The Coupled Model Intercomparison Project (CMIP) is instrumental in advancing our understanding of the Earth’s climate system and its future projections. However, Earth system models (ESM) exhibit disparities in critical aspects, particularly in their responses to anthropogenic forcings and the dynamical coupling of physical and biogeochemical systems. Given that the Earth system science community, and notably the IPCC, relies on CMIP outputs to inform policy and mitigation strategies, it becomes imperative to address these inherent uncertainties through a multidisciplinary approach that unites atmospheric, oceanic, and terrestrial modeling analyses. In this session, we invite studies that investigate uncertainties and model disagreements across all facets associated with the CMIP ensembles. These may include, but are not limited to, the following contributions:
1. Identification of processes and key entities with significant disparities across CMIP models: Quantifying sources of uncertainty across CMIP models, which may include i) internal variability, ii) process representations/model parameterization, iii) ESM architecture, and iv) external forcing.
2. Use of reduced complexity models and emulators: Exploring the uncertainty range with computationally fast model approaches, particularly the parts of the distribution not well represented by the CMIP ensembles.
3. Critical scientific priorities for future CMIP/Earth system model development: Recognizing and comprehending uncertainties and their underlying mechanisms are essential for guiding future model development and refining climate projections. We welcome contributions that focus on enhancing model performance and reducing uncertainties across disciplines for future CMIP iterations.
4. Opportunities, challenges, and constraints in using CMIP output for impact research: Uncertainties are amplified at regional scales; nevertheless, CMIP model projections are extensively utilized for impact studies by researchers unfamiliar with these sources of uncertainty and structural limitations of CMIP projections. We invite contributions that use innovative approaches to address these challenges in impact studies with CMIP output.
In summary, this session aims to foster collaboration and dialogue among climate scientists and modelers to increase the efficient use of CMIP output and meet the pressing challenges of climate change.
1. Identification of processes and key entities with significant disparities across CMIP models: Quantifying sources of uncertainty across CMIP models, which may include i) internal variability, ii) process representations/model parameterization, iii) ESM architecture, and iv) external forcing.
2. Use of reduced complexity models and emulators: Exploring the uncertainty range with computationally fast model approaches, particularly the parts of the distribution not well represented by the CMIP ensembles.
3. Critical scientific priorities for future CMIP/Earth system model development: Recognizing and comprehending uncertainties and their underlying mechanisms are essential for guiding future model development and refining climate projections. We welcome contributions that focus on enhancing model performance and reducing uncertainties across disciplines for future CMIP iterations.
4. Opportunities, challenges, and constraints in using CMIP output for impact research: Uncertainties are amplified at regional scales; nevertheless, CMIP model projections are extensively utilized for impact studies by researchers unfamiliar with these sources of uncertainty and structural limitations of CMIP projections. We invite contributions that use innovative approaches to address these challenges in impact studies with CMIP output.
In summary, this session aims to foster collaboration and dialogue among climate scientists and modelers to increase the efficient use of CMIP output and meet the pressing challenges of climate change.