Case Study 1 



Climate Modeling 



Sea surface temperature from a multi-year simulation with the UCLA coupled atmosphere-ocean model. 

 The atmospheric component of the model is the UCLA General Circulation Model and the oceanic compo- 

 nent is the GFDL Modular Ocean Model. The simulation was performed on the Cray Y-MP at the San 

 Diego Supercomputer Center. 



Understanding the Earth's climate system and its 

 trends is one of the most challenging problems 

 facing the scientific community today. Better 

 understanding of our climate system is critical 

 for the Nation as it prepares for the 21st century. 

 The Earth's atmosphere-ocean system and the 

 physical laws that control its behavior are com- 

 plex and contain subtle details. This system is 

 only crudely represented by the most compre- 

 hensive of present-day climate models. 

 Improvements in the computational modeling of 

 many of the component physical processes, such 

 as cloud-radiation interaction, will require long- 

 term effort. Climate model improvements will 

 necessitate a hundred to thousand-fold increase 

 in computing, communications, and data man- 



agement capabilities before these goals can be 

 met. In addition, large increases in model detail 

 and sophistication are necessary for regional cli- 

 mate change forecasting. 



Under the sponsorship of the Federal HPCC 

 Initiative and other programs, new computing 

 and communications resources are being devel- 

 oped for climate research. Current state-of-the- 

 art climate models are being redesigned to exe- 

 cute efficiently on promising new scalable archi- 

 tecture systems. Scientists are also investigating 

 distributed computing strategies that will use 

 gigabit-per-second data transfer between distant 

 supercomputers. 



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