Abstract
We present and validate a method of reconstructing high-resolution sea surface wind fields from multi-sensor satellite data over the Grand Banks of Newfoundland off Atlantic Canada. Six-hourly ocean wind fields from blended products (including multi-satellite measurements) with 0.25° spatial resolution and 226 RADARSAT-2 synthetic aperture radar (SAR) wind fields with 1-km spatial resolution have been used to reconstruct new six-hourly wind fields with a resolution of 10 km for the period from August 2008 to December 2010, except July 2009 to November 2009. The reconstruction process is based on the heapsort bucket method with topdown search and the modified Gauss–Markov theorem. The result shows that the mean difference between the reconstructed wind speed and buoy-estimated wind speed is smaller than 0.6 m/s, and the standard deviation is smaller than 2.5 m/s. The mean difference in wind direction between reconstructed and buoy estimates is 3.7°; the standard deviation is 40.2°. There is fair agreement between the reconstructed wind vectors and buoy-estimated ones.
Highlights
Measurements of ocean wind vectors serve as a basis for marine weather forecasting and offshore wind farms planning and contribute to the understanding of air-sea interactions and atmospheric dynamics [1,2,3]
The present study aims at developing a method that combines synthetic aperture radar (SAR) and the blended products (BP) wind fields for high-resolution wind fields over the Grand Banks of Newfoundland
BP winds with a temporal resolution of six hours and a spatial resolution of km × 25 km for the selected geographic region have been blended with SAR data to produce reconstructed wind fields in this study
Summary
Measurements of ocean wind vectors serve as a basis for marine weather forecasting and offshore wind farms planning and contribute to the understanding of air-sea interactions and atmospheric dynamics [1,2,3]. Sensors operating at microwave frequencies can make measurements of the ocean surface day and night and under most-weather conditions [4,5] Both active (radar, scatterometer and altimeter) and passive (radiometer) microwave sensors have been shown to be capable of retrieving the ocean surface wind speed [4,6]. The mission goal of the WindSat radiometer on the Coriolis satellite (2003) was to demonstrate that wind measurements from passive microwave emissions can achieve the same accuracy as conventional scatterometry, both in wind speed and wind direction [18]. Whether through active microwave scatterometry or through passive polarimetry, the measurements of the ocean surface wind vector at 25-km resolution from space could be achieved.
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
