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This study explores the empirical rain correction methods for SeaWinds data using AMSR, evaluating their performance and impacts on speed and direction biases.
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SeaWinds Empirical Rain Correction Using AMSR January 17, 2005 Bryan Stiles, Svetla Hristova-Veleva, and Scott Dunbar
Outline • Method Overview • Data set description • Variance computation change in objective function • Rain correction methods • Performance Summary • Metrics • Direction and Speed Histograms of DIRTH vectors • 2-D NCEP/Retrieved Relative Direction Histograms • Cross Track Bias (by liquid and speed) • Speed Bias (by liquid and speed) • RMS Direction Difference (by liquid and speed) • Discussion
Method Overview • The entire SeaWinds mission was processed 3 ways. • Climatological attenuation correction only (SCAT) • Physically based rain correction (PHY) • Empirically based rain correction (EMP) • The objective function was modified for all three cases. • Log(var) term was put in. • Variance was modified so that: • assuming the standard deviation of the backscatter correction b was 50% • noting that measurement noise was multiplied by the attenuation correction a.
Method Overview • PHY • Uses physical models of attenuation and backscatter to compute a and b from AMSR liquid, vapor, SST, and rain rate. • s is the splash ratio as a function of rain rate • EMP • Estimates a and b as function of liquid, vapor, and SST using NCEP winds collocated with SeaWinds 0 values. • To avoid biases due to NCEP errors • Scaled a to match physical liquid=0 values. • Scaled b so that minimum backscatter was 0.
Performance summary • Rain free cases are not affected significantly by the corrections. • Both rain corrections improve speed bias and reduce cross track direction preference. • RMS direction performance is mixed • Nearest RMS direction difference from NCEP is increased by the correction techniques, but that may be explained by: • The number of ambiguities decreases in the corrected cases for liquids over 1 mm. • Selected RMS direction difference has little change • One would expect improvement due to reduced cross track preference. • Lack of improvement may indicate an additional directional noise imparted by the corrections. • DIRTH RMS direction difference is significantly decreased especially for the empirical correction. • DIRTH tends to smooth out directional noise in the corrected winds.
Performance summary (cont) • RMS speed performance • RMS speed differences (not shown) decrease due to speed bias improvement • Speed variance increases; especially for the empirical case.
1-D Direction and Speed Histograms • Plot format • NCEP Histograms were plotted together with the DIRTH vector histograms for each correction method. • Direction and Speed Histograms were computed for varying: • Correction Strategy (line color) • Geographic region (plot in slide) • Liquid Range (slide) • Percentage of Data in each liquid range is noted. • Observations • Corrections tend to match model direction histograms better • Corrections tend to follow model wind speed trends by geographic region • DIRTH creates cardinal direction spikes (investigating …)
2-D Direction Histograms • Two dimensional histograms of retrieved direction and NCEP direction, relative to the s/c flight direction. • Demonstrates the removal of rain-related artifacts [e.g. cross-track directions]. • Histograms were computed for varying • Correction method (slide) • Liquid range (plot in slide) • Choice of DIRTH, Selected, or Nearest (slide) • SCAT-only histograms repeated as the top row of each slide for comparison. • SCAT-only histograms differ for EMP and PHY slightly due to differences in flagging.
Plot Formats • Metrics from here on are: • Plotted as a function of • Liquid (x-axis) (full range or 0-3 mm) • Due to a bug liquids values on the x-axis are 4 times the true values. • NCEP speed (multiple plots in slide) • Correction method (line color, cyan=EMP, red=PHY, black=SCAT, dotted black=SCAT w/o log(var)) • Computed for 200 orbits of SeaWinds data. • Plots for full liquid range and 0-3 mm (99.97% of data) are on separate slides.
Speed Biases • Metric Definition • Selected speed - NCEP speed • Performance Summary • Nearest and DIRTH speed biases (not shown) are similar. • Significant improvement for all but highest wind speeds. • Even heavy rain cases show improvement. • Correction imparts little or no change for rain free data. • Slight change in rain free biases with addition of log(var).
Speed Bias, All Liquids (Liquid x-axis values are 4X true liquid values)
Speed Bias, 1-3 mm(Liquid x-axis values are 4X true liquid values)
Cross Track Direction Bias • Metric Definition • The average amount closer to the cross swath than NCEP in degrees. • Angle between NCEP and cross swath minus the angle between selected and cross swath. • A positive value indicates the cross track direction is preferentially retrieved. • Performance Summary • Corrections reduce rain induced preference for cross swath direction. • Nearest and DIRTH performance is similar to Selected. • Full liquid range and 0-3 mm plots are shown.
Cross Track Bias, All Liquids (Liquid x-axis values are 4X true liquid values)
Cross Track Bias, 1-3 mm(Liquid x-axis values are 4X true liquid values)
RMS Direction Difference • Nearest, Selected, and DIRTH stats are plotted. • Performance Summary • Correction increases Nearest RMS direction difference in rain. • Number of ambiguities are reduced. • Correction noise is added. • Selected direction difference - no change • Correction noise competes with removal of cross track preference. • DIRTH direction difference - improvement with rain correction • Best case DIRTH spatially smooths correction noise. • Worst case DIRTH smooths directional features in rain.
RMS Direction Diff, Nearest (Liquid x-axis values are 4X true liquid values)
Number of Ambiguities (Liquid x-axis values are 4X true liquid values)
RMS, Direction Diff, Selected(Liquid x-axis values are 4X true liquid values)
RMS Direction Diff, DIRTH (Liquid x-axis values are 4X true liquid values)
RMS Dir. Diff, DIRTH, All Liquids(Liquid x-axis values are 4X true liquid values)
Discussion • What further validation is needed? • What can change analysis tell us? • Should change analysis look at: • DIRTH solution performance? • Cross Track Direction Bias? • What can we compare with besides NCEP? Buoys?