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- W4285151640 abstract "The airborne Stepped Frequency Microwave Radiometer (SFMR) provides measurements of 10-m ocean-surface wind speed in high and extreme wind conditions. These winds are calibrated using the surface-adjusted wind estimates from the so-called dropsondes. The surface-adjusted winds are obtained from layer-averaged winds scaled to 10-m altitude to eliminate the local surface variability not associated with the storm strength. The SFMR measurements and, consequently, the surface-adjusted dropsonde winds represent a possible reference for satellite instrument and model calibration/validation at high and extreme wind conditions. To this end, representativeness errors that those measurements may introduce need to be taken into account to ensure that the storm variability is correctly resolved in satellite retrievals and modelling. In this work, we compare the SFMR winds with the dropsonde surface-adjusted winds derived from the so-called WL150 algorithm, which uses the lowest 150-meter layer between 10 m to 350 m. We use nine years of data from 2009 to 2017. We focus on the effects of the layer altitude and thickness. Our analysis shows that the layer altitude has a significant impact on dropsonde/SFMR wind comparisons. Moreover, the averaged winds obtained from layers thinner than the nominal 150 m and closer to the surface are more representative of the SFMR surface wind speed than the WL150 speeds. We also find that the surface-adjusted winds are more representative of 10-km horizontally averaged SFMR winds. We conclude that for calibration/validation purposes, the WL150 algorithm can introduce noise and the use of actual 10-m dropsonde measurements should be further investigated." @default.
- W4285151640 created "2022-07-14" @default.
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- W4285151640 date "2022-01-01" @default.
- W4285151640 modified "2023-09-27" @default.
- W4285151640 title "On Dropsonde Surface-Adjusted Winds and Their Use for the Stepped Frequency Microwave Radiometer Wind Speed Calibration" @default.
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- W4285151640 doi "https://doi.org/10.1109/tgrs.2022.3189310" @default.
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