Presented at the
1997 CRPC Annual Meeting Poster Session
The development of a problem-solving environment (PSE) for air quality
models is presented. The focus of the work is on the integration of a
variety of parallel and sequential computers into a unified workbench
accessible to scientists and engineers who concentrate on the science and
not on the parallel programming aspects of air pollution modeling. In
addition, the problem-solving environment is designed to serve as a tool
to be used in education and public awareness efforts. The central idea of
this work is that of model abstraction in physical simulations. The
abstraction of the PSEs for physical simulations deals with space, time,
and a collection of model data. We call this problem domain the 3D+T+Mk
domain. The 3D+T+Mk abstraction is used to navigate through input and
output data, manage I/O, and specify modules of parallel programs. The
first problem in which these ideas are implemented is air pollution
modeling in the South Coast Air Basin of California. We present results of
developments of a PSE for atmospheric chemical dynamic models that
describe mathematically the transport and transformation of pollutants
using a three-dimensional Eulerian approach. This work uses the California
Institute of Technology (CIT) model as the underlying air quality model
to drive the PSE.