The ocean significantly mitigates climate change by absorbing fossil fuel carbon from the atmosphere. Cumulatively since the preindustrial times, the ocean has absorbed 40% of emissions. To understand past changes, diagnose ongoing changes, and to predict the future behavior of the ocean carbon sink, we must understand its spatial and temporal variability. However, the ocean is poorly sampled and so we cannot do this from direct measurements.

In the McKinley group, we have developed several data science techniques to reconstruct ocean carbon data based on association to satellite-based full-field driver data. We have also developed the Large Ensemble Testbed, a compilation of Earth System simulations designed for the evaluation of ocean carbon reconstructions (Gloege et al., in review). In this Spring 2020 project, the DSI Scholar will apply the Large Ensemble Testbed to compare the strengths and weaknesses of several ocean carbon reconstruction approaches.

For this project, the data will be 100 realizations of simulated surface ocean pCO2, subsampled as the real data (SOCAT, www.socat.info), as well as simulated sea surface temperature, chlorophyll, salinity, and mixed layer depth for 1982-2016. All dataset are already in use, thus data preparation will not be a significant task.

One selected candidate will receive a stipend via the DSI Scholars program. Amount is subject to available funding.

Faculty Advisor

  • Professor: Galen McKinley
  • Department/School: Earth and Environmental Science
  • Location: Lamont Doherty Earth Observatory / Comer 429
  • The McKinley Ocean Carbon Research Group studies how ocean physical and biogeochemical processes impact large-scale carbon cycling and primary productivity. These studies encompass fluid dynamics, climate processes, biogeochemistry and ecology. Our primary research tools are numerical models and large historical datasets.

Project Timeline

  • Earliest starting date: 3/1/2020
  • End date: 5/15/2020
  • Number of hours per week of research expected during Spring 2020: ~12
  • Number of hours per week of research expected during Summer 2020: ~0

Candidate requirements

  • Skill sets: In addition to the data science skills and python, students should have an interest in the oceans and climate. It would be great if students have had some introductory earth / ocean science classes in the past, but this is not required.
  • Student eligibility: freshman, sophomore, junior, senior, master’s
  • International students on F1 or J1 visa: eligible