University of Colorado CIRES/GSD GNSS Research Associate in Boulder, Colorado
CIRES/GSD GNSS Research Associate
The Cooperative Institute for Research in Environmental Sciences (CIRES) at the University of Colorado Boulder seeks to
fill a Research Associate (RA) position. This position will be within the National Oceanic and Atmospheric
Administration (NOAA), Earth System Research Laboratory (ESRL), Global Systems Division (GSD) in Boulder, Colorado
(office will be in Boulder).
The Global Observing Systems Analysis (GOSA) Group from the NOAA/ESRL Global Systems Division (GSD) helps NOAA
management to cost-effectively identify and prioritize current and future observing system solutions to improve the
skill of NOAA's global weather prediction models.
The GOSA Group conducts Observing System Experiments (OSEs) and Observing System Simulation Experiments (OSSEs) to
improve the uses of current observations and to evaluate how new observations could improve our understanding of the
Furthermore, GOSA leads NOAA research on Radio Occultation (RO) observations as input to global and regional weather
forecast models. The Global Navigation Satellite Systems (GNSS) RO technology consists of placing satellites at lower
orbits that enable tracking of the GNSS signals. From a Low Earth Orbit (LEO) satellite standpoint, an occultation
occurs when the transmitting GNSS satellite sets or rises behind the Earth. During an occultation, the rays connecting
the GNSS and LEO satellites scan the atmosphere quasi-vertically, providing information on the thermodynamic state of
the atmosphere. RO soundings are assimilated at most operational numerical weather prediction centers and they are
ranked as one of the top contributors in improving global forecast skill. RO is minimally affected by clouds and
precipitation, provides equal accuracy over land than over oceans, and profiles are provided at a very higher vertical
resolution and thus, are capable of resolving smaller vertical structures. Finally, as a result of the unbiased nature
of RO measurements, assimilating these observations acts as an "anchor" to the model, preventing it from drifting
towards its climatology, and thus enhancing satellite radiance data assimilation. NOAA started assimilating RO
observations into its global data assimilation system from the US/Taiwan COSMIC mission in May 2007. At the present,
NOAA is using operational data from the following additional satellites: GRAS on MetOp-A/B, TerraSAR-X, and GRACE-A/B.
Retrievals from other missions are planned to be assimilated once the data become available in real-time and their
accuracy is fully evaluated.
The goal of this project is to continue improving the utilization of RO observations into NOAA's models. The candidate,
and under the supervision of the GOSA Chief, will be working on improving current assimilation algorithms to improve
weather forecast skill. This includes building more accurate forward operators, better use of the data in the lower
troposphere and mid- stratosphere, increasing impact of GNSS RO on moisture fields, optimizing quality control
procedures, updating observation error characteristics, and RO data-readiness and monitoring. Furthermore, the
candidate will be working on the evaluation of the impact of RO on the assimilation of radiance data and the
complementarity of the different satellite observing systems in global weather forecasting.
The incumbent is also expected to participate in research work related to other applications of the GNSS technology
(e.g. reflections), by exploring methodologies to use these products into weather models and evaluating their impact in
weather forecast skill through OSEs/OSSEs.
The successful candidate will be a member of the GOSA Group, located in Boulder, CO., and he/she is expected to work
with the rest of the GOSA Group and to collaborate with scientists at the NOAA Atlantic Oceanographic and
Meteorological Laboratory (AOML), the National Weather Service, and other NOAA institutions. He or she will also be
responsible for presenting findings at scientific meetings and publishing results in scientific journals.
A PhD degree in atmospheric sciences or related fields
Knowledge in theoretical and data assimilation methods
Knowledge in remote sensing
Knowledge in numerical weather prediction and meteorological analysis
Experience with Fortran programming, UNIX/LINUX systems, and statistical analysis and visualization packages
Ability to work in a team
Capability in oral and written communications
Special Instructions to Applicants:The University of Colorado Boulder conducts background checks on all final applicants being considered for employment, prior to the issuance of an offer letter. The University of Colorado Boulder is committed to providing a safe and productive learning, living and working community. To achieve this goal, we conduct background investigations for all final applicants being considered for employment. Background investigations include a criminal history record check, and an EPLS (Excluded Parties List System) check. The Immigration Reform and Control Act requires that verification of employment eligibility be documented for all new employees by the end of the third day of work.
Application Materials Required:Cover Letter, Resume/CV, Reference Letters (Not Confidential), Unofficial transcript(s)
Application Materials Instructions:Applicants must complete the Faculty/University Staff and EEO Data (application) form, and upload the following required documents: 1 - Cover Letter; 2 - Resume; 3 - The document uploaded for Proof of Degree can be a Transcript which shows the date the degree was conferred; Copy of Diploma; or official letter from the Registrar or the Dean of the School or College conferring the degree; and 4 - Letter of RecommendationThis position is eligible for medical, dental and life insurance, retirement benefits programs, and is eligible for monthly vacation and sick leave accruals.