期刊论文详细信息
Sensors
Assessment and Analysis of QuikSCAT Vector Wind Products for the Gulf of Mexico: A Long-Term and Hurricane Analysis
Neha Sharma1 
[1] id="af1-sensors-08-01927">Louisiana State University, Department of Oceanography and Coastal Sciences, Coastal Studies Institute, LA 70803, U
关键词: coastal ocean wind;    hurricane;    scatterometer;    SeaWinds;   
DOI  :  10.3390/s8031927
来源: mdpi
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【 摘 要 】

The northern Gulf of Mexico is a region that has been frequently impacted in recent years by natural disasters such as hurricanes. The use of remote sensing data such as winds from NASA's QuikSCAT satellite sensor would be useful for emergency preparedness during such events. In this study, the performance of QuikSCAT products, including JPL's latest Level 2B (L2B) 12.5 km swath winds, were evaluated with respect to buoy-measured winds in the Gulf of Mexico for the period January 2005 to February 2007. Regression analyses indicated better accuracy of QuikSCAT's L2B DIRTH, 12.5 km than the Level 3 (L3), 25 km wind product. QuikSCAT wind data were compared directly with buoy data keeping a maximum time interval of 20 min and spatial interval of 0.1° (≈10 km). R2 values for moderate wind speeds were 0.88 and 0.93 for L2B, and 0.75 and 0.89 for L3 for speed and direction, respectively. QuikSCAT wind comparisons for buoys located offshore were better than those located near the coast. Hurricanes that took place during 2002-06 were studied individually to obtain regressions of QuikSCAT versus buoys for those events. Results show QuikSCAT's L2B DIRTH wind product compared well with buoys during hurricanes up to the limit of buoy measurements. Comparisons with the National Hurricane Center (NHC) best track analyses indicated QuikSCAT winds to be lower than those obtained by NHC, possibly due to rain contamination, while buoy measurements appeared to be constrained at high wind speeds. This study has confirmed good agreement of the new QuikSCAT L2B product with buoy measurements and further suggests its potential use during extreme weather conditions in the Gulf of Mexico.

【 授权许可】

Unknown   
© 2008 by MDPI

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