Open-Ocean Deep Convection Events Across CMIP6 Models
Open-ocean deep convection events are an important part of the general ocean circulation. For example, they play a key role in the dynamics of the thermohaline and meridional overturning circulations (Marshall & Schott, 1999), and in some locations are affecting the local nutrient budget and phytoplankton blooms (Severin et al., 2017). In the Southern Ocean (SO), open-ocean convection is related to the Antarctic Bottom Waters formation rate - which affects the ocean heat and carbon storages (De Lavergne et al., 2014). Moreover, it was shown that SO convection periods are linked with the warming of the Southern Hemisphere through changes in the atmosphere-ocean energy balance (Cabréet al., 2017). Thus, any progress in tracking and understanding global deep convection events can promote our understanding of the climate system.
However, there are no specific parameters for convection inside the models, and even when choosing a specific convection index - CMIP5 models showed large differences between them: (Reintges, Martin, Latif, & Park, 2017) and supplementary of (De Lavergne et al., 2014). Therefore, tracking deep convection events is not an easy task, and developing a systematic approach for detecting and analyzing them could be very beneficial for the ocean sciences community.
Frequency and duration of simulated Southern Ocean convective events under pre-industrial conditions. Distribution of the 25 convecting CMIP5 models (De Lavergne et al., 2014)
In this project, the main goal is to compare open-ocean deep convection events between the different CMIP6 models. The proposed way to do this is by:
Designing universal and location-specific convection indices (e.g. we might need a specific index for the Weddell Sea and a different one for the Labrador Sea)
Constructing metrics for comparing various indices across models
Writing comprehensive Jupyter Notebooks with the indices definitions and the code for evaluating them, for future use by the oceanic research community
Comparing observations to findings from models to check the indices (in the future)
Anticipated Data Needs
Annual and monthly 3D oceanic parameters (temperature, salinity, and velocities).
Anticipated Software Tools
Standard Python libraries such as: pandas, xarray, dask, etc.
Depending on how the project progresses, there might be a need for using the signal processing toolbox in MATLAB as well.
People who are inspired by the physics of the ocean and its contribution to climate
Cabré, A., Marinov, I., & Gnanadesikan, A. (2017). Global atmospheric teleconnections and multidecadal climate oscillations driven by Southern Ocean convection. Journal of Climate.
De Lavergne, C., Palter, J. B., Galbraith, E. D., Bernardello, R., & Marinov, I. (2014). Cessation of deep convection in the open Southern Ocean under anthropogenic climate change. Nature Climate Change.
Marshall, J., & Schott, F. (1999). Open-ocean convection: Observations, theory, and models. Reviews of Geophysics.
Reintges, A., Martin, T., Latif, M., & Park, W. (2017). Physical controls of Southern Ocean deep-convection variability in CMIP5 models and the Kiel Climate Model. Geophysical Research Letters.
Severin, T., Kessouri, F., Rembauville, M., Sánchez-Pérez, E. D., Oriol, L., Caparros, J., … Conan, P. (2017). Open-ocean convection process: A driver of the winter nutrient supply and the spring phytoplankton distribution in the Northwestern Mediterranean Sea. Journal of Geophysical Research: Oceans.