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Ocean Surface Wind Speed Retrieval From the RADARSAT Constellation Mission Co- and Cross-Polarization Images Without Wind Direction Input.
- Source :
- IEEE Transactions on Geoscience & Remote Sensing; Mar2022, Vol. 60, p1-15, 15p
- Publication Year :
- 2022
-
Abstract
- New techniques for automated retrieval of ocean surface wind speed from the RADARSAT Constellation mission (RCM) without input wind direction have been developed and tested. We collected a large number of collocated and coincided ocean buoy wind measurements and RCM co- and cross-polarization observations acquired over the West and East coasts of Canada from February 1, 2020 to July 25, 2021: 1190 data points for RCM ScanSAR 50 m (SC50M) VV–VH, 3819 points for SC50M HH–HV, and 397 points for ScanSAR Low Noise (SCLN) HH–HV images. The observations captured a wide range of wind conditions with the maximum wind speeds of 22.3, 23.8, and 19.7 m/s for SC50M VV–VH, SC50M HH–HV, and SCLN HH–HV, respectively. For these three types of RCM data, the ocean surface wind speed was modeled as a function of the co-polarization (VV or HH) and cross-polarization backscatter (VH or HV) as well as the noise floor and the incidence angle. The models were tested on completely independent subsets of data, and their performance was compared against CMOD5.N (for VV) and CMODH (for HH) models which require input wind direction. The root-mean square errors (RMSEs) for the proposed models in the testing subsets are 1.20, 1.52, and 1.26 m/s, while CMOD models showed 1.37, 1.91, and 3.06 m/s for SC50M VV–VH, SC50M HH–HV, and SCLN HH–HV, respectively. The proposed models are being integrated in various Environment and Climate Change Canada applications including ice and wind data assimilation systems and the National SAR Winds program. [ABSTRACT FROM AUTHOR]
- Subjects :
- WIND speed
RADARSAT satellites
OCEAN
WIND measurement
SYNTHETIC aperture radar
Subjects
Details
- Language :
- English
- ISSN :
- 01962892
- Volume :
- 60
- Database :
- Complementary Index
- Journal :
- IEEE Transactions on Geoscience & Remote Sensing
- Publication Type :
- Academic Journal
- Accession number :
- 156372236
- Full Text :
- https://doi.org/10.1109/TGRS.2021.3137127