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Ocean Vector Winds: BYU Daily Browse Images of SeaWinds Sigma-0 Measurements (D. Long)

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Abstract
Citation

Product 123

Data
(Binary)
Documentation Software FAQs Start Time End Time Temporal
Resolution
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Coverage
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table 123
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FTP
BROWSE
HEFT

Data Set Guide

All Software N/A 10Apr2003 24Oct2003 Daily 22.5km Global


Abstract
ab123

Source/sensor: SeaWinds on ADEOS-II (Midori-II)

Coverage: 10 April 2003 to 24 October 2003, global

Abstract:
The SeaWinds on ADEOS-II (Midori-II) scatterometer provides normalized radar cross section (sigma0) measurements of the Earth's surface. Typically, products such as PO.DAAC products 108 and 109 convert the sigma0s to wind measurements. However, scatterometers have also proven useful in a variety of land and ice studies. This product consists of browse images made directly from the sigma0s to aid in the selection of regions and time periods for study.

The processing for this product is the same as for PO.DAAC Product 121, BYU Daily Browse Images of QuikSCAT Sigma-0 Measurements (D. Long) except that the raw sigma0s come from SeaWinds on ADEOS-II instead of SeaWinds on QuikSCAT.

For each day, this dataset has 1 sigma0 browse image for each combination of

  • 3 regions: global, north, and south
  • 2 polarizations: horizontal and vertical
  • 3 image types: average, standard deviation, and count

Regions: all global images (6 per day) are rectangular lat/lon grids covering the entire globe with a resolution of 5 pixels/deg, or about 22.5 km/pixel at the equator. They well suit mid-latitude regions but distort polar regions. The two sets of hemispheric products well suit the high-latitude regions. Those images are polar stereographic projections using a 70° reference latitude with a nominal grid size of about 22.5 km. The polar views include only measurements above a high latitude cutoff of 52°.

Polarizations: SeaWinds measures the sigma0s at both vertical and horizontal polarization. Since it is undesirable to combine measurements from different polarizations, measurements for each are kept separate.

Image Types: the average sigma0s are temporal averages over a one-day period of all the sigma0 measurements whose centers fall within each image pixel area. These are the most useful of the three image types. The standard deviation images are the normalized standard deviation of the measurements hitting each pixel divided by the mean value. The count images are the number of measurements.

Data Set Volume: There are 18 data files per day:
SIR Files Size (in bytes)
region image type polarization uncompressed compressed
global average sigma0 horizontal 3240960 ~2500000
vertical 3240960 ~2700000
count horizontal 3240960 ~700000
vertical 3240960 ~800000
standard deviation horizontal 3240960 ~1900000
vertical 3240960 ~2000000
north average sigma0 horizontal 302080 ~200000
vertical 302080 ~200000
count horizontal 302080 ~80000
vertical 302080 ~80000
standard deviation horizontal 302080 ~150000
vertical 302080 ~150000
south average sigma0 horizontal 302080 ~210000
vertical 302080 ~210000
count horizontal 302080 ~80000
vertical 302080 ~80000
standard deviation horizontal 302080 ~160000
vertical 302080 ~150000
total per day 23070720 ~10800000

Smallest order: One average sigma0 file via FTP.

Standard Product: FTP

Data Format: SIR

Media Format: These data are available via anonymous FTP to podaac.jpl.nasa.gov, directory /pub/ocean_wind/seawinds/sigma0browse, or on DVD


Citation
ci123

References:

  • Ashcraft, I.S. and D.G. Long, 2000. SeaWinds Views Greenland, Proc. Int. Geosci. Rem. Sens. Sym., Honolulu, Hawaii, 6-10 July 2000

  • Dunbar, R.S. et al, October 2003. SeaWinds Science Data Product User's Manual, Version 1.1, JPL Document D-21551, Jet Propulsion Laboratory, Pasadena, CA.

  • Huddleston, J.N. and B.W. Stiles, 2000. Multidimensional Histogram (MUDH) Rain Flag Product Description, Version 2.1, Jet Propulsion Laboratory, Pasadena, CA.

  • Long, D.G., 2000. A QuikSCAT/SeaWinds Sigma-0 Browse Product, Version 2.0, Brigham Young University, Provo, UT.

  • Long, D.G. and M.R. Drinkwater, 1999. Cryosphere Applications of NSCAT Data, IEEE Trans. on Geoscience and Remote Sensing, Vol. 37, No. 3, pp. 1671-1684

  • Remund, Q.P. and D.G. Long, 2000. Iterative Estimation of Antarctic Sea Ice Extent Using SeaWinds Data, Proc. Int. Geosci. Rem. Sens. Sym., Honolulu, Hawaii, 6-10 July 2000

  • Remund, Q.P. and D.G. Long, 1998. Sea Ice Mapping Algorithm for QuikSCAT and Seawinds, Proc. Int. Geosci. Rem. Sens. Sym., Seattle, Washington, 6-10 July, 1998, pp. 1686-1688.
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