Climate sensitivity and feedbacks
Understanding and quantifying the most important feedback processes operating in the climate system.
An important aspect of this work is to use both models and observations to try to establish links between physical processes operating in past, present and future climates. This involves the development and refinement of diagnostics and metrics for assessing model performance, and for isolating the key feedback mechanisms relevant to improved simulations of present-day climate and climate change.
Key aims
- Improve our understanding of the physical basis for cloud and water vapour feedbacks.
- Improve the representation of clouds, water vapour and the Earth's radiation budget in the Met Office climate models.
- Develop tools and analysis methods to enable observational data, e.g. from satellites, to be used to best effect for model development and evaluation.
- Use palaeoclimate simulations to understand physical processes relevant to projections of future climate.
Current projects
- Cloud Feedback Model Intercomparison Project (CFMIP): CFMIP is an international collaboration aimed at improving our understanding of clouds and cloud feedbacks. Key aims of this project are to improve collaboration between the process modelling and global climate modelling communities and to make optimal use of observational data to improve the representation of cloud processes in models.
- The CFMIP Observational Simulator Package (COSP): COSP has modules capable of simulating satellite observations in climate models. It is to be distributed to the modelling groups in order to evaluate model clouds (and contribute to the model development process) using observations from the new generation of space-borne sensors, e.g. CloudSAT and CALIPSO.
- The Palaeoclimate Modelling Intercomparison Project (PMIP): The aims of PMIP are to evaluate climate models under palaeoclimate conditions and improve our understanding of past climate changes.
- Implementation of the new prognostic cloud scheme (PC2) in the Unified Model.