increases the moisture gradient between the boundary layer and free troposphere. The increased moisture gradient enhances the effectiveness of mixing to dry the boundary layer, which decreases cloud amount and optical depth. When a full-depth ocean with dynamics and thermodynamics is included, ocean heat uptake preferentially cools the mid-latitude Southern Ocean, partially inhibiting the positive cloud feedback and slowing warming. Overall, the results highlight strong connections between Southern Ocean mixed-phase cloud partitioning, cloud feedbacks, and ocean heat uptake in a climate forced by greenhouse gas changes.

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Acknowledgements

We thank Brian Medeiros, Isla Simpson and Kris Karnauskas for helpful conversations related to this work and useful suggestions on the manuscript. We thank Dave Bailey and Bob Tomas for their help with setting up our model runs. We gratefully acknowledge high-performance computing support from Yellowstone (ark:/85065/d7wd3xhc) provided by NCAR’s Computational and Information Systems Laboratory, sponsored by the National Science Foundation. This work was supported by start-up funds awarded to J. E. Kay by the University of Colorado Cooperative Institute for Research in the Environmental Sciences and NSF award AGS 1554659. W. R. Frey is also supported by the Air Force Institute of Technology. The views expressed in this article are those of the authors and do not reflect the official policy or position of the United States Air Force, Department of Defense, or the US Government.

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  1. Cooperative Institute for Research in Environmental Sciences (CIRES) and Department of Atmospheric and Oceanic Sciences (ATOC), University of Colorado Boulder, 216 UCB, Boulder, CO, 80309, USA

    William R. Frey & Jennifer E. Kay

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Appendix 1

Appendix 1

In this appendix, we show that the cloud feedbacks produced by the experiment model are unaffected by model tuning. There are two model changes differentiating our experiment model from the control: (1) We adjust the Tice parameter in the shallow convection scheme to detrain more liquid and less ice in mixed-phase clouds (the Tice change). And (2) We tune the model by adjusting the relative humidity for low cloud formation (the tuning change). The tuning change is necessary in both the slab ocean and fully coupled frameworks to maintain a stable climate. However, the tuning change impacts cloud amount in a given climate state and therefore it seems possible that the tuning change could impact the cloud feedbacks and cloud amount decreases produced by the experiment model.

To determine whether this is the case we use an AMIP (Atmospheric Model Intercomparison Project)-style, or atmosphere only, modeling framework where surface temperatures and sea ice are prescribed to the model in a repeating annual cycle. With this framework, we can run the model with only the Tice change in isolation and not be concerned with global energy balance as the surface temperatures are prescribed. We prescribe sea surface temperatures and sea ice conditions to the AMIP model by taking averages of the monthly mean temperatures and sea ice conditions from 10 years of the SOM1xExp and SOM2xExp runs. We then run two AMIP runs for ten years each; one with pre-industrial CO2 levels (AMIP1xTiceOnly) and one with doubled CO2 levels. (AMIP2xTiceOnly). Both AMIP runs include the Tice change and omit the tuning change. See Table 4 for a full description of the two AMIP runs.

Comparing the total cloud feedback between the SOM Experiment runs and the AMIP TiceOnly runs reveals almost no change in the cloud feedback when the Tice change is made without the tuning change (Fig. 13a). We also see that the change in low cloud fraction due to doubled CO2, which is responsible for part of the positive cloud feedback at mid-latitudes, is virtually unchanged between the SOM Experiment runs and AMIP TiceOnly runs (Fig. 13b). Though inclusion of the tuning change does result in a lower cloud fraction in the SOM Experiment runs compared with the TiceOnly runs (not shown), this is true in both doubled CO2 and preindustrial runs and the difference between the two remains unchanged. The difference in cloud feedbacks between our experiment and control (Fig. 3) is primarily the result of our changes to shallow convective mixed-phase clouds (the Tice change) and largely unaffected by our model tuning change.

Table 4 Description of atmosphere-only model runs. All runs use the Community Earth System Model with the Community Atmosphere Model, version 5 [CESM(CAM5)] at one-degree horizontal resolution
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Fig. 13
figure 13

Shortwave cloud feedback (a) and change in low cloud fraction (b) resulting from a doubling of CO2. Slab Ocean Experiment (solid red) and AMIP TiceOnly (dotted black). Shortwave cloud feedback estimated using the APRP method (Taylor et al. 2007) and normalized with the local surface warming. Feedback and low cloud fraction difference for SOM Experiment calculated using the average of the last 20 years of SOM2xExp (years 41–60) and the average of the entire SOM1xExp run. Feedback and low cloud fraction difference for AMIPTiceOnly calculated using the average of years 1–10 of AMIP2xTiceOnly and AMIP1xTiceOnly

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Frey, W.R., Kay, J.E. The influence of extratropical cloud phase and amount feedbacks on climate sensitivity. Clim Dyn 50, 3097–3116 (2018). https://doi.org/10.1007/s00382-017-3796-5

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