26-121 Numerical Weather Prediction Analyst

Colorado State University•Boulder, CO

23h•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 associate position designed to conduct collaborative research and development 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. The Cooperative Institute for Research in the Atmosphere 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. Position Summary: The individual in this position will lead the design and evaluation of output from real-time and retrospective, hypothesis-driven numerical weather and Earth system prediction model experiments. The outcomes of these experiments will be used to inform developments necessary to improve the forecast skill and physical fidelity of the Model for Prediction Across Scales (MPAS)-based numerical weather and Earth system prediction models developed by GSL, including regional forecast systems such as NOAA’s Rapid Refresh Forecast System and future global forecast systems. The individual in this position will work closely with model developers on designing appropriate experiments, interpreting results, and translating results into scientific feedback to inform model development priorities. This position will report to the Ensemble Prediction Scientist.

Requirements

A Ph.D. in Atmospheric Science or related field; or A M.S. in Atmospheric Science or related field and at least two years of relevant post-M.S. experience; or A B.S. in Atmospheric Science or related field and at least five years of relevant post-B.S. experience
At least two years of experience in numerical weather prediction testing, evaluation, and verification, including planning, coordinating, managing, and executing 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.
US citizens and lawful permanent residents with a physical USCIS “Green Card” are eligible.

Nice To Haves

Experience running and evaluating the output from numerical weather prediction models to test scientific hypotheses.
Knowledge of state-of-the-art regional and/or global numerical weather prediction models.
Knowledge of deterministic and/or ensemble forecast system verification techniques.
Knowledge of ensemble forecast system design and verification.
Knowledge of the availability and strengths/weaknesses of observations from in situ and/or remotely sensed platforms as it relates to numerical weather prediction model development and evaluation.

Responsibilities

In collaboration with model developers, designs, conducts, and evaluates hypothesis-driven experiments to quantify forecast errors in regional and global, deterministic and ensemble, physics-based and data-driven weather forecast systems and/or test and evaluate improvements proposed to reduce those errors.
Contributes to leading the planning, maintenance, and execution of real-time and retrospective regional and global deterministic and ensemble forecast systems.
Provides scientific feedback to inform current and future development activities.
Serves as a subject-matter expert on routine and field-campaign observations from in situ and remotely sensed platforms to inform model development and verification.
Contributes to formulating, executing, and tracking priorities for physics and model development for regional and global deterministic and ensemble forecast systems.
Prepares briefing materials and presentations for branch management, internal meetings, conferences, and workshops, and regularly publishes scientific content.
The individual in this position may eventually supervise up to two employees, as the project expands and funding is maintained.