Abstract
One of the key factors in the improved understanding of climate science is the development and improvement of high fidelity climate models. These models are critical for projections of future climate scenarios, as well as for highlighting the areas where further measurement and experimentation are needed for knowledge improvement. In this paper, we focus on several computing issues associated with climate change modeling. First, we review a fully coupled global simulation and a nested regional climate model to demonstrate key design components, and then we explain the underlying restrictions associated with the temporal and spatial scale for climate change modeling. We then discuss the role of high-end computers in climate change sciences. Finally, we explain the importance of fostering regional, integrated climate impact analysis. Although we discuss the computational challenges associated with climate change modeling, and we hope those considerations can also be beneficial to many other modeling research programs involving multiscale system dynamics.
