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Statistical Analysis of Massive Data Streams: Proceedings of a Workshop (2004)

Chapter: GLOBAL AND REGIONAL SURFACE WIND FIELD INFERENCES FROM SPACE-BORNE SCATTEROMETER DATA

« Previous: Global and Regional Surface Wind Field Inferences Given Spaceborne Scatterometer Data Ralph F.Milliff
Suggested Citation:"GLOBAL AND REGIONAL SURFACE WIND FIELD INFERENCES FROM SPACE-BORNE SCATTEROMETER DATA." National Research Council. 2004. Statistical Analysis of Massive Data Streams: Proceedings of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/11098.
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Page 53

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GLOBAL AND REGIONAL SURFACE WIND FIELD INFERENCES FROM SPACE-BORNE SCATTEROMETER DATA 53 GLOBAL AND REGIONAL SURFACE WIND FIELD INFERENCES FROM SPACE-BORNE SCATTEROMETER DATA Ralph F.Milliff Colorado Research Associates (CoRA) Division, NorthWest Research Associates (NWRA) Collaborators: L.Mark Berliner (Ohio State University) Christopher K.Wikle (University of Missouri) Doug Nychka (National Center for Atmospheric Research) Tim Hoar (National Center for Atmospheric Research) Jan Morzel (CoRA) The global ocean surface wind field transfers momentum, and modulates the transfers of heat and material properties (e.g. fresh water, CO2, etc.), between atmosphere and ocean. Momentum inputs create and sustain the wind- driven general circulation of the ocean, and heat and fresh water exchanges drive the thermohaline general circulation; both of which have important implications for Earth climate. On regional scales, the surface wind field is an indicator of synoptic variability affecting weather forecasts. The surface wind vector field over the ocean has been observed by active scatterometer systems in space with increasing precision, coverage, and resolution since 1978. Table 1 indicates characteristics of past, existing, and planned scatterometer missions since sustained earth observing missions began in 1991. In scatterometry, radar pulses of known frequency and polarizations are directed at the ocean surface where they are scattered by capillary waves. The space-borne sensor detects the backscatter signal, from several different geometries (e.g. look, azimuth, and incidence angles) and across two polarizations, to return a normalized radar backscatter cross section, or σo. The σo are spatially averaged within so-called wind vector cells (WVC) that form an array spanning the satellite ground track along its orbit. For each WVC, a geophysical model function is fit to relate averaged σo to wind speed and direction. The NASA QuikSCAT (QSCAT) satellite bears the first SeaWinds scatterometer instrument. The WVC are ordered at 25 km resolution across an 1800 km swath, along a polar orbit that is declined 8º. Roughly 1,000,000 surface wind vectors are retrieved over the global ocean in about 14 orbits every 24 hr by QSCAT. A second SeaWinds instrument is planned for launch aboard the ADEOS-2 satellite of the Japanese Space Agency (NASDA) on

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Massive data streams, large quantities of data that arrive continuously, are becoming increasingly commonplace in many areas of science and technology. Consequently development of analytical methods for such streams is of growing importance. To address this issue, the National Security Agency asked the NRC to hold a workshop to explore methods for analysis of streams of data so as to stimulate progress in the field. This report presents the results of that workshop. It provides presentations that focused on five different research areas where massive data streams are present: atmospheric and meteorological data; high-energy physics; integrated data systems; network traffic; and mining commercial data streams. The goals of the report are to improve communication among researchers in the field and to increase relevant statistical science activity.

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