Abstract
This study compares wind speeds derived from five satellite microwave radiometers with those directly observed by buoy-mounted anemometers and the global analyses produced by the European Center for Medium-Range Weather Forecasts (ECMWF) model. Buoy comparisons yield wind speed root mean square errors of 0.82 m/s for WindSat, 1.45 m/s for SSMIS F16, 1.39 m/s for SSMIS F17, 1.43 m/s for AMSR-E, and 1.45 m/s for AMSR2. The overall mean bias for each satellite is typically <0.25 m/s when averaged over all selected buoys for a given study time. The satellite wind speeds are underestimated with respect to the buoy observations at a band of the tropical Pacific Ocean from −8°S to 4°N. The mean buoy–satellite difference as a function of year is always <0.4 m/s, except for SSMIS F16. The selected satellite wind speeds show an obvious seasonal characteristic at high latitudes. In comparison with the ECMWF data, some obviously positive differences exist at high southern latitudes in January and at high northern latitudes in July.
Highlights
Passive microwave remote sensing is an important tool for studying atmospheric and oceanographic processes, and it can provide both daytime and nighttime observations of geophysical parameters such as atmospheric water vapor, cloud liquid water, rain rate, sea surface temperature, surface wind speed, and sea surface salinity
A successive dataset of wind speed measurements has been obtained from different spaceborne microwave radiometers, which has been used as an important input for numerical weather forecasting and certain ocean circulation models [18,19]
We focus on five different satellite radiometers: Sensor Microwave Imager/Sounder (SSMIS) F16, SSMIS F17, AMSR-E, Advanced Microwave Scanning Radiometer 2 (AMSR2), and WindSat
Summary
Passive microwave remote sensing is an important tool for studying atmospheric and oceanographic processes, and it can provide both daytime and nighttime observations of geophysical parameters such as atmospheric water vapor, cloud liquid water, rain rate, sea surface temperature, surface wind speed, and sea surface salinity. These satellite measurements offer a much larger area of observation than in situ measurements. A successive dataset of wind speed measurements has been obtained from different spaceborne microwave radiometers, which has been used as an important input for numerical weather forecasting and certain ocean circulation models [18,19]. Accurate estimation of ocean surface winds is important in such applications
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