PNNL-13501 - Pacific Northwest National Laboratory

Study Control Number: PN99059/1387
Prototype Regional Climate Collaboration Center
L. Ruby Leung
Understanding climate change and its regional consequences is important for supporting national and international energy
and environmental policies. A prototype Regional Climate Collaboration Center is being assembled for the generation of
regional climate change scenarios and assessment of climate change impacts in water resources and agriculture. A
problem-solving environment is being developed to support the advanced modeling framework.
Project Description
A prototype Regional Climate Collaboration Center is
being assembled that makes use of a regional climate
model, a watershed hydrology model, a hydrosystem
management model, and a crop model for the purpose of
assessing regional impacts of global climate change. A
parallel version of the regional climate model has been
developed, and selected physics parameterizations have
been modularized for contribution toward the
development of a community regional climate model. A
problem-solving environment is being developed for
regional climate modeling. Several proofs of principle
have been demonstrated.
Introduction
This project was proposed to support the missions of the
DOE Accelerated Climate Prediction Initiative. One
component of Accelerated Climate Prediction Initiative is
the establishment of Regional Climate Collaboration
Centers, which would provide the link between advanced
climate prediction models and those who will use output
of these models for scientific research and assessment of
possible impacts of climate change. Products to be
developed and maintained to support climate change
impact assessment activities include downscaling tools
that bridge the spatial scales typically resolved by global
climate models and that needed to resolve hydrological
and ecological processes for assessing the impacts of
climate change and variability. This project is aimed at
developing and maintaining a suite of physically based
process models and product delivery tools for the impact
assessment community.
We have developed a regional climate-hydrology
modeling capability that has proven to be very useful for
assessing climate change impacts. An outstanding feature
of our regional modeling system is its capability to
238 FY 2000 Laboratory Directed Research and Development Annual Report
provide high spatial resolution (1 to 10 km) simulations of
climate and hydrologic conditions in regions with
complex topography through a subgrid parameterization
of orographic precipitation. High spatial resolution is
critical for water resources and ecosystem managers for
reliable and defensible estimates of water and fisheries
management impacts. Our ability to couple the regional
climate model, PNNL-RCM (Leung and Ghan 1995,
1998), and the watershed model (DHSVM) (Wigmosta et
al. 1994; Leung et al. 1996) has been enthusiastically
received as the state-of-the-science tool for assessing
water, fishery, and ecosystem management options.
Results and Accomplishments
Parallelization of a Regional Climate Model
One of the most computationally demanding components
of the Collaboration Center is regional climate modeling.
We have adapted the regional climate model to massively
parallel architectures. Two parallel versions of the
regional climate model have been developed. In
collaboration with Professor Suresh Kothari of Iowa State
University, the automatic parallelization tool (ParAgent)
has been applied to develop a one-dimensional
decomposition parallel version of PNNL RCM. The code
has been tested on Beowulf clusters. Load balancing
associated with the subgrid parameterization of
orographic precipitation is tackled by assigning different
numbers of longitude bands with approximately equal
numbers of subgrid elevation bands to each processor.
This parallel regional climate model is, however, not ideal
for massively parallel computation.
In collaboration with John Michalakes of Argonne
National Laboratory, we have developed a parallel
regional climate model by implementing the subgrid
orographic precipitation scheme to the parallel Penn
State/NCAR Mesoscale Model (MM5) that runs on a