CIRES / NOAA Chemical Sciences Laboratory, Research Scientist in Atmospheric Modeling and Data Analysis

Job Summary

The Cooperative Institute for Research in Environmental Sciences (CIRES) at the University of Colorado seeks a Research Scientist to join the Stratospheric Modeling and Analysis (SMA) Program of the National Oceanic and Atmospheric Administration's Chemical Sciences Laboratory (CSL) in Boulder, Colorado. Our group uses a variety of models and observations to study the complex relationships between stratospheric composition, chemistry, dynamics, and radiation, and how these processes affect weather and air quality. If hired, you will work closely with a team of federal and CIRES scientists to implement improvements to an in-house satellite stratospheric composition dataset and use it to support new chemical forecast development/validation efforts and other scientific analyses of coupled stratospheric processes. This project will involve work with large satellite and model data sets, chemistry-climate modeling in a supercomputing environment, and likely investigation and implementation of machine learning software for scientific applications. We seek a person with experience and interest in global-scale modeling and data analysis. A PhD degree is required, preferably in atmospheric science. The ideal candidate would have experience with satellite data analysis, statistics, atmospheric chemistry/radiation/dynamics, numerical modeling, computer programming, and machine learning. While few candidates will possess every desirable skill, we prioritize applicants who demonstrate a capacity to rapidly acquire and utilize new expertise, an eagerness to advance scientific understanding using simulations and observations, a willingness to work both independently and collaboratively, and a strong ability to communicate results in both written and oral form. This job will be in the CIRES Research Scientist career track.

What Your Key Responsibilities Will Be

• Participate/lead in UFS-chem validation/development efforts, particularly with relation to stratospheric aerosols, ozone and water vapor, including: (40%)
• Evaluation of stratospheric ozone/water vapor/aerosol biases in comparison to observations (e.g. SWOOSH, SAGE III/ISS, OMPS), including episodic events (e.g., volcanic eruptions)
• Targeted UFS-chem experiments to test potential improvements with respect to stratospheric composition, and process studies to understand whether improved stratospheric composition and/or dynamics improve forecasts
• Develop and implement improvements to the SWOOSH multi-satellite water vapor and ozone data record, with a specific focus on SAGE III/ISS data and ensuring reliability of the long-term record. (55-60%)
• Evaluate new and updated satellite data sets for inclusion into SWOOSH,
• Improve data screening, data homogenization, and uncertainty characterization.
• Use SWOOSH, SAGE III/ISS, and complementary data sets for improved quantification and process level understanding of decadal variability and trends in stratospheric composition and circulation.
• Performs other relevant duties as necessary (Not to exceed 5%)