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. Five main initiatives make up this Grand Challenge:
- Climate and hydrological sensitivity
- Coupling clouds to circulations
- Changing patterns
- Leveraging the past record
- 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.
Leveraging the past record
Aim: Exploitation of observations of the recent past, or proxies for longer-term changes, to better constrain cloud processes and feedbacks.
Focus: Analysis of decadal/multi-decadal records from satellite and in-situ observations; Improvement of paleo-climates reconstructions and syntheses; Comparisons of past vs future changes.
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.