MELODIES MONET is a joint project between NCAR and NOAA to develop a modular framework that integrates existing and future diverse atmospheric chemistry observational datasets with chemistry model results for the evaluation of air quality and atmospheric composition. MELODIES MONET combines the Model EvaLuation using Observations, DIagnostics and Experiments Software (MELODIES) project at NCAR with the Model and ObservatioN Evaluation Toolkit (MONET) project at NOAA to develop a python diagnostic package that is open source, generic, portable, and model-agnostic. Overall, the project provides a framework for evaluating a wide range of models in a more consistent manner. The tool is accessible to everyone including university and national laboratory researchers, as well as graduate students and postdocs.

The goal is to evaluate research, operational, and regulatory models against a variety of observations including surface, aircraft, and satellite data all within a common framework. MELODIES MONET uses the functionality already developed by MONETIO to read in multiple observational and model datasets and MONET to do pairing/analysis/plotting. For more information on MONET and MONETIO please refer to:


MELODIES MONET is currently under development. The code is public to encourage collaboration amongst the community. Do not publish results using MELODIES MONET without consulting the development team.


Please cite the following to acknowledge use of MELODIES MONET

  • Baker, Barry; Pan, Li. 2017. “Overview of the Model and Observation Evaluation Toolkit (MONET) Version 1.0 for Evaluating Atmospheric Transport Models.” Atmosphere 8, no. 11: 210