Background:
The Assimilation and Modeling Branch within ESRL/GSD develops high resolution operational numerical weather prediction models using the latest hourly observations to provide the most accurate analyses and very short-range forecasts over the US. The Rapid Refresh (RR)) assimilates all available observations, including profiler, aircraft, surface, rawinsonde, VAD winds, GOES-based precipitable water and atmospheric motion vectors (cloud-drift winds), GPS-precipitable water, radar reflectivity, GOES-based cloud retrievals, and METAR cloud observations. Satellite radiances are also assimilated in the Rapid Refresh through application of the Gridpoint Statistical Interpolation (GSI) data assimilation package. With the emphasis on hourly updated short-term forecasts for improved guidance for aviation/transportation, severe weather, hydrology, and energy applications, improved assimilation of satellite cloud data, as one component of satellite data assimilation for the RR/HRRR, is critical to improving model hydrometeor/cloud forecasts. In particular, the assimilation of GOES-R planned-derived cloud properties and near-storm environment is of critical importance.
Responsibilities:
The individual in this position will be a member of the GSD/Assimilation and Modeling Branch Rapid Refresh development team, which develops and test improved methods for the assimilation of satellite data to increase the accuracy of mesoscale model forecasts. He/She will be responsible for participation in the development team’s goals including:
* Development and testing of assimilation of hyperspectral sounding data from AIRS/IASI (LEO precursor to GEO Advanced IR Sounder) and GOES-derived convective initiation fields into Rapid Refresh for impact on forecasts of severe weather and convective weather impacts on aviation operations.
* Cloud retrievals from satellite sensors such as MODIS (GOES-R ABI proxy), AIRS and IASI;
* Temperature and/or moisture profile retrievals from AIRS and/or IASI;
* Development and testing of satellite radiance and data assimilation into hourly updating of Rapid Refresh using Gridpoint Statistical Interpolation (GSI).
* Determination of forecast impact using the 3-km High-Resolution Rapid Refresh (HRRR) being run to provide storm-resolving high-frequency updated guidance for convection.
* Publication of results in peer-reviewed literature and presentation at national / international conferences.
Required Qualifications:
* M.S. degree in Atmospheric Sciences, Meteorology, or closely related field, including training and research in:
-- variational data assimilation and adjoint sensitivity analysis
-- use of satellite radiance data from hyperspectral sensors such as AIRS
-- numerical weather prediction using models such as WRF or MM5
* Expertise with radiative transfer models (such as CRTM or SARTA) used with satellite radiance data
* Strong knowledge and skills in tangent linear model and adjoint model development and coding
* Expertise with variational analysis of AIRS radiance data including channel selection methods
* Ability to work effectively in a team environment
Apply electronically by sending a resume, cover letter, and the names of three references to the attention of HRS Manager at the following email address: cira_hr@mail.colostate.edu.
Please put your name in the subject line of the email and reference position 12-132.
Colorado State University does not discriminate on the basis of race, age, color, religion, national origin or ancestry, sex, gender, disability, veteran status, genetic information, sexual orientation, or gender identity or expression. Colorado State University is an equal opportunity/equal access/affirmative action employer fully committed to achieving a diverse workforce and complies with all Federal and Colorado State laws, regulations, and executive orders regarding non-discrimination and affirmative action. The Office of Equal Opportunity is located in 101 Student Services.
