CIRES/GSD Mesoscale Numerical Weather Prediction and Data Assimilation Professional Research Assist

1 day left

Location
Boulder, Colorado
Posted
May 21, 2019
Closes
Jun 20, 2019
Ref
Internal #18037
Education Level
Masters
Job Type
Full-time
Relocation Cost
Negotiable
Sector Type
Government

Job Summary

The Cooperative Institute for Research in Environmental Sciences (CIRES) at the University of Colorado is looking to fill two Research Scientist positions in mesoscale data assimilation and numerical weather prediction for its collaborative research as a Cooperative Institute with the National Oceanic and Atmospheric Administration (NOAA) Office of Oceanic and Atmospheric Research (OAR) Global Systems Division (GSD). The incumbent will work within GSD’s Assimilation Development Branch (ADB).

The Global Systems Division (GSD) is designing, developing and testing new convection allowing models (CAM) to improve weather prediction. The goal is to improve prediction of severe weather including hurricanes, tornadoes, thunderstorms, flooding, and other weather that can have enormous impact on transportation, commerce, energy, and other sectors of the U.S. economy.  GSD is collaborating with the National Center for Environmental Prediction (NCEP) of the National Weather Service (NWS) as well as other NOAA laboratories and national research institutes on the next generation Unified Forecast System (UFS). Key NOAA strategic mission goals are designed to reduce loss of life, injury, and economic costs.

The two research scientists will support the UFS through the development of the Finite Volume 3 (FV3) model by developing capabilities for meso- and storm-scale analysis and forecast applications. The FV3 will replace the current operational hourly assimilating regional Rapid Refresh (RAP) and High-Resolution Rapid Refresh (HRRR).  The scientists will contribute to community development the SAR (and global) FV3, to meet the needs of rapidly updating data assimilation cycles for an accurate deterministic and ensemble CAM analysis and forecast.

Who We Are:

At CIRES, the Cooperative Institute for Research in Environmental Sciences, more than 800 environmental scientists work to understand the dynamic Earth system, including people’s relationship with the planet. CIRES is a partnership of NOAA and the University of Colorado Boulder, and our areas of expertise include weather and climate, changes at the Earth’s poles, air quality and atmospheric chemistry, water resources, and solid Earth sciences. Our vision is to be instrumental in ensuring a sustainable future environment by advancing scientific and societal understanding of the Earth system.

For more information on CIRES, please visit https://cires.colorado.edu/

The Global Systems Division (GSD) of the Earth System Research Laboratory (ESRL) conducts world-class applied research and directed development resulting in technology transfer of environmental data, models, products, and services that enhance environmental understanding with the outcome of supporting commerce, supporting NWS in protecting life and property, and promoting a scientifically literate public.

For more information on the Global Systems Divison, please visit https://www.esrl.noaa.gov/gsd/

What your Key Responsibilities Will be:

  • Implement and test physics modules into the FV3 model via a common community framework.
  • Implement and test mesoscale data assimilation components in the FV3 cycled model system.
  • Evaluate the performance of physically-based stochastic parameterizations of model uncertainty.
  • Test strategies for filtering noise caused by more frequent state updates (4DIAU, digital filters).
  • Evaluate impacts of high-temporal frequency observations (e.g., geostationary all-sky radiances atmospheric motion vectors, tropical cyclone observations) on model forecasts.
  • Maintain real-time and retrospective SAR FV3 parallel systems with verification and downstream evaluation.
  • Compare output of the FV3 against current operational models.
  • While a candidate will need to be self-directed, they will work closely with other members of GSD’s modeling and data assimilation teams and other outside collaborators.

What You Should know:

CIRES commits to inclusive excellence by advancing equity and diversity in all that we do. We are an Affirmative Action/Equal Opportunity employer, and particularly encourage applications from members of historically underrepresented racial/ethnic groups, women, individuals with disabilities, veterans, LGBTQ community members, and others who demonstrate the ability to help us achieve our vision of a diverse and inclusive community.

This position will be rostered in CIRES at the University of Colorado Boulder, but will be physically situated in the David Skaggs Research Center, 325 Broadway, Boulder, CO 80305. If you are the selected finalist you will be required to pass a federal laboratory background clearance for site access.

What We Can Offer:

We can offer a competitive salary, commensurate with experience, along with a generous benefits package.

What We Require:

  • M.S. or Ph.D. in Meteorology/Physics/Computer Science/Applied Mathematics or STEM discipline with experience in numerical weather prediction and/or data assimilation (if the selected finalist has a PhD, the job title will be Research Associate instead of Professional Research Assistant).
  • Demonstrated experience (1 to 2 years of professional experience or experience obtained through academic training) with modifying modeling and/or assimilation system codes such as FV3, WRF-ARW, HWRF, MPAS, NEPTUNE, GSI, DART, WRFDA, JEDI. 
  • Demonstrated experience (1 to 2 years of professional experience or experience obtained through academic training) running scientific software on large-scale supercomputer environments (e.g., NOAA’s HPC platforms such as WCOSS, Jet, Theia, and Gaea).
  • Ability to work and communicate effectively (verbal and written) within a team environment and to facilitate communication across multiple teams and organizational units.

What You Will Need:

  • Knowledge of Fortran/Fortran 90.
  • Proficiency using open source scripting software (e.g., Python, NCL, CSH).
  • Knowledge of software management tools (e.g., Make, Git).
  • Knowledge of mesoscale meteorology

What We'd Like You to Have:

  • Knowledge of numerical weather prediction and/or ensemble data assimilation theory and techniques.
  • Knowledge of atmospheric physical processes.
  • Ability to prepare technical analyses and reports for senior level management. 
  • Strong desire to improve operational NWP capabilities and support research community.

The University of Colorado is an Equal Opportunity Affirmative Action Employer

If you wish to Apply, please use this link and complete your full application through our portal:

https://jobs.colorado.edu/jobs/JobDetail/?jobId=18037

 

 

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