DocumentCode
2262814
Title
A multidimensional histogram rain-flagging technique for SeaWinds on QuikSCAT
Author
Huddleston, James N. ; Stiles, Bryan W.
Author_Institution
Jet Propulsion Lab., California Inst. of Technol., Pasadena, CA, USA
Volume
3
fYear
2000
fDate
2000
Firstpage
1232
Abstract
The SeaWinds scatterometer was developed by NASA JPL to measure the speed and direction of global ocean surface winds. SeaWinds was launched aboard the QuikSCAT spacecraft on June 19, 1999 and has continued to operate successfully since being turned on. Although the initial SeaWinds wind vector products were of excellent quality, they were occasionally degraded by the presence of rain. It soon became obvious that a way to flag wind vector cells for rain contamination was needed. The authors have determined a set of parameters that are sensitive to rain and are computed from the scatterometer measurements. These parameters are: (1) the retrieved wind speed, (2) the retrieved wind direction relative to the satellite ground track, (3) the normalized beam difference, which indicates a statistically significant imbalance in the beams relative to the geophysical model function, (4) the maximum likelihood estimate calculated by the wind retrieval algorithm, and (5) the radiometric brightness temperature. Using these parameters and external rain information (SSM/I) an estimate of the conditional probability of rain given the parameters is developed using a multidimensional histogram technique. This probability estimate is then used to flag rain contaminated wind vector cells using only scatterometer data. This technique is currently employed to generate a rain flag for SeaWinds on QuikSCAT data. In this paper, the effects of rain on SeaWinds data are explored, the rain flagging technique is explained, and the performance of the rain flag is illustrated using a number of metrics
Keywords
atmospheric techniques; meteorological radar; remote sensing by radar; spaceborne radar; wind; QuikSCAT; SeaWinds; atmosphere; geophysical model function; maximum likelihood estimate; measurement technique; meteorological radar; multidimensional histogram; radar remote sensing; radar scatterometry; rain; rain contaminated wind vector cell; rain flag; rain-flagging; retrieval algorithm; spaceborne radar; wind; Geophysical measurements; Geophysics computing; Histograms; Multidimensional systems; NASA; Pollution measurement; Radar measurements; Rain; Sea measurements; Spaceborne radar;
fLanguage
English
Publisher
ieee
Conference_Titel
Geoscience and Remote Sensing Symposium, 2000. Proceedings. IGARSS 2000. IEEE 2000 International
Conference_Location
Honolulu, HI
Print_ISBN
0-7803-6359-0
Type
conf
DOI
10.1109/IGARSS.2000.858077
Filename
858077
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