Motivation: Earth System Models (ESMs) are highly-ambitious – they attempt to help understand and project how the physical climate and biogeochemical cycles of the globe changes under a wide-range of anthropogenic and natural forcings. Given the challenge of this task, it is perhaps unsurprising that different models project rather different degrees of climate change over the next 100 years. However, it is vital that this range is reduced to improve the quality of the information that policymakers, businesses, and the public, have to act upon. This proposal aims to contribute to reducing the spread of climate projections by enabling more complete evaluation of model outputs against observations, and by identifying Emergent Constraints - observable aspects of the contemporary Earth System that are most closely related to future projections.
Description: The experimental design of CMIP6 is now finalized. One purpose of the Diagnostic, Evaluation and Characterization of Klima (DECK) experiments and the CMIP6 historical simulations is to provide a basis for documenting model simulation characteristics. Towards that end infrastructure is being developed to allow analysis packages to be routinely executed whenever new model simulations are contributed to the CMIP archive at the Earth System Grid Federation (ESGF), utilizing observations from obs4MIPs and related efforts. Examples of available tools that target routine ESM evaluation in CMIP6 include the Earth System Model Evaluation Tool (ESMValTool) and the PCMDI Metrics Package (PMP). These tools can be used to comprehensively characterize agreement with observations (or “performance”) for the wide variety of models that will contribute to CMIP6, with first results being produced in time to be discussed at the workshop. The workshop will also focus on scientific improvements that are required to further advance ESM evaluation. Topics will include a better consideration of observational uncertainty, internal variability and model tuning. It will also emphasize advanced process- or regime-oriented diagnostics that can be used to understand the sources of errors and uncertainties in models, thereby highlighting specific areas requiring model improvements. A related open scientific question is the relation between present-day model performance and future projections. We will review and discuss Emergent Constraint studies that use observations to constrain climate sensitivity. Innovative methods that can be used to more objectively weight multi-model climate projections will also be discussed, taking into account both model performance and model inter-dependence. Advancing on these important topics requires the modelling community to get together with the observational community, scientists involved in CMIP6-Endorsed MIPs, statisticians and users of climate model output.
Relevance: The climate projections considered in IPCC AR5 were largely based on ESM experiments defined and internationally coordinated as part of CMIP5. CMIP is providing understanding of past, present and future climate variability and change, but intelligent use of CMIP results requires an awareness of their limitations. It is essential, therefore, to subject models to a systematic evaluation against observations and to further improve evaluation methods and techniques. The benefits of a more efficient and systematic approach to model evaluation are clear. The recording of a set of informative diagnostics and metrics would enable anyone interested in CMIP research to obtain a broad overview of model performance and simulation behavior. Emergent Constraint studies can guide model development priorities towards processes crucial to the magnitude and spread of future climate change, inform future observational priorities, and ultimately reduce uncertainties in climate sensitivity. These efforts would also substantially support the IPCC AR6 by facilitating the assessment of the models in IPCC WG I and by supporting WGs II and III through a better quantification of related uncertainties.
Workshop Topic (s):
- Atmospheric Composition
- Carbon Cycle
- Climate Variability and Change (including Climate Modeling)
- Human Contributions & Responses