NPAC Technical Report SCCS-533
The Parallelization of a Weather Predition Model
Gregor von Laszewski
Submitted October 01 1993
Abstract
Recent devastating events caused by storms show how important
the development of a reliable storm prediction system is. One such
effort was started at the Center for Analysis and Prediction of Storms
(CAPS) in Oklahoma. This institute tries to develop techniques for
the practical prediction of weather phenomena on scales ranging from a
few kilometers to hundreds of kilometers.
The use of a prediction model is possible in near future because a
network of 175 Doppler radars will be installed around the U.S in
order to gather the necessary initial data for the model. The
initialization is an important part of this application since the
precise initial data leads to more accurate predictions.
It is easy to imagine that this data accumulation leads to
huge storage requirements. One way to deal with this problem is to
distribute the prediction of a storm at the area of interest. Since,
many sites have different computers it is useful to develop a highly
portable source code. Another important requirement is that a
modification of the program should be possible with moderate effort in
order to incooperate new computational schemes determining the
modeling equations.
Naturally a storm has to be predicted as fast and long as possible
with very high accuracy in order to avoid damages by invoking early
prevention methods. This can be achieved by, e.g. using
supercomputers for solving the modeling equations.
This report describes the parallelization of a weather prediction code
using the dataparallel programming scheme. In addition, it is shown
how to obtain a version for message passing computers while using High
Performance Fortran. Benchmarking for the dataparallel program is done
on a CM5 with 32 nodes and vector units.