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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.
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