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1. Improvement in AR5

    Cloud Research

 

 

  Thanks to advances in computer power and the results from the cloud process models (CRMs and LES models), AR5 has better understanding of cloud processes associated with cumulus convection, cloud formation processes in mixed-phase and ice clouds. Improvement has been made in understanding cloud feedbacks on a warming climate, such as changes in the altitude of cloud top, pole-ward shift of large-scale circulation and cloud system, and the corresponding impact on precipitation patterns. Understanding of cloud rapid responses has also been improved, such as reduction in cloud cover soon after warming of troposphere, as well as the variability associated with existence of black carbons.

   Aerosol Research

 

 

    Aerosol process studies have great progress, thanks to the advances in remote-sensing instruments and cloud modeling studies. There is better understanding of nucleation and condensation processes associated with aerosol formation and in aerosol chemical composition and mixing state. Better understanding of aerosol-cloud interactions and aerosol rapid response to climate warming has also been made. Advances in remote-sensing technique further helps differentiate clouds from aerosols and vice versa, therefore, being helpful for studying aerosol-cloud interactions.

    Modeling Study

  All the above-mentioned process studies on clouds, aerosols, and their interactions with each other and the climate, have significantly improved representation of cloud and aerosol fields, parameterization of aerosol-cloud interactions and their responses and feedbacks on climate in GCMs

2. Remaining issues in AR5

    Cloud Research

   Understanding of low-cloud processes and mixed-phase/ice clouds still contain great uncertainties.

    Great uncertainties exist in aerosol-cloud interactions and therefore estimating their responses to and feedbacks on climate change.

   Aerosol Research

    Modeling Study

  •   Radiative forcing due to aerosol and aerosol-cloud interactions still contribute to the largest uncertainties in model estimate of anthropogenic radiative forcing and thus influencing on GCMs' long-term projections.

  •   Parameterization of cloud feedbacks remains to cause the largest model spread form climate sensitivity.

 

         Indeed due to the existence of these imperative uncertainties, the CMIP6 proposal has listed “Clouds, Circulation and Climate Sensitivity” as the No.1 issue out of its six WCRP grand challenges [Meehl et al., 2014].

3. Updates since AR5

Progresses have been made after AR5, reflected in some selected publications listed below, although they just cover a small fraction of those progresses.

 

  • Sherwood et al. (2014) Nature – Convective mixing & model climate sensitivity

  • Ban-Weiss et al. (2014) JGR – Clouds, aerosols, their interactions by satellite simulator

  • Rosenfeld et al. (2014) Science – Aerosol-cloud interactions

  • Zelinka et al. (2014) JGR – modeling aerosol-cloud-radiation interaction

  • Meehl et al. (2014) EOS – CMIP 6 initiative

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