The Smoke-Screen: An Open-Source Visualizer of CALIPSO Data

Category: Monitoring Environmental Health and Disturbances
Project Team: CALIPSO Cross-Cutting III
Team Location: NASA Langley Research Center – Hampton, Virginia

Atmospheric scientists analyze satellite data as part of their assessments of atmospheric health. One such satellite, the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO), outputs images of longitudinal cross-sections of the Earth’s atmosphere. Depending on the wavelength of light used in the observation, it is possible to detect the presence of various aerosols. Some are natural sources, like dust storms, and sulfur dioxide from volcanos. Others are human-made, like sulfates from factories and smoke from burning biomass. It is important to track aerosols because an abundance of atmospheric aerosols contribute to accelerated cooling and further warming of the Earth. The first instance of a visualizer for this data was written in an obscure, proprietary language, Interactive Data Language (IDL), making further modification of this tool virtually impossible. Since then, DEVELOP has produced new visualization software, Visualization of CALIPSO (VOCAL), written in Python. At the completion of the previous term, in addition to displaying CALIPSO images, the team added the ability for the user to “select” regions of interest by drawing shapes and assigning attributes to them. This information can subsequently be pushed to a backend database for the purposes of sharing and collaboration. However, the tool still needed to be enriched with other features such as better exception-handling and descriptors for annotations, and it needed to have cross-platform compatibility. Consequently, we have added these and other features to enrich the user experience, and we streamlined installation of the software on the Windows and Mac OS X operating systems. These updates have greatly improved VOCAL’s usability.

Screenshot of “one-click” Windows installer with example data and drawn polygons behind. Image Credit: CALIPSO Cross-Cutting III Team

Authors:
Kathleen Moore
Jordan Vaa

Mentors/Advisors:
Grant Mercer (University of Nevada, Las Vegas)
Dr. Kenton Ross (NASA Langley Research Center)

Past/Other Contributors:
Emily Adams (Center Lead)
Nathan Qian
Courtney Duquette
Ashna Aggarwal

Abstract:

Atmospheric scientists analyze satellite data as part of their assessments of atmospheric health. One such satellite, the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO), outputs images of longitudinal cross-sections of the Earth’s atmosphere. Depending on the wavelength of light used in the observation, it is possible to detect the presence of various aerosols. Some are natural sources, like dust storms, and sulfur dioxide from volcanos. Others are human-made, like sulfates from factories and smoke from burning biomass. It is important to track aerosols because an abundance of atmospheric aerosols contribute to accelerated cooling and further warming of the Earth. The first instance of a visualizer for this data was written in an obscure, proprietary language, Interactive Data Language (IDL), making further modification of this tool virtually impossible. Since then, DEVELOP has produced new visualization software, Visualization of CALIPSO (VOCAL), written in Python.

At the completion of the previous term, in addition to displaying CALIPSO images, the team added the ability for the user to “select” regions of interest by drawing shapes and assigning attributes to them. This information can subsequently be pushed to a backend database for the purposes of sharing and collaboration. However, the tool still needed to be enriched with other features such as better exception-handling and descriptors for annotations, and it needed to have cross-platform compatibility. Consequently, we have added these and other features to enrich the user experience, and we streamlined installation of the software on the Windows and Mac OS X operating systems. These updates have greatly improved VOCAL’s usability.

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