26-118: Ensemble Prediction Researcher

Colorado State University•Boulder, CO

1d•Hybrid

About The Position

The Cooperative Institute for Research in the Atmosphere (CIRA) at Colorado State University (CSU) seeks to fill a full-time Research Scientist position designed to conduct collaborative research with the National Oceanic and Atmospheric Administration (NOAA) located at the Global Systems Laboratory (GSL) in Boulder, CO. The individual in this position will work in the NOAA/OAR/GSL Earth Prediction Advancement Division (EPAD) Physics Branch. CIRA at Colorado State University is a multi-million-dollar research organization located on CSU's Foothills Campus in Fort Collins, Colorado. CIRA is a cooperative institute that is also a research department within CSU's College of Engineering, in partnership with the Department of Atmospheric Science. Its vision is to conduct interdisciplinary research in the atmospheric sciences by entraining skills beyond the meteorological disciplines, exploiting advances in engineering and computer science, facilitating transitional activity between pure and applied research, leveraging both national and international resources and partnerships, and assisting the National Oceanic and Atmospheric Administration, CSU, the State of Colorado, and the Nation through the application of our research to areas of societal benefit. NOAA's Global Systems Laboratory is a federal science and research laboratory under NOAA’s Office of Oceanic and Atmospheric Research. GSL provides the National Weather Service (NWS) and the nation with environmental observation, prediction, computer, visualization, and information systems. These systems deliver data, forecasts, and predictions of weather, including severe weather events, within the next few minutes to weeks away. GSL is a leader in the applied research, directed development, and technology transfer of environmental data, models, products, and services that enhance environmental understanding with the outcome of supporting commerce, protecting life and property, and promoting a scientifically literate public. The individual in this position will contribute to the development of next-generation ensemble (or probabilistic) numerical weather prediction systems. They will contribute scientific understanding to inform how these systems are designed and how they can be leveraged to provide effective decision-support guidance to end users. Major duties will include contributing to the refinement of existing ensemble generation and evaluation methods; applying scientific understanding to help identify and implement innovations for improving probabilistic forecast skill and spread; and contributing to designing, conducting, and evaluating the outputs of hypothesis-driven ensemble numerical weather prediction experiments. The person in this role is expected to help contribute to the goal of developing high-resolution, regional and global, ensemble weather prediction systems that are skillful, reliable, physically realistic, and useful to a wide range of stakeholders. This position will report to the CIRA Associate Director.

Requirements

Bachelor’s Degree in Atmospheric Science or related field plus 10 years of relevant work experience, or Master’s Degree in Atmospheric Science or related field plus 5 years of relevant work experience, or PhD in Atmospheric Science plus 2 years of relevant work experience.
Bachelor’s Degree in Atmospheric Science or related field plus 5 years of relevant work experience, or Master’s Degree in Atmospheric Science or related field plus 2 years of relevant work experience, or a recent PhD in Atmospheric Science.
Experience with ensemble weather prediction systems, including knowledge of their strengths and weaknesses for balancing probabilistic skill with appropriate forecast dispersion.
At least two years of experience in developing, running, and evaluating numerical weather prediction model experiments.
At least two years of experience in Fortran and/or C++, Python, high-performance computing, and Linux computing environments.
Experience communicating scientific results, such as through conference presentations, seminars, technical reports, and/or publications.

Nice To Haves

Experience with designing, running, and/or evaluating the output from ensemble numerical weather prediction systems.
Understanding of methods for verifying ensemble/probabilistic weather prediction forecasts.
Understanding of state-of-the-art regional (particularly thunderstorm-resolving) and/or global numerical weather prediction models.
Familiarity with artificial intelligence applications for weather prediction, particularly those that can provide probabilistic forecast information.
Experience using and contributing to community modeling systems.
Experience with NOAA’s Unified Forecast System (UFS), the Weather Research and Forecasting (WRF) model, and/or the Model for Prediction Across Scales (MPAS).

Responsibilities

Apply scientific understanding to inform the design of skillful and reliable high-resolution ensemble weather prediction and decision-support systems.
Contribute to the refinement and evaluation of existing ensemble prediction methods.
Assist with developing and testing novel ensemble methods, including but not limited to artificial intelligence applications.
Contribute to designing, conducting, and evaluating hypothesis-driven experiments to test innovations for improving probabilistic forecast skill and generating appropriate dispersion.
Prepare briefing materials and presentations for branch management, internal meetings, conferences, and workshops, and regularly publish scientific content.
This position may supervise 1-3 employees.