Clouds, circulation and climate sensitivity

Clouds, circulation and climate sensitivity

Humanity has a primordial fascination with clouds. The meteorological and hydrology communities, through decades of observations and research, have come to understand that cloud processes - from microphysics of initial nucleation to superstorms viewed from satellites - provide vital information in weather prediction, particularly for precipitation. Understanding clouds from a climate perspective introduces new and challenging questions, questions which in turn challenge our overall assumptions of how our moist cloudy atmosphere actually works. 

As one of the main modulators of heating in the atmosphere, clouds control many other aspects of the climate system. Limited understanding of clouds is the major source of uncertainty in climate sensitivity, but it also contributes substantially to persistent biases in modelled circulation systems.

"Clouds, Circulation and Climate Sensitivity" is one of seven Grand Challenges of the WMO World Climate Research Programme. Four main intiatives make up this Grand Challenge:

  • Climate and hydrological sensitivity 
  • Coupling clouds to circulations
  • Changing patterns
  • Towards more reliable models


Initiative on climate sensitivity

Aim: Design critical tests for the treatment of cloud process climate models, whose application will help assess the most likely estimates of climate sensitivity.
Focus: Intensify efforts to identify causes of inter-model differences in sensitivity; Interpret robust features; Explain extreme behaviours; Unravel uncertainties and propose strategies to tackle them.








Initiative on coupling clouds to circulation

Aim: Tackle the parameterization problem through a better understanding the interaction between cloud / convective processes and circulation systems.
Focus: Lessons from observations and cloud-resolving modelling over large domains; Interaction between diabatic heating and large-scale dynamics.










Initiative on changing patterns

Aim: Better anticipate how large-scale atmospheric circulation will respond to anthropogenic forcings (GHG, aerosols, ozone).
Focus: Role of local vs large-scale or remotely forced changes in driving regional changes; Identify robust responses; Interpret uncertain components; Assess the impact of model biases or shortcomings on regional responses, leveraging the past record.






Initiative towards more reliable models

Aim: Interpret and reduce model errors to gain confidence in projections and predictions.
Focus: Long-standing model biases (at least a few of them); Understand how model errors or shortcomings impact projections and predictions; Gain physical understanding of the climate system through model development.









For more information, see this White Paper from the World Climate Research Programme.