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Proceedings Paper

Rich client data exploration and research prototyping for NOAA
Author(s): Michael Grossberg; Irina Gladkova; Ingrid Guch; Paul Alabi; Fazlul Shahriar; George Bonev; Hannah Aizenman
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Paper Abstract

Data from satellites and model simulations is increasing exponentially as observations and model computing power improve rapidly. Not only is technology producing more data, but it often comes from sources all over the world. Researchers and scientists who must collaborate are also located globally. This work presents a software design and technologies which will make it possible for groups of researchers to explore large data sets visually together without the need to download these data sets locally. The design will also make it possible to exploit high performance computing remotely and transparently to analyze and explore large data sets. Computer power, high quality sensing, and data storage capacity have improved at a rate that outstrips our ability to develop software applications that exploit these resources. It is impractical for NOAA scientists to download all of the satellite and model data that may be relevant to a given problem and the computing environments available to a given researcher range from supercomputers to only a web browser. The size and volume of satellite and model data are increasing exponentially. There are at least 50 multisensor satellite platforms collecting Earth science data. On the ground and in the sea there are sensor networks, as well as networks of ground based radar stations, producing a rich real-time stream of data. This new wealth of data would have limited use were it not for the arrival of large-scale high-performance computation provided by parallel computers, clusters, grids, and clouds. With these computational resources and vast archives available, it is now possible to analyze subtle relationships which are global, multi-modal and cut across many data sources. Researchers, educators, and even the general public, need tools to access, discover, and use vast data center archives and high performance computing through a simple yet flexible interface.

Paper Details

Date Published: 12 August 2009
PDF: 12 pages
Proc. SPIE 7456, Atmospheric and Environmental Remote Sensing Data Processing and Utilization V: Readiness for GEOSS III, 74560C (12 August 2009); doi: 10.1117/12.826523
Show Author Affiliations
Michael Grossberg, The City College of New York (United States)
Irina Gladkova, The City College of New York (United States)
Ingrid Guch, NOAA (United States)
Paul Alabi, The City College of New York (United States)
Fazlul Shahriar, The City College of New York (United States)
George Bonev, The City College of New York (United States)
Hannah Aizenman, The City College of New York (United States)


Published in SPIE Proceedings Vol. 7456:
Atmospheric and Environmental Remote Sensing Data Processing and Utilization V: Readiness for GEOSS III
Mitchell D. Goldberg; Hal J. Bloom, Editor(s)

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