[ES_JOBS_NET] Post-Doctorate Position – Atmospheric Data Assimilation, PNNL
christin at ucar.edu
Wed Jul 20 06:35:42 MDT 2016
Post-Doctorate Position – Atmospheric Data Assimilation
The Atmospheric Sciences and Global Change Division
(http://www.pnnl.gov/atmospheric) at Pacific Northwest National
Laboratory (PNNL) is seeking a postdoctoral scientist to work on data
assimilation for cloud-resolving (grid spacing ~1 km) and Large-Eddy
Simulation (LES, grid spacing ~10’s of m) spatial scales. The
post-doctoral fellow will work with a project team (Drs. Jerome Fast,
Robert Houze, Samson Hagos, Zhe Feng, Larry Berg, William Gustfson, and
Heng Xiao) to create more realistic initial and boundary conditions for
simulations of shallow clouds and the transition from shallow to deep
convection. This will involve merging extensive in situ (surface
monitoring, radiosondes, aircraft) and remote sensing (lidar, radar,
satellite) measurements with model predictions to create high spatial
and temporal resolution analyses.Development will be based on existing
data assimilation packages developed for the Weather Research and
Forecasting (WRF) model. In addition, the fellow will be expected to
contribute to challenging modeling studies designed to 1) better
understand the processes contributing to the initiation, evolution, and
organization of convective clouds, 2) improve physics parameterizations,
and 3) optimize meteorological sampling locations.
The candidate should have demonstrated expertise in data assimilation.An
understanding of the processes represented by cloud microphysics and
convective parameterizations used by atmospheric models is desirable.
Proficiency with FORTRAN and coding experience in atmospheric modeling
are required, and the ability to modify, compile and run WRF is
essential. Familiarity with U.S. Department of Energy Atmospheric
Radiation Measurement (ARM) data products is useful, but not required.
Teamwork and strong communication skills for engaging with project teams
at PNNL and the broader climate research community are also important.
The successful candidate will join the team of PNNL researchers that are
expanding the knowledge of fundamental atmospheric processes, developing
state-of-the-art modeling capabilities, and improving understanding of
how human and natural systems interact. Working across disciplines, we
integrate theory, measurements, and modeling at molecular to global scales.
Use the following link,
for the full position description with specific requirements and details
on how to submit your application. Or visit http://jobs.pnnl.gov and
search for Job ID 305637 under the current job openings.
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