1.2 Representation of Cloud Radiative Effects in Climate Sensitivity and Predictability (Invited Presentation)

Monday, 8 January 2018: 9:15 AM
Room 4ABC (ACC) (Austin, Texas)
Dennis L. Hartmann, Univ. of Washington, Seattle, WA

The past decades have seen significant advances in our ability to observe and model clouds. Confidence in the sign and magnitude of cloud feedback has increased, but much work remains to be done. Observations and models are in agreement that warm, low clouds are likely to reduce their area coverage in a warmed climate, contributing a likely important positive cloud feedback to climate change. The conversion of ice to liquid in high latitude clouds is a possibly important negative cloud feedback, but both the observations of ice/liquid fraction and the mixed-phase microphysics in climate models are in great need of improvement. We have no reliable global measurements of the mass of ice in the atmosphere. Extended ice clouds associated with deep convection in the tropics have a large role in climate, and they affect the atmospheric, surface and top of atmosphere energy balances. It is fairly well established that these ‘anvil’ clouds maintain a constant top temperature in a changing climate that would create a positive longwave cloud feedback, all else being equal. It is not well understood, however, how the area coverage and ice content of these clouds might change in a warmed climate. Active remote sensing and high-resolution cloud models suggest that the effect of radiative heating and in-cloud turbulence affects the area fraction and optical properties of anvil clouds, but these processes are not well resolved in global climate models. Observations and model ensembles are also beginning to converge on the magnitude of the indirect effects of aerosols on cloud properties. Critical requirements involve better observations of the amount of ice in low clouds, better methods of simulating radiation-turbulence interactions in clouds, and better methods of treating and validating mixed-phase microphysics in climate models.
- Indicates paper has been withdrawn from meeting
- Indicates an Award Winner