CIRES/NOAA PSD Land Data Assimilation Scientist for Numerical Weather Prediction
NOAA is developing a next-generation, community-based, coupled prediction system for weather and short-term climate prediction (the Unified Forecast System or UFS). The Joint Effort for Data Assimilation Integration (JEDI) is the data assimilation framework for the UFS. The University of Colorado’s Cooperative Institute for Research in Environmental Sciences (CIRES) and the Physical Sciences Division (PSD) at the NOAA Earth System Research Lab in Boulder, Colorado, seeks a scientist to help update the snow Data Assimilation (DA) scheme in the UFS. We are seeking a Ph.D scientist, ideally with experience in modeling and/or DA of snow.
The successful applicant will work with scientists at NOAA/PSD to update the current offline snow DA methodology used in the UFS, and to merge the snow DA into JEDI. Additionally, the UFS land surface model is being updated to include a multi-layer snow model, and the snow DA will need to be adapted accordingly.
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/
For more information on the Physical Sciences Division, please visit https://www.esrl.noaa.gov/psd/
The scientist will work with NOAA and CIRES scientists at PSD to update the snow DA capability of NOAA’s operational global prediction system. Tasks will include:
- Updating the snow DA methodology, and merging it into JEDI
- Running experiments to test the impact of the updated snow DA on UFS forecast skill.
What You Should Know
This is a 2-year grant funded position.
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
- Experience working with global-scale models, remotely sensed data sets, and/or ensemble systems.
- Familiarity with modern object-oriented software development, Fortran, and running applications on high performance computing system.
- Experience with the modeling and/or DA of snow.
- A relevant PhD degree and one to five years of relevant post-graduate experience.
The University of Colorado offers excellent benefits, including medical, dental, retirement, paid time off, tuition benefit and ECO Pass. The University of Colorado Boulder is one of the largest employers in Boulder County and offers an inspiring higher education environment. Learn more about the University of Colorado Boulder.
To apply, please submit the following materials:
- Resume or CV
- Cover letter addressed to the Search Committee briefly describing your qualifications, professional goals, and specific interest in this position.
- List of 3 references: the names, professional titles, and contact information of those who are familiar with your qualifications and work history.
If you are selected as the finalist, we will contact you through email and request that you submit 1 name and email of a reference who will be asked to submit a letter of recommendation. This information will be kept confidential and viewable only by the search committee.
This position will remain open until filled.
Note: Application materials will not be accepted via email. For consideration, applications must be submitted through CU Boulder Jobs.