Description

Visualization of air quality forecasts and observations in a 4-dimensional environment with interactive capabilities is a novel and unprecedented approach for data evaluation. This visualization can be performed using the Visualization and Analysis Platform for Ocean, Atmosphere, and Solar Researchers (VAPOR) tool. The objective of this project is to develop a user-friendly extension of the current version of VAPOR (v2.3) that will allow modeled and observed air quality data to be displayed in tandem in the VAPOR 4-D model space. The extension was developed using the python programming language. The program generates a VAPOR-ready rendering file that assigns a color value to the representative graphic according the user-specified air quality observation. Observed metrics are synced with volumetric air quality data, commonly generated using WRF-CHEM, in time to allow visual comparison of both datasets simultaneously. This visualization capability is cutting-edge and is being developed for use in evaluating data collected during the Front Range Air Pollution and Photochemistry Experiment (FRAPPE).