Research Tools & Software

Software tools and libraries developed to advance climate and atmospheric research

fastKDE

Documentation

High-performance kernel density estimation library for arbitrarily dimensioned data. Provides extremely fast computational performance (up to 10,000x faster than traditional methods) with comparable statistical accuracy to state-of-the-art packages.

Key Features:

  • Rapid calculation of probability density functions
  • Standard and conditional PDF calculations
  • Multi-dimensional data support
  • Efficient handling of large datasets
Applications: Statistical distribution analysis, multi-dimensional data exploration, conditional probability estimation

TECA

Documentation

Toolkit for Extreme Climate Analytics - A powerful parallel data analytics framework designed for large-scale climate research. Written in C++ with Python bindings and state-of-the-art performance scaling using "MPI + X" architecture.

Key Features:

  • High-performance parallel computing capabilities
  • Advanced climate event detection algorithms
  • Python bindings for flexible scripting
  • GPU and multi-threading support
Applications: Storm tracking, atmospheric river detection, tropical cyclone analysis, water vapor transport calculations

simpleMPI

PyPI

A Python wrapper around mpi4py that simplifies parallel computing for embarrassingly parallel tasks. Provides easy scattering of iterable objects across processors with automatic MPI initialization and load balancing.

Key Features:

  • Simple parallel loop execution (parfor function)
  • Automatic MPI initialization and cleanup
  • Even distribution of work across processors
  • High-level abstraction over mpi4py complexity
Applications: Embarrassingly parallel computations, SPMD tasks, large-scale parameter sweeps, batch processing