Perturbator
Abstract
A Python tool for generating spatially-correlated random perturbations for atmospheric emission fields, designed for ensemble data assimilation applications. Uses gamma distributions and Gaussian kernel smoothing to create perturbation fields with specified error magnitudes and spatial correlation lengths.
Fields of Study & Subjects
Meteorological Phenomena and Simulations
Atmospheric chemistry and aerosols
Atmospheric and Environmental Gas Dynamics
Publication details
- Journal / source
- Zenodo (CERN European Organization for Nuclear Research)
- Publication date
- 11 March 2026
- Language
- EN