Providing Access and Visualization to Global Cloud Properties from GEO Satellites

Friday, 18 December 2015
Poster Hall (Moscone South)
Thad Chee1, Louis Nguyen2, Patrick Minnis3, Douglas Spangenberg4, Rabindra Palikonda4 and J Kirk Ayers5, (1)Science Systems and Applications, Inc. Hampton, Hampton, VA, United States, (2)Nasa, Hampton, VA, United States, (3)NASA Langley Research Center, Hampton, VA, United States, (4)Science Systems & Applications, Inc., Hampton, VA, United States, (5)SSAI, Hampton, VA, United States
Providing public access to cloud macro and microphysical properties is a key concern for the NASA Langley Research Center Cloud and Radiation Group. This work describes a tool and method that allows end users to easily browse and access cloud information that is otherwise difficult to acquire and manipulate. The core of the tool is an application-programming interface that is made available to the public. One goal of the tool is to provide a demonstration to end users so that they can use the dynamically generated imagery as an input into their own work flows for both image generation and cloud product requisition.

This project builds upon NASA Langley Cloud and Radiation Group’s experience with making real-time and historical satellite cloud product imagery accessible and easily searchable. As we see the increasing use of virtual supply chains that provide additional value at each link there is value in making satellite derived cloud product information available through a simple access method as well as allowing users to browse and view that imagery as they need rather than in a manner most convenient for the data provider.

Using the Open Geospatial Consortium’s Web Processing Service as our access method, we describe a system that uses a hybrid local and cloud based parallel processing system that can return both satellite imagery and cloud product imagery as well as the binary data used to generate them in multiple formats. The images and cloud products are sourced from multiple satellites and also “merged” datasets created by temporally and spatially matching satellite sensors. Finally, the tool and API allow users to access information that spans the time ranges that our group has information available. In the case of satellite imagery, the temporal range can span the entire lifetime of the sensor.