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This research evaluates two methods of calculating speed impact for wind speed estimation derived from AMSR data. The study compares the accuracy of speed biases computed from different parameters and proposes a hybrid table to address errors in low and high wind speed estimations. Analysis of discrepancies in NCEP-driven speed biases and the influence of liquid and backscatter errors on wind speed calculations are discussed. The final hybrid table aims to provide a comprehensive solution for enhancing the accuracy of wind speed estimation in atmospheric studies.
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SeaWinds AMSR-derived Impact Table Jan 17, 2006 Bryan Stiles and R. Scott Dunbar
Impact Table Overview • Speed Bias and Cross Track Directional Bias are tabularized by: • Attenuation • Backscatter ratio B/ 0 • Cross Track Distance • Average outer beam measured 0 • Cross track bias is computed for Scatterometer-only DIRTH w.r.t NCEP • Speed Bias is computed similarly below a 0 threshold but is computed directly from A and B above the threshold.
To compute speed impacts at high winds we: • Estimate retrieved wind speed from average measured s0. (using QSCAT1) • An estimate of speed is derived for each beam. • An average value is computed weighted by the number of measurementsfrom each beam. • Estimate true wind speed similarly from s0s corrected using A and B. • Compute the difference between the two speeds. • Accumulate difference for each WVC in SWS mission into bins in speed impact table. • This resulting table is the GMF-derived table.
Why do we compute Speed Impact two different ways? • The two methods agree well for moderate wind speeds (7-15 m/s). • The A, B model of rain impact on s0 was estimated as a function of liquid, vapor, SST, and beam. • To obtain agreement between the A, B model and the NWP speed biases at high winds. • Rain backscatter would have to be a increasing function of wind speed. AND/OR • Attenuation would have to decrease with wind speed. • Because the required changes in A, B seem counterintuitive, we conclude that the NWP speed winds are systematically biased low for cases with high wind speed and high liquid. • This could be explained by rain correlating with small scale high wind regions, poorly represented by low resolution NWP fields. • For this reason we do not want to use NCEP speed impacts for high winds.
At low wind speeds computing speed impact directly from A and B overestimates speed impact. • Why? • Errors in liquid estimate. • Cases of truly high liquid and low measured s0 do not occur. • Some bins in impact table are populated solely by the high end of the liquid error distribution. • Errors in backscatter, B, estimate • For very low winds where rain-free s0< -25 dB, B estimates cannot meet the required precision to correct the speeds well. • Solution? • New table using NCEP-derived impact for average outer beam measured s0 < 0.021. • O.021 is the 99.9 percentile of the B value.
Speed impact as originally derived by SWS-NWPHigh wind biases are wrong due to NCEP error
Speed Biases Computed from A and BLow wind biases are wrong due to errors in liquid and B
