Postdoc Fellowship in Atmospheric Science

University of Michigan, Cooperative Institute for Great Lakes Research (CIGLR)
Ann Arbor, MI
Job Category
Post Doctoral Appointments
Last Date to Apply
The Cooperative Institute for Great Lakes Research (CIGLR) is seeking outstanding candidates for a postdoctoral scholar position in atmospheric science. In collaboration with the National Oceanic and Atmospheric Administration (NOAA) Great Lakes Environmental Research Laboratory (GLERL) and School for Environment and Sustainability (SEAS), the successful candidate will lead research in atmospheric science, regional climate variability, understanding and predicting hydrometeorology within regional domains. The postdoctoral fellow will be part of a large interdisciplinary team at GLERL, CIGLR, and SEAS that is developing the next generation prediction system for determining the mean and extreme water levels in the Great Lakes. This new system will provide the foundation for defining risk of coastal inundation impacts across subseasonal to annual time scales for the Laurentian Great Lakes. Specifically, the postdoctoral fellow will evaluate existing hydrometeorological datasets as inputs to the next generation water level prediction system, characterize hydrometeorological variability across space-time scales, and develop modeling approaches to advance hydrometeorological prediction for a target domain using statistical, process-oriented, and hybrid methods. Work will be conducted as part of an interdisciplinary team bringing together expertise in meteorology and climate, hydrology, water management, and stakeholder engagement.
Required Qualifications PhD in meteorology, atmospheric science, climatology, or similar field (e.g., hydrometeorology and hydroclimatology). Demonstrated ability to work with gridded atmospheric model outputs using statistical, data-driven analysis techniques and/or process-oriented analyses that support physical relations indicated by statistical analyses. Example datasets include the data from models participating in the North American Multi-Model Ensemble (NMME), the Subseasonal Experiment (SubX), and the Coupled Model Intercomparison Project (CMIP). Strong publication record in the relevant field, including at least one lead-author publication. Strong communication skills and demonstrated ability to work independently in collaboration with an interdisciplinary team. Proficiency with handling various data formats, such as NetCDF, GRIB2, ASCII, and shapefiles. This includes visualization, geospatial data analyses, and dealing with map projections using existing libraries for programming languages such as Python, R, and Matlab. Proficiency with working on a supercomputer or a cluster computing environment. This includes shell scripting, batch job submissions, and data transfer. Desired Qualifications Experience with model intercomparison across different types of modeling (e.g., lumped, conceptual models, physics-based models, statistical models). Experience performing analyses targeted to subseasonal, seasonal, and/or annual time scales. Understanding of global circulations, teleconnection patterns, and their impacts on regional climate (e.g., precipitation patterns). Familiarity with various parameterization schemes utilized in atmospheric modeling. Experience using Great Lakes regional hydrological/climate datasets (e.g., Regional Deterministic Reanalysis System, the Canadian Precipitation Analysis system).
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