Several tools are useful and freely avilable for analyzing and visualizing TROPOMI data files. A list including brief descriptions and links (where available) are provided below.

PyCAMA - A python-based tool designedI to analyze all TROPOMI data files parameters. PyCAMA stands for Python “Correleer Alles met Alles” (Correlate Everything with Everything). Its toolkit is useful for algorithm developers and validation researchers to perform a quick check on the output of a level 2 retrieval algorithms. It can be used to read in TROPOMI swaths from various level 2 files, for which the correlations between all given parameters are calculated (hence the name “correlate everything with everything”). This software is being run at the PDGS data processing facility to extract key data quality parameters and can be used to produce Level 3 gridded data as well.

HARP - Software designed to serve as a data harmonization toolset for scientific earth observation data.

Panoply - Visualization tool designed to plot geo-referenced data including the netCDF-4 format used for TROPOMI data files. 

ADAGUC - Another visualization tool design currently designed to plot many types of data including satellite data from OMI. It will be possible to plot TROPOMI using this tool when the data becomes available. Datasets from different instruments are converted to the ADAGUC data product standards format and are made available to other users by using the OGC Web Services. Satellite swath data can be retrieved using the Web Feature Service. Using the Web Services it is possible to reproject, resample and make selections in space and time.