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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8 Comments

Daryl Ann Winstead (Lake Victoria Water Resources II) 13-04-2016, 20:54

Amazing! This data is awesome and I can’t wait for the software to become open source so I can test it out! Great job!

Reply
Jordan Vaa 20-04-2016, 10:28

Yea! The process of getting it released for open source has been a long one, but we hope to have it finished soon! We cant wait to start getting community involvement in the process of updating and expanding the functionality of the code!

Reply
Katie Moore 20-04-2016, 10:33

Thank you, Daryl Ann! We’re excited for open source too. Just a matter of waiting for various clearances now.

Reply
Jessica Sutton 12-04-2016, 17:37

This project makes me want to include CALIPSO data in our work. I am curious why you are making a new software to visualize and analyze the data when you could use a program like R to do similar things. Are there specific functions or components of the new software that make it better? This is really great work 🙂

Reply
Jordan Vaa 13-04-2016, 16:22

The motivation behind writing this software is to allow users will less coding ability to more easily engage the data. While much of the visualization achieved through VOCAL could be done script-wise, that is very time and effort intensive, and also requires fairly extensive coding ability. With this software, the visualization becomes much easier, as well as removing the coding ability altogether.

In addition to all that, VOCAL gives the ability to pick out specific features of the CALIPSO curtain, and export them to share with other researchers, as well as to combine for interesting effects over time or area.

Reply
Katie Moore 20-04-2016, 10:35

Thanks, Jessica. That vertical profile atmospheric data is powerful. I want to learn more about categorizing aerosols myself.

Reply
Leigh Sinclair 08-04-2016, 15:02

Awesome job! Very informative! Makes me want to go try out CALIPSO data

Reply
Jordan Vaa 12-04-2016, 15:04

It would definitely be cool to utilize more CALIPSO data in our projects

Reply

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