Developing a Regional Climate Model
an ORNL LDRD project

CSM staff are participating in both the science and infrastructure portions of this ORNL-funded LDRD project. more info

Science goals

As a first demonstration, the project will obtain long term records of stream flow from gauging stations in the region and benchmark the regional climate model's hydrological results against this record. We will perform an assessment of the change in stream flow using CCM3 Global Circulation Model to provide projected climate change over the next 50 years with atmospheric CO2 increasing at a rate of 1% per year and downscaling accomplished by the regional climate model for performing hydrological calculations.

Specific tasks of this project include:

1. Nesting a state-of-the-art mesoscale regional climate model within the parallel atmospheric GCM CCM3 over the eastern United States, and replacing the surface boundary condition soil-vegetation-atmosphere transfer scheme in the mesoscale climate model with an existing ORNL regional terrestrial ecosystem carbon-water model, extended to incorporate additional processes (e.g., albedo) required for integration with the regional climate model;

   This coupling will provide a unique capability for an internally consistent simultaneous simulation of surface boundary conditions and carbon cycle dynamics for the assessment of carbon sequestration and the impacts of climate change.

2. Establishing a benchmark data set based on regional stream-flow gauge stations;



3. Incorporating a surface hydrology routing scheme in the regional climate and ecosystem carbon-water model; and



4. Benchmarking the performance of the integrated regional model by testing predictions of stream flow against the regional stream flow data set.

Infrastructure goals

The heart of the infrastructure for regional climate collaborators will be a computational service that shares capabilities across geographically distributed computers and data archives. It aggregates the hardware and software resources of any number of sites that are loosely connected across a network and offers up their combined power and capabilities through client interfaces that are familiar from the world of uniprocessor computing.

ORNL is very strong in the development of distributed computing infrastructure with proven tools, such as PVM and NETSOLVE, and ongoing development projects, such as CUMULVS and HARNESS and Problem Solving Environments. For this LDRD proposal we will integrate the capabilities of the existing tools to provide a computational grid structure for existing CSMD and ESD computing equipment and extend CUMULVS functionality to include the coupling of parallel models. To unify these projects and to support externally-developed software for use within the test grid, the infrastructure portion of this proposal will define, assemble, and /or build the appropriate infrastructure that:

1. Allows compatible parallel model components to plug together using a standardized interface;

   This enables a systematic approach for building multi-component coupled models to test various configurations.

2. Provides a mechanism for scheduling the various grid components (parallel processors, storage servers, and visualization engines) to complete an analysis or model ensemble;



3. Catalogues, provides access, and performs data distillation of the large model output runs; and



4. Unifies various grid components using a graphical user interface (GUI) that is useful to both programmers and end users.

Computational grid

The simulation and assessment of streamflow will be carried out in a computational grid structure showing our ability to integrate novel computer science infrastructure projects with innovative regional climate science research.

New and existing computing resources at ORNL and UTK will be used to form a grid testbed on which model development, production, and assessment activities will be undertaken. The grid resources include two PC-based clusters (48 CPUs total), an SGI Origin 2000 (8 CPUs), an SGI Onyx SMP (8 CPUs), a DEC Server (2 CPUs), and a SUN Enterprise 450 data server (180 Gigabytes disk storage). A variety of high-speed and legacy networks will be used to link these components into a usable computational grid that will be accessible from researcher's desktop workstations.