In the United States, photochemical air quality models are the principal tools used by governmental agencies to develop emission reduction strategies aimed at achieving National Ambient Air Quality Standards (NAAQS). Before they can be applied with confidence in a regulatory setting, models' ability to simulate key features embedded in the air quality observations at an acceptable level must be assessed. With this concern in mind, the U.S. Environmental Protection Agency (EPA) has recently completed several executions of the Community Multiscale Air Quality model (CMAQ) and the Regional Modeling System for Aerosols and Deposition model (REMSAD) to simulate air quality over the contiguous United States during year 2001 with a horizontal cell size of 36 km x 36 km. The meteorological model MM5 and the emission processor SMOKE were used to generate the input fields necessary for CMAQ and REMSAD. Since these annual model simulation generate a huge amount of information, failure to properly organize the results may lead to confusion and hamper the evaluation procedure. The challenge is therefore to identify a technique that would make use of all pertinent observations over a large region and clearly indicate which spatial and temporal features are reproduced by the model. To address this challenge, we propose a procedure to objectively condense the spatial and temporal observational domain into a limited number of homogeneous categories.