College of Science
Resources for students
out research in the fields of numerical weather prediction, atmospheric
transport and dispersion, and computational methods to optimize the
tools and to develop advanced methods to improve current capabilities.
This program is in a unique position to make a significant
contribution towards addressing many of the atmospheric transport and
dispersion modeling challenges. Our Current research activities include
the following main research areas (please click on the links embedded
in the following list or on the left side to get more details on the
specific areas and see pictures and animations):
our strengths in these areas by continuing to put additional emphasis
how the surface and atmosphere interact and continuing to address
of fundamental importance to atmospheric processes.
aerosol impacts on clouds and climate are being investigated.
transport and dispersion models (such as CALPUFF, HPAC/SCIPUFF,
VLSTRACK and JEM) are being evaluated
independently with field data
from urban to mesoscale field experiments.
of assessing the uncertainties in predictions of numerical weather
prediction models are being developed and tested.
- Computational Fluid Dynamics (CFD)
models are being used in research of
turbulent atmospheric boundary layer flows around obstacles and are
being tested with fluid modeling data.
meteorologiocal models are being used for application to mesoscale
atmospheric flows and are being tested with atmospheric observations
physics of mesoscale meteorologiocal models are being improved and
evaluated against atmospheric observations and analysis.
Particle Dispersion Models (LPDM) are being improved to account for a
variety of boundary layer stability conditions and generalized LPDM
algorithms are being developed for implementation in a variety of
boundary layer flow models.
of estimating the surface roughness of urban and industrial sites are
being proposed and tested with a comprehensive set of data.
- Field and laboratory data sets
and models of urban transport and dispersion are being acquired and
will be used in comprehensive model evaluation studies.
- Artificial Neural Network
algorithms are developed and used for
improving atmospheric mesoscale model predictions.
we sponsor an annual summer
workshop on Atmospheric Transport and Dispersion Modeling.
Approximately 75 papers are presented
See the CAMP
contact page for detailed