Tropospheric data from a number of aircraft campaigns have been gridded onto global maps, forming “data composites” of chemical species important in ozone photochemistry. Although these are not climatologies in the sense of a long temporal average, these data summaries are useful for providing a picture of the global distributions of these species and are a start to creating observations-based climatologies. Using aircraft measurements from a number of campaigns, we have averaged observations of O3, CO, NO, NOx, HNO3, PAN, H2O2, CH3OOH, HCHO, CH3COCH3, C2H6, and C3H8 onto a 5° latitude by 5° longitude horizontal grid with a 1-km vertical resolution. These maps provide information about the distributions at various altitudes, but also clearly show that direct observations of the global troposphere are still very limited. A set of regions with 10°–20° horizontal extent has also been chosen wherein there is sufficient data to study vertical profiles. These profiles are particularly valuable for comparison with model results, especially when a full suite of chemical species can be compared simultaneously. The O3 and NO climatologies generated from measurements obtained during commercial aircraft flights associated writh the MOZAIC and NOXAR programs are incorporated with the data composites at 10–11 km. As an example of the utility of these data composites, observations are compared to results from two global chemical transport models, MOZART and IMAGES, to help identify incorrect emission sources, incorrect strength of convection, and missing chemistry in the models. These comparisons suggest that in MOZART the NOx biomass burning emissions may be too low and convection too weak and that the transport of ozone from the stratosphere in IMAGES is too great. The ozone profiles from the data composites are compared with ozonesonde climatologies and show that in some cases the aircraft data agree with the long-term averages, but in others, such as in the western Pacific during PEM-Tropics-A, agreement is lacking. Finally, the data composites provide temporal and spatial information, which can help identify the locations and seasons where new measurements would be most valuable. All of the data composites presented here are available via the Internet (http://aoss.engin.umich.edu/SASSarchive/).