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<dt id="dspJobTxtDescDiv" class="cssDspJobHead"><b><a class="moz-txt-link-freetext" href="http://tinyurl.com/o7go6hw">http://tinyurl.com/o7go6hw</a></b></dt>
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<p><strong>PLEASE NOTE</strong>: This is a full time position.
Initial consideration will be given to applications received
prior to 4:00 p.m. on Friday, June 26th, 2015. Thereafter,
applications will be reviewed on an as-needed basis.</p>
<p> </p>
<p>NCAR –Research Applications Laboratory (RAL) - National
Security Applications Program (NSAP)</p>
<p> </p>
<p>Partial Relocation costs paid per UCAR’s relocation policy.</p>
<p> </p>
<p>If necessary, UCAR/NCAR will sponsor a work visa to fill this
position.</p>
<p><strong> </strong></p>
<p><strong>BASIC JOB FUNCTION</strong>: This Project Scientist I
position specializes in numerical weather and air quality
prediction and data assimilation, with variational,
ensemble-based, and hybrid approaches. The candidate will work
on a variety of projects in a team-oriented environment,
spanning modeling applications from meso to micro and urban
scales, air pollution, and transport and diffusion
simulations.</p>
<p> </p>
<p>The first two years of the project to which the candidate
will contribute are funded by the National Aeronautics and
Space Administration (NASA) to improve the accuracy of the
National Oceanic and Atmospheric Administration (NOAA) /
National Centers for Environmental Prediction (NCEP)
short-term predictions of ground-level ozone and particulate
matter less than 2.5 m in diameter (PM2.5) and to provide
reliable quantification of their uncertainty, by exploiting
NASA Earth Science Data with chemical data assimilation and
analog-based approaches. To improve the initialization of the
NOAA/NCEP operational air quality system, which is based on
the Community Multiscale Air Quality (CMAQ) model, the
successful candidate will use the Community Gridpoint
Statistical Interpolation (GSI) system to assimilate surface
and satellite data. These data sets include retrievals of
aerosol optical depth (AOD) from the NASA Aqua/Terra Moderate
Resolution Imaging Spectroradiometer (MODIS) satellite
instruments and possibly retrieval of carbon monoxide from the
NASA/Terra Measurements Of Pollution In The Troposphere
(MOPITT) and the EUMETSAT/MetOp Infrared Atmospheric Sounding
Interferometer (IASI). Surface observations of PM2.5 (and
possibly of ground-level ozone) from the AIRNow network, the
Interagency Monitoring of Protected Visual Environments
(IMPROVE) stations, and the Clean Air Status and Trends
Network (CASTNET) will also be assimilated.</p>
<p> </p>
<p><strong>DUTIES INCLUDE</strong>:</p>
<p> </p>
<ul>
<li>Coupling of the CMAQ and GSI system for the assimilation
of AOD satellite retrievals, surface observations of PM2.5,
and possibly CO retrievals and ground-level O3 measurements.
This will include the development of forward operators for
the observation platforms for which are not available, the
extension of the analysis control variable list that defines
which model fields get updated, new data readers,
observation quality control procedures, and bias correction
schemes and error specification within the GSI system from
NCEP Central Operation (NCO).</li>
<li>Building of the horizontal and vertical auto-covariances,
as well as cross-covariances via statistical processing of a
dataset of CMAQ forecasts, to train the stationary model of
background error covariances. Testing, refinement, and
further improvement of the chemical data assimilation system
based on GSI/CMAQ.</li>
<li>Contributing to the transition to operation of the new
chemical data assimilation capability to NOAA/NCEP
operations, in collaboration with NOAA Air Resource
Laboratory (ARL) team members, assuring the code compliance
with NCO protocol and computational environment.</li>
<li>Communicate research results through publication in
peer-reviewed journals, meeting proceedings, and
presentations at scientific meetings.</li>
<li>Contribute to the development of new research programs
with internal and external collaborators across disciplines
and participate in developing and writing proposals for
external funding.</li>
<li>Interactions with stakeholders and air quality
forecasters, which will be the end-users of the new AQ
products.</li>
</ul>
<p> </p>
<p><strong>REQUIREMENTS INCLUDE</strong>:</p>
<p> </p>
<p>Educations and Experience:</p>
<p> </p>
<ul>
<li>PhD. degree in atmospheric sciences or closely related
disciplines</li>
<li>Well-developed experience of air quality forecasting and
variational data assimilation</li>
</ul>
<p> </p>
<p>Knowledge Skills and Abilities:</p>
<p> </p>
<ul>
<li>Advanced capabilities in air quality forecasting and
variational data assimilation.</li>
<li>Demonstrated knowledge of satellite data assimilation.</li>
<li>Ability to establish and maintain a nationally recognized
publication record.</li>
<li>Ability to participate in and interact productively with
experts from different disciplinary fields both within NCAR,
with our partner universities and national laboratory (i.e.,
NOAA/ARL and ESRL, CU Boulder, University of Maryland).</li>
<li>Strong skills in written and oral communication of
research results.</li>
<li>Ability to write proposals for research program
development.</li>
<li>Familiarity with the atmospheric boundary layer physical
and chemical processes</li>
<li>Familiarity with high performance computing architectures</li>
<li>Fluency in scientific programming languages such as
FORTRAN, C, C++, PERL and/or Python</li>
<li>Strong written and oral communication skills</li>
<li>Demonstrated record of research and publication</li>
<li>Familiarity with the proposal writing process for
different sponsors</li>
<li>Familiarity with GSI and CMAQ are desired.</li>
</ul>
<p> </p>
<p>The University Corporation for Atmospheric Research (UCAR) is
an <a
href="http://www1.eeoc.gov/employers/upload/eeoc_self_print_poster.pdf"><strong>equal
opportunity employer</strong></a>. We evaluate qualified
applicants without regard to race, color, religion, gender,
national origin, ancestry, age, marital status, sexual
orientation, domestic partner status, disability, or veteran
status.</p>
</dd>
<dt id="dspJobTxtJobLocDiv" class="cssDspJobHead"> Job Location </dt>
<dd id="jobPositionLocationDiv" class="cssDspJobBody"> Boulder,
Colorado, United States </dd>
<dt id="dspJobTxtPosTypeDiv" class="cssDspJobHead"> Position Type
</dt>
<dd id="translatedJobPostingTypeDiv" class="cssDspJobBody">
Full-Time/Regular </dd>
</dl>
<div class="cssDspJobHead">Appointment Type</div>
<div class="cssDspJobBody">Regular, Full-Time (R1)</div>
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