Postdoctoral Research Associate position on development of multi-scale and near-surface data assimilation cycling systems in a global-nested weather prediction model
The Atmospheric and Oceanic Sciences Program at Princeton University, in cooperation with NOAA’s Geophysical Fluid Dynamics Laboratory (GFDL), seeks a postdoctoral or more senior researcher to join the NOAA Research Global-Nest project. This multi-laboratory project aims to develop ultra-high resolution atmospheric prediction models for better prediction, understanding, and projection of extreme weather events. An important component of this project is designing a multiscale data assimilation (DA) system using the GFDL System for High-resolution prediction on Earth-to-Local Domains (SHiELD; www.gfdl.noaa.gov/shield), an FV3-based global weather model. This DA system aims to improve medium-range and subseasonal predictions of weather events and specifically extreme weather and to provide useful tools for understanding the predictability of these events.
The successful applicant will work with members of the GFDL FV3 Team to further the development of SHiELD-DA, and in particular to develop new assimilation algorithms and observation operators; perform ingest and quality control of remotely-sensed and in-situ data sets, especially satellites and station observations; improve model and observation error estimation; incorporate updates from other SHiELD and DA system developers; and evaluate the performance of the DA cycling system and initialized forecasts. We are especially interested in multiscale data assimilation techniques and the assimilation of near-surface (winds, screen-level temperature and humidity) and soil conditions (moisture, temperature) for new two-way global-to-regional nested configurations of SHiELD designed to reach convective scales (< 5 km) over the contiguous United States and beyond. The project will cooperate closely with other DA developers at US operational centers and other laboratory collaborators, including at NCEP and through the Unified Forecast System (UFS) development activities.
All applicants should have a strong background in using DA systems (such as GSI or JEDI) and a strong understanding of the data sets and algorithms used in DA systems. Selected applicants will be expected to work in a collaborative environment, adhere to best coding and data handling practices, write technical notes and peer-reviewed publications on their work, and for their work to be prepared for use by coworkers and external collaborators after publication.
This is a one year position with potential for an additional year based on candidate performance and continued funding. Candidates should have a doctoral degree in atmospheric science or a related field. Applicants are asked to submit a CV, publication list, a one-to-two page statement of research interests, and contact information for 3 references. Review of applications will begin as soon as they are received and continue until the position is filled. 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/27662. This position is subject to Princeton University's background check policy.
For more information about the research project and application process, please contact Mingjing Tong at email@example.com or Lucas Harris at firstname.lastname@example.org. The position is subject to the 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.