TECA is a collection of climate analysis algorithms geared toward extreme event detection and tracking implemented in a scalable parallel framework. The code has been successfully deployed and run at massive scales on current DOE supercomputers. TECA’s core is written in modern C++ and exploits MPI + X parallelism where X is one of threads, OpenMP, or GPUs. The framework supports a number of parallel design patterns including distributed data parallelism and map-reduce. While modern C++ delivers the highest performance, Python bindings make the code approachable and easy to use.
The Calibrated and Systematic Characterization, Attribution, and Detection of Extremes (CASCADE) project advances the Nation’s ability to identify and project climate extremes and how they are impacted by environmental drivers.