The key to analysis of simulation datasets is software infrastructure. Below are my packages, packages I contributed to, and some all time favorites. Some tutorials are also available.
Python interface to the Remote Sensing Information Gateway
Access EPA, NOAA, and NASA data: from surface monitors to the latest satellites in familiar pandas and xarray objects.
AirFuse
Combines air quality model forecasts (NASA or NOAA) with surface observations (EPA) and low-cost sensors (PurpleAir) to create a best estimate map
Python Environment for Reaction Mechanism/Mathematics
Network-based queries of chemical mechanisms (Carbon Bond, GEOS-Chem, MCM, etc)
Air Quality Model Boundary Conditions
https://github.com/barronh/aqmbc
(previous options: http://github.com/barronh/geos2cmaq; http://github.com/barronh/pygeos2cmaq)
PseudoNetCDF Python Library
Do you like air quality models? Do you struggle with the many custom binary formats? PseudoNetCDF presents a netcdf-like interface to data from many, many, many formats (CAMx, GEOS-Chem, CMAQ, AERMOD, GEOS, ICARTT, HYSPLIT, ...)
Python-based Kinetic Pre-Processor
Python-based Process Analysis
Integrate processes output from CAMx, CMAQ, or WRF-Chem to synthesize multi-dimensional data in logical air parcels.
NetCDF Java Library
http://www.unidata.ucar.edu/software/netcdf-java/
Python-based Performance Analysis Supporting System
https://dawes.sph.unc.edu/trac/pyPASS
Dynamically Simple Model of Atmospheric Chemical Complexity
http://github.com/barronh/DSMACC
Wisconsin Horizontal Interpolation Program for Satellites
http://github.com/barronh/WHIPS
matplotlib
NumPy
SciPy
NetCDF Operators (NCO)
Climate Data Operators