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IEEE J Sel Top Appl Earth Obs Remote Sens. 2017 May;10(5):2165-2185. doi: 10.1109/JSTARS.2016.2643641. Epub 2017 May 23.

Evaluating and Extending the Ocean Wind Climate Data Record.

Author information

1
Remote Sensing Systems, Santa Rosa, CA 95401 USA.
2
Jet Propulsion Laboratory, Pasadena, CA 91109 USA.
3
Florida State University, Tallahassee, FL 32306 USA.
4
Brigham Young University, Provo, UT 84062 USA.
5
Cooperative Institute for Marine and Atmospheric Studies, University of Miami, Key Biscayne, FL 33149 USA.
6
Royal Netherlands Meteorological Institute, De Bilt, Netherlands.
7
Oregon State University, Corvallis, OR 97331 USA.
8
Woods Hole Oceanographic Institution, Woods Hole, MA 02543 USA.
9
University of New Hampshire, Durham, NH 03824 USA.

Abstract

Satellite microwave sensors, both active scatterometers and passive radiometers, have been systematically measuring near-surface ocean winds for nearly 40 years, establishing an important legacy in studying and monitoring weather and climate variability. As an aid to such activities, the various wind datasets are being intercalibrated and merged into consistent climate data records (CDRs). The ocean wind CDRs (OW-CDRs) are evaluated by comparisons with ocean buoys and intercomparisons among the different satellite sensors and among the different data providers. Extending the OW-CDR into the future requires exploiting all available datasets, such as OSCAT-2 scheduled to launch in July 2016. Three planned methods of calibrating the OSCAT-2 σo measurements include 1) direct Ku-band σo intercalibration to QuikSCAT and RapidScat; 2) multisensor wind speed intercalibration; and 3) calibration to stable rainforest targets. Unfortunately, RapidScat failed in August 2016 and cannot be used to directly calibrate OSCAT-2. A particular future continuity concern is the absence of scheduled new or continuation radiometer missions capable of measuring wind speed. Specialized model assimilations provide 30-year long high temporal/spatial resolution wind vector grids that composite the satellite wind information from OW-CDRs of multiple satellites viewing the Earth at different local times.

KEYWORDS:

Radar cross section; remote sensing; satellite applications; sea surface; wind

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