Other team members:
Annie Bares University of Texas at Austin
Stephanie Zeller University of Texas at Austin
Scientific Focus of Data Sets: Earth systems science
Description of Data Sets:
The data used in this presentation is output from a climate model simulation using the Department of Energy’s Energy Exascale Earth System Model (E3SM). This E3SM configuration is focused on the ocean model component, which was run at a high-resolution of 10 kilometer grid cell widths and was driven by historical atmospheric conditions from 1948–2009, such as winds, runoff, precipitation, and air-to-sea heat fluxes. Our simulation produced typical output of the physical state of the ocean, but also included ocean biogeochemistry, such as nutrients, oxygen, carbonate chemistry, and phytoplankton concentrations. We simultaneously ran the climate model in its standard gridded mode (Eulerian mode) to produce grid cell averages globally as well as in a particle-tracking mode (Lagrangian mode) to capture the pathways of fluid parcels and particulate matter in the ocean. The combination of a high spatial resolution, ocean biogeochemistry, and the addition of the particle–tracking mode made the run very computationally expensive. We ran the simulation on Los Alamos National Lab’s supercomputer “Grizzly,” using 10,000 processor cores over the course of six months, corresponding to approximately 11 million core hours. As the simulation was executed by the project lead, we are authorized to share visualizations and results from it.
Scientific Potential of Presentation:
Our proposed presentation is a demonstration of recent work on Lagrangian methods for running and visualizing ocean climate model simulations. This work uses the Lagrangian perspective of ocean simulations, which follows virtual fluid parcels along their trajectories to better take into account ocean currents and other movement of particulate matter across the globe, such as phytoplankton and marine debris. Using high performance computing allowed us to compute both the standard Eulerian perspective (i.e., grid cell averages of Earth System variables) and the Lagrangian perspective simultaneously at model runtime to transform how scientists understand the connectivity between ocean basins and the circulation of waters from the surface to deep ocean. The presentation begins by explaining the Eulerian perspective, the traditional model of simulating and visualizing global climate models, which depends upon static calculations within individual grid cells. As this method does not adequately account for ocean flows, which are crucial to understanding the global climate system, we used the Lagrangian method, in which virtual floats were pushed by 3-dimensional ocean currents as we ran the climate simulation. As the visualizations in this presentation will demonstrate, the Lagrangian method, when applied as cutting edge simulations are run, offers much more dynamic, accurate, and precise climate data visualizations that allow scientists to track pathways of carbon emissions and particulate ocean matter, such as plankton or oil particles after a spill.
The presentation will include original movies, original still image visualizations, and original scientific illustrations accompanied by captions and narration to demonstrate the advantages of climate visualizations created using the Lagrangian method. For the purposes of the contest submission, we have included three movies, a storyboard with descriptions of the other planned visuals, and the narration that will be delivered. The first movie is of a global climate simulation using the traditional Eulerian view to provide a point of reference and comparison and demonstration of the limits of grid-based climate modeling. The second is a movie of a climate model simulation of the Southern Ocean created using the Lagrangian perspective, which shows the pathways of dissolved inorganic carbon from 300—2000 meters within the ocean interior. This showcases how the vast amounts of carbon stored in the ocean circulates. The third is a visualization created using the Lagrangian perspective that shows particles moving over time into the Great Pacific Garbage Patch, an unexpected finding in our research and demonstration of how this method can enable scientists to consider a wider scope of interconnected phenomenon when studying climate simulations.
Brady, Riley
Description
Current Insitute of Study/Organization: University of Colorado Boulder
Currently Pursuing: Doctorate
Winner Status
- Runner-Up