TECA: A Parallel Toolkit for Extreme Climate Analysis

نویسندگان

  • Prabhat
  • Oliver Rübel
  • Surendra Byna
  • Kesheng Wu
  • Fuyu Li
  • Michael F. Wehner
  • E. Wes Bethel
چکیده

We present TECA, a parallel toolkit for detecting extreme events in large climate datasets. Modern climate datasets expose parallelism across a number of dimensions: spatial locations, timesteps and ensemble members. We design TECA to exploit these modes of parallelism and demonstrate a prototype implementation for detecting and tracking three classes of extreme events: tropical cyclones, extra-tropical cyclones and atmospheric rivers. We process a modern TB-sized CAM5 simulation dataset with TECA, and demonstrate good runtime performance for the three case studies.

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تاریخ انتشار 2012