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|Weihs, R. R., & Bourassa, M. A. (2014). Modeled diurnally varying sea surface temperatures and their influence on surface heat fluxes. J. Geophys. Res. Oceans, 119(7), 4101–4123.|
|Weissman, D. E., Apgar, G., Tongue, J. S., & Bourassa, M. A. (2005). Corrections to the SeaWinds scatterometer wind vectors by removing rain effects. Bulletin of the American Meteorological Society, 86, 621–622.|
|Weissman, D. E., & Bourassa, M. A. (2009). The combined effect of surface rain and wind on scatterometer observations of surface roughness. In 2009 IEEE International Geoscience and Remote Sensing Symposium, IEEE, Cape Town, South Africa (I-pp. 108– I-111).|
|Weissman, D. E., & Bourassa, M. A. (2008). Measurements of the Effect of Rain-induced Sea Surface Roughness on the Satellite Scatterometer Radar Cross Section. In XXIX General Assembly of the International Union of Radio Science, Union of Radio Science International (Vol. 4).|
|Weissman, D. E., Bourassa, M. A., & Tongue, J. (1999). Relationship between QuikSCAT wind speed errors and rain rate using simultaneous, collocated NEXRAD data. In Arcadia, CA, USA.|
|Weissman, D. E., & Bourassa, M. A. (2011). The Influence of Rainfall on Scatterometer Backscatter Within Tropical Cyclone Environments-Implications on Parameterization of Sea-Surface Stress. In IEEE Transactions on Geoscience and Remote Sensing (Vol. 49, pp. 4805–4814).|
|Weissman, D. E., & Bourassa, M. A. (2008). Measurements of the Effect of Rain-Induced Sea Surface Roughness on the QuikSCAT Scatterometer Radar Cross Section. IEEE Trans. Geosci. Remote Sensing, 46(10), 2882–2894.|
|Weissman, D. E., Bourassa, M. A., O'Brien, J. J., & Tongue, J. S. (2003). Calibrating the quikscat/seawinds radar for measuring rainrate over the oceans. IEEE Trans. Geosci. Remote Sensing, 41(12), 2814–2820.|
|Weissman, D. E., Bourassa, M. A., & Tongue, J. (2002). Effects of Rain Rate and Wind Magnitude on SeaWinds Scatterometer Wind Speed Errors. J. Atmos. Oceanic Technol., 19(5), 738–746.|
Wentz, F. J., Ricciardulli, L., Rodriguez, E., Stiles, B. W., Bourassa, M. A., Long, D. G., et al. (2017). Evaluating and Extending the Ocean Wind Climate Data Record. IEEE J Sel Top Appl Earth Obs Remote Sens, 10(5), 2165–2185.
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 sigmao measurements include 1) direct Ku-band sigmao 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