Back to opportunities | Category Index
These are the intended use-case/justification for one or multiple variable groups. Opportunities are linked to relevant experiment groups. Identifying opportunities helps to provide a structure to map variables against requirements. Each opportunity description will convey why this combination of variables and experiments is important and how they contribute to impact.
| Attribute | Value |
|---|---|
| description | The opportunity includes the most relevant variables and experiments to address the main goals of DynVarMIP, which focuses on the dynamics and variability of the stratosphere-troposphere system. In this opportunity we define requirements for diagnosing the atmospheric circulation and variability across temporal scales and for evaluating the momentum and heat budgets, both resolved and unresolved in the models. These analyses of dynamical processes are crucial for identifying the sources of circulation biases in climate models and advance understanding of the atmospheric response to both natural variability and human-induced changes. These biases in atmospheric dynamics significantly contribute to uncertainties in regional climate forecasts, precipitation trends, and the occurrence of extreme events. |
| expected_impacts | The opportunity mainly follows the CMIP6 DynVarMIP data request published in Gerber and Manzini (2016), which has already made possible the assessment of stratospheric mean climate, variability, and change, as well as of the stratosphere-troposphere dynamical coupling in climate models. Also, the original data request proved extremely helpful in detecting the intermodel differences in dynamics and transport in the free atmosphere and identifying the underlying physical processes causing this spread. The outcome includes high impact studies on Sudden Stratospheric Warmings, stratospheric polar vortex, Brewer-Dobson circulation, stratosphere-troposphere coupling and tropospheric large-scale circulation, listed in https://dynvarmip.github.io/publications/. Key questions that require the variables and experiments defined in this opportunity include: - In what ways do resolved and parameterized dynamical processes lead to persistent biases in climate models, particularly in the mean state and atmospheric variability, including the position, intensity, and frequency of blocking events, storm tracks, and the stratospheric polar vortex? - How does the stratosphere influence climate variability on a range of time scales? - How do atmospheric dynamics shape the climate’s response to human-induced changes, such as global warming and ozone depletion, and what role do they play in adding uncertainty to future climate projections? - What is the significance of stratosphere-troposphere interactions in driving extreme weather and climate events? |
| justification_of_resources | The required variables and experiments are crucial for assessing dynamical processes and their future changes, one of the key uncertainties in future climate projections (Shepherd et al. Climatic Change, 2018). Most of the required variables are either included in other groups or are zonal mean fields, and thus imply a small computational and storage burden. The reason to include the zonal mean of basic variables such as wind and temperature is to include more vertical levels, crucial for stratosphere-troposphere coupling studies. Transformed Eulerian Mean variables are central and widely used in the analyses of momentum budget in the free atmosphere. The requested tendencies from unresolved processes are necessary for closing the momentum and energy budgets and proved helpful for attributing the causes of intermodel differences and biases. |
| lead_theme | Atmosphere |
| minimum_ensemble_size | 3 |
| name | Atmospheric dynamics and variability |
| opportunity_id | 9 |
| data_request_themes | Atmosphere |
| experiment_groups | dynvar |
| mips | TIPMIP, PMIP, DAMIP |
| time_subsets | 80ac3156-a698-11ef-914a-613c0433d878 |
| variable_groups | dynvar_advanced, dynvar_basic |