The University of Miami's Rosenstiel School of Marine and Atmospheric
Sciences (RSMAS) is seeking a research associate to work with
hydrographic data. The objective of the project is to develop
statistical models for estimating salinity and density from
observations of temperature together with knowledge of location and
time. Because the relationship between salinity and temperature can
be highly variable due to meandering fronts, it is important to be
able to recognize from which side of a front the data come.
Consequently, developing a water-type classifier is part of the
project. Once the models have been developed, they are to be
implemented as a component of computational codes for assimilating
data into an ocean-circulation model.
The relationship between temperature and salinity is to be derived
from a database of temperature-salinity-pressure profiles irregularly
distributed over the world oceans and over the past thirty years. A
much larger data-base of temperature-depth profiles is available for
use in predicting salinity. Satellite-based observations are
available to help in determining where the more recent data are
situated relative to fronts. The equation of state for sea water can
be used to transform the estimated salinity, together with observed
temperature, into estimates for density. The salinity estimates
should be constrained so that the resulting density increases
monotonically with depth.
The successful candidate should have substantial computational skills.
Ability to work with large data sets is imperative, as is the ability
to examine the data graphically. Some knowledge of statistics is
essential, especially regression, classification, and spatial
statistics. Experience with splus and matlab is highly desirable, as
is facility with fortran and/or C. He/she should be comfortable
working in a unix environment. Experience working with hydrographic
data, while not essential, is certainly desirable.
The work is to be done in collaboration with scientists at UM and at
the Atlantic Oceanographic and Meteorological Laboratory (AOML), so
there will be substantial guidance in how to approach the project.
However, the successful candidate should be able to function with a
minimal of supervision once the project is underway and he/she should
assume responsibility for the project's success. Salary will reflect
the candidate's experience and qualifications.
RSMAS and AOML are located on Virginia Key, a short drive across
Biscayne Bay from downtown Miami, Florida. Contact Arthur Marino
(305-361-4193/marino@rsmas.miami.edu) or Carlisle Thacker
(305-361-4323/thacker@aoml.noaa.gov) for further information. To
apply, send resume to Jean Overton, RSMAS, 4301 Rickenbacker Causeway,
Miami FL 33149. Please include names, addresses, and phone numbers of
at least three references.
