The Atmospheric and Oceanic Sciences Program at Princeton University, in collaboration with NOAA's Geophysical Fluid Dynamics Laboratory (GFDL), NOAA’s Center for Operational Oceanographic Products and Services (CO-OPS), and Rutgers University’s Earth System Science and Policy Lab seeks a postdoctoral or more senior researcher to conduct research on decadal to centennial scale sea level rise. The overall goal of the project is to contextualize projections of sea level rise from the latest generation of coupled global climate models developed at NOAA-GFDL against previous generation simulations and assess opportunities for model improvements to narrow the uncertainty of sea level projections.
The research at Princeton University/GFDL will focus on how differences in ocean model resolution and formulation contribute to overall uncertainty in future sea level projections. Existing US-based sea level rise scenarios used in previous National Climate Assessments and by the public for assessing coastal inundation risk are informed by a probabilistic framework that combines output from coupled atmosphere-ocean general circulation models along with the uncertainty associated with other Earth system processes that contribute to sea level rise. In order to increase the utility of these scenarios, it is important to understand how the current generation ocean models simulate patterns of dynamical sea level rise and ocean heat uptake relative to previous generations and how these differences translate to overall uncertainty in the probabilistic framework. The recent hierarchy of models developed by the Geophysical Fluid Dynamics Laboratory (NOAA/OAR) provides an opportunity to explore these questions in more detail.
The research at Princeton University/GFDL will focus on connecting a probabilistic sea level projection framework directly to GFDL’s ocean model output in order to explore how model differences translate into sea level projection uncertainty. Potential areas of exploration include the role of different model horizontal resolutions, differences among climate forcing scenarios, ocean heat uptake and exchange between the upper ocean and deep ocean, and global climate sensitivity to greenhouse gas forcing. The research will require analysis and interpretation of model output, management of large datasets, and the development of mean-state and process-level model diagnostics of sea level rise. The postdoc will be expected to collaborate with researchers at Princeton, GFDL, CO-OPS, and Rutgers.
In addition to a quantitative background, the selected candidates will ideally have one or more of the following attributes: a) a strong background in physical oceanography, sea level rise dynamics, ocean heat uptake, or a closely related field, b) demonstrated experience in conducting analysis of ocean-only and coupled climate model output, and c) experience in ocean model development or conducting model simulations. Additional experience in statistical methods is also preferred.
A Ph.D. is required, preferably in Oceanography or a closely related field. The initial appointment is for one year with the possibility of a second-year renewal subject to satisfactory performance and available funding.
Complete applications, including a cover letter, CV, publication list, research statement (no more than 2 pages incl. references), and 3 letters of recommendation should be submitted by August 15, 2021, 11:59 pm EST for full consideration. Princeton is interested in candidates who, through their research, will contribute to the diversity and excellence of the academic community.
Applicants should apply online at https://www.princeton.edu/acad-positions/position/21321 . For additional information about the project contact Dr. John Krasting (John.Krasting@noaa.gov).
This position is subject to Princeton University's background check policy.
Princeton University is an equal opportunity/affirmative action employer and all qualified applicants will receive consideration for employment without regard to age, race, color, religion, sex, sexual orientation, gender identity or expression, national origin, disability status, protected veteran status, or any other characteristic protected by law.