[ES_JOBS_NET] Postdoctoral Position in Extreme Precipitation Events Diagnosis, University of California, Davis

Postdoctoral Position in Extreme Precipitation
Events
Diagnosis

At the University of California, Davis

The UC
Davis Department of Land, Air and Water Resources
seeks a postdoctoral scholar to be supervised by Prof. Richard
Grotjahn and
Prof. Paul Ullrich.  A
successful
candidate is expected to begin in Fall 2016.

 The
postdoctoral scholar position is in conjunction with
Project Hyperion, a new and exciting multi-institutional
Department of Energy
project directed at nationwide stakeholder-driven regional climate
data
evaluation.  In addition to
research,
prospective candidates are expected to engage with water manager
and other
related stakeholders to understand data needs. The project
incorporates
outreach related to four river basins (Sacramento-San Joaquin,
Upper Colorado, Kissimmee,
and Susquehanna). The successful applicant will work on projects
described
below related to the simulation, synoptics, and dynamics of the
large-scale
flow associated with extreme precipitation events in regions
across the US.
This project combines expertise in atmospheric synoptics, extreme
value
statistics, and climate modeling.

 The
research focuses on the development of software for
extreme precipitation (PEx) detection and associated metrics.
Example metrics
include ETCCDI indices, 95% and 5% seasonal thresholds, fixed
thresholds, and
return period. A major component of this research will be the
development of
automated algorithms for PEx event detection and cause. The areas
of extreme precipitation
are first detected and then the causes of each area (frontal,
cut-off low,
tropical cyclone, convection, etc.) are identified from large
scale patterns in
relevant variables. These large-scale patterns will be the
foundation for
empirical statistical downscaling of PEx events.

These algorithms developed will be applied to
historical data
(primarily gridded and reanalysis datasets) and model output. The
tasks above
may require implementation of some extreme value statistics as
well as
preprocessing of the data.   

A PhD in an atmospheric or closely related
science is
required. Some programming experience is required (preferably
FORTRAN or
C/C++). Knowledge of atmospheric dynamics and atmospheric modeling
is strongly
preferred. Also desired, but not required is experience with NCL,
R, experience
with large datasets, and/or expertise in extreme value statistics.

Demonstrable written and verbal communication
skills are
also required, as the successful applicant is responsible for the
production of
reports, journal articles and conference presentations and is
encouraged to
explore instructional activities and authorship of grants.

 The
position is open
until filled. The initial appointment is for one year, with
funding available for
up to three years. Salary is commensurate with experience with an
expected
range of $50,123 to $56,385.  The
position includes vacation with supervisory approval and health
care benefits (which
includes family coverage).  The
position
is covered by a collective bargaining unit.

 To
ensure
consideration, a complete application packet should be submitted
by 23
September 2016. Applications should be submitted electronically to
Prof.
Richard Grotjahn (grotjahn@ucdavis.edu) and include the following:   

1. 
A cover letter of
no more than 2 pages that outlines your interests and how they
relate to this
project. Include evidence of your experience and your expertise in
synoptics, dynamics,
global atmospheric modeling, statistics, and computer programming. 

2.  Your
CV containing
your contact information, your educational experience and degrees,
lists of
your publications and presentations, and any other academic
information (e.g.
TA experience) you feel is relevant. Publication lists with links
to online
papers are desirable.

3.  Names
and contact
information for 3 references. The contact information should
include postal
mail address, telephone number(s), and email address for each
reference.

4.  Transcripts
of
your graduate education. Preferred, but not required are
transcripts of undergraduate
education (such transcripts are especially useful if your computer
programming
or meteorology coursework was mainly as an undergraduate).

 

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