This article is a part of the NASA DEVELOP’s Summer 2017 Virtual Poster Session. For more articles like these, click here
Project Team: CALIPSO Cross-Cutting
Team Location: NASA Langley Research Center – Hampton, Virginia
Authors: Collin Pampalone, Ryan Avery, William Turner
Mentors/Advisors: Dr. Kathleen Moore (NASA Langley Research Center), Dr. Kenton Ross (NASA Langley Research Center)
Past or Other Contributors: Grant Mercer, Nathan Qian, Ashna Aggarwal, Jordan Vaa, Kathleen Moore, Ahmad Aburizaiza, Andrea Martinez, Adama Ba, Joseph Driscoll
This image shows curtains of CALIPSO backscatter over MODIS imagery during a long-range dust transport event off the western coast of Africa. Image Credit: Roman Kowch, CALIPSO Science Team
Abstract:
The Cloud-Aerosol LiDAR and Infrared Pathfinder Satellite Observation (CALIPSO) satellite’s CALIOP sensor generates vertical LiDAR profiles of the atmosphere at a global scale. Currently, the standard visualization tool for these data is written in Interactive Data Language (IDL), a proprietary language that does not support features for tracking aerosols, selecting data, or sharing those selected sections. This makes working with CALIPSO data difficult for researchers and does not allow them to visually identify aerosol features from these data. Previous DEVELOP teams have built a working version of the Visualization of CALIPSO (VOCAL) software, a Python language replacement for this IDL-based software. During this term, the team enhanced VOCAL by improving the shape drawing tool, adding the capability to view multiple levels of data, and adding more flexible data inputs and outputs that support a decentralized database in the form of a CSV file. These features will increase the usability of VOCAL, expediting the process of visually identifying features and analyzing the resulting subsets of data. Finally, the DEVELOP team conducted a case study with Saharan dust transport over the Atlantic Ocean to test the capabilities of the VOCAL software and to produce a database of dust events. The database and case study will help members of the CALIPSO Science Team compare the performance of classification algorithms used to create Level 2 (L2) CALIPSO data products, and support preliminary analysis of the atmospheric interactions and consequences related to long-range dust transport.