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The radar backscatter from a nadir-pointing radar is related to the wind speed and is directly proportional to the normal incidence Fresnel power reflection coefficient and inversely proportional to the mean square slope of the low pass filtered version of the ocean surface [Brown, 1978]. Using an algorithm, radar cross section can be converted to wind speed. There are two wind speed fields on this disc, one computed using the Chelton-Wentz algorithm [Chelton and Wentz, 1986] and one using the Smoothed Brown algorithm [Goldhirsh and Dobson, 1985]. The data on this disc were extracted to form the larger Geosat data set in 1988, and at that time these were the two algorithms chosen to compute wind speed. In terms of rms (root mean square) accuracy, the Smoothed Brown is slightly more accurate but has the drawback that it should not be used for wind speeds greater than 14 m/s.
Since 1988 several additional algorithms have been proposed. Appendix B gives three of these algorithms which can easily be used to compute wind speed when using the radar cross section values contained herein. A bibliography is included in Appendix A, and the reader is encouraged to read some of the pertinent papers for further clarification of the differences of these algorithms. A general review can be found in Dobson . The general accuracy of wind speed measurements from Geosat is 1.8 m/s.
Significant wave height (SWH) data on this disc were derived from an algorithm used onboard the spacecraft during the Geosat mission. The SWH is related to the slope of the returned radar pulse. When there are waves present on the ocean, the surface appears rough causing the leading edge of the pulse to intersect the wave crests before the troughs, which results in a broadening of the pulse shape. As the distribution of wave heights broadens, so does the returned pulse shape. Thus from this knowledge, an algorithm was developed relating the pulse slope to SWH. SWH is defined to be that wave height for which there is a 33 percent probability of waves higher than that value. In addition, if the probability density of wave amplitudes is assumed to be a Rayleigh distribution, then it can be shown that SWH is 4 times the standard deviation of the surface waves [Borgman, 1982]. In the last few years several papers have been published that indicate the onboard SWH algorithm underestimates SWH [Mognard et al., 1991; Carter et al., 1992; Glazman, 1991]. The user may want to consult these publications before using the SWH data. A bibliography has been included which contains these three papers and many others that have used Geosat SWH and wind measurements.
Where: DDD is the year day , 001-365; and YY is the year, 85 or 86.
The table below gives the format for the integer binary data records, which have a record length of 26 bytes.
|1||1-4||Geodetic Latitude in microdegrees|
|2||5-8||East Longitude in microdegrees|
|3||9-12||Time in seconds from 1985.000...|
|4||13-14||Time continued in units of .1 milliseconds|
|5||15-16||Significant Wave Height in centimeters|
|6||17-18||Radar Cross Section (Sigma Naught) in .01 db|
|7||19-20||Attitude Angle in .01 degrees|
|9||23-24||Chelton-Wentz Wind, cm/sec (divided by 1.06)|
|10||25-26||Smoothed Brown Wind, cm/sec|
Also included on this CD-ROM is a C-program named WW_SWAB.C. For VAX and PC users, whose computers use "little-endian" byte order, this program will convert the "big-endian" data on this CD to the format used by their machines. This program should be uploaded to their computer and compiled with a command line such as: "cc -O -s -o ww_swab ww_swab.c". The program acts like a Unix "filter", reading from standard in and writing to standard out. A typical usage would be: "ww_swab < orginal.file > swapped.file".
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Barrick, D. E., A relationship between the slope probability density
Barrick, D. E., Wind Dependence of quasi-specular micrplsqlve sea scatter,
Borgman, L.E., Summary of probability laws for wave properties, Proc.
Brown,G.S., Estimation of Surface wind Speeds Using Satellite-Borne
Cardone, V. J. , J. G. Greenwood, and M. A. Roy, On trends in historical
Carter. D. J. T., P.G. Challenor,and M. A. Srokosz, An assessment of
Chelton, D. B. and P. J. McCabe, A review of satellite altimeter
Chelton,D. B. and Wentz,F. J., Further Development of an improved altimeter
Chelton,D. B., WOCE/NASA altimeter algorithm workshop, U. S. WOCE Tech.
Dobson, E. B.,F. Monaldo, J. Goldhirsh, J. Wilkerson,'Validation of Geosat
Dobson, E. B., Geosat altimeter wind speed and waveheight measure
Dobson, E.B., Wind Speed from Altimeters - A Review, JHU/APL S1R-93U-024,1993.
Glazman, R. E. and Pilorz, Effects of sea maturity on satellite altimeter
Glazman, R. E., Statistical problems of wind generated gravity waves arising
Glazman, R. E. and A. Greysukh, Satellite altimeter measurements of surface
Goldhirsh, J. and E. B. Dobson, A recommended algorithm for the determination
Jackson, F.C, W. T. Walton, D. E. Hines, B. A. Walter, C. Y. Peng, Sea
Mognard, N. M. and B. Lago, The computation of wind speed and wave height
Mognard, N. M., J. A. Johannessen, C. E. Livingstone, D. Lyzenga,
Monaldo, F. Expected differences between buoy and radar altimeter
Tournadre,J, and R. Ezraty, Local climatology of wind and sea state by
Townsend, W. F., An initial assessment of the performance acheived by the
Ulaby, F. T., R.K. Moore, A. D. Fung, Micrplsqlve Remote Sensing - Active and
Wentz, F. J., L. A. Mattox, and S. Peteherych, New algorithms for micrplsqlve
Radar Cross Section = -4.0 - 10(logbase10[0.009 + 0.012 ln U(sub10)])Where U(sub10) = U sub 10 = wind speed at 10 meters above the surface and Radar Cross Section is in decibars.
Note: All algorithms are referenced to 10 meters height above the surface.
|Last modified: Wed, 10-Oct-2007 20:03 UTC||NCEI.firstname.lastname@example.org|
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