Ultra-High Resolution ASCAT Products & Progress in Simultaneous Wind/Rain Retrieval
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1 Ultra-High Resolution ASCAT Products & Progress in Simultaneous Wind/Rain Retrieval David G. Long Brigham Young University Ocean Vector Wind Science Team Meeting May 2010
2 Introduction σ 0 imaging SIR/AVE optimized for ASCAT Beta version of ASCAT enhanced resolution land/ice products now available at the Scatterometer Climate Record Pathfinder ( Wind Ultra-high resolution (UHR) (1.25 km/pixel) ASCAT wind processing now operational Simultaneous wind/rain (SWR) retrieval Bayes estimator selection to optimally select between windonly, SWR, and rain-only retrieval Rain flag and correction Conventional Resolution SIR Enhanced Resolution Conventional Resolution Ultra-High Resolution db
3 ASCAT Resolution Enhancement ASCAT SZF comparable to QuikSCAT L1B slices Reconstruction to enhance resolution Single pass for winds Multipass for land/ice SZF slice spatial response function derived with aid of Julian Wilson 6 db spatial response ASCAT SZF slices QuikSCAT slices Adapt NSCAT version of SIR to deal with incidence angle Two images: σ 0 at 40º (A) and incidence angle slope (B) SIR algorithm tuned for ASCAT ASCAT slice response function
4 ASCAT Enhanced Resolution Land/Ice Images Images on standard grids Aids in comparison and data fusion with other sensors Resolution enhanced products: AVE, SIR, none (gridded) AVE and SIR enable higher spatial resolution Support studies otherwise not possible Standard incidence angle Trade noise, spatial and temporal resolution Combine multiple passes Separate single pass, local time-of-day, daily, multi-day products Longer integrations improve spatial resolution, reduce noise Smooth temporal change Local time-of-day products provide high temporal resolution while combining multiple passes in the polar regions Image data now available from the Scatterometer Climate Pathfinder
5 ASCAT & QuikSCAT Comparison V-pol A Images ASCAT Slice (SZF) GHz σ 0 at 40º km pixels QuikSCAT Slice 13.4 GHz σ 0 at 54º JD 214, 2008
6 Deepwater Horizon Oil Spill Enhanced Resolution ASCAT Observations Spill alters wave spectrum, visible in enhanced resolution sigma-0 images land Oil spill Potential confusion with low wind speed regions JD 117, 2010, two days after leak begins
7 Deepwater Horizon Oil Spill Enhanced Resolution ASCAT Observations Spill alters wave spectrum, visible in enhanced resolution sigma-0 images land Oil spill Potential confusion with low wind speed regions JD 118, 2010
8 Deepwater Horizon Oil Spill Enhanced Resolution ASCAT Observations Spill alters wave spectrum, visible in enhanced resolution sigma-0 images Oil spill JD 119, 2010
9 Deepwater Horizon Oil Spill Enhanced Resolution ASCAT Observations Spill alters wave spectrum, visible in enhanced resolution sigma-0 images land Oil spill JD 120, 2010
10 Deepwater Horizon Oil Spill Enhanced Resolution ASCAT Observations Spill alters wave spectrum, visible in enhanced resolution sigma-0 images Oil spill JD 122, 2010
11 Deepwater Horizon Oil Spill Enhanced Resolution ASCAT Observations Spill alters wave spectrum, visible in enhanced resolution sigma-0 images Oil spill Potential confusion with low wind speed regions JD 124, 2010
12 Deepwater Horizon Oil Spill Enhanced Resolution ASCAT Observations Spill alters wave spectrum, visible in enhanced resolution sigma-0 images Oil spill Potential confusion with low wind speed regions JD 127, 2010
13 Deepwater Horizon Oil Spill Enhanced Resolution ASCAT Observations Spill alters wave spectrum, visible in enhanced resolution sigma-0 images Oil spill JD 131, 2010
14 Deepwater Horizon Oil Spill Enhanced Resolution ASCAT Observations Spill alters wave spectrum, visible in enhanced resolution sigma-0 images land Oil spill JD 132, 2010
15 Enhanced Resolution ASCAT & QuikSCAT Enhanced resolution false color image using a single day (JD 217, 2008) of data from Ku-band QuikSCAT and C-band ASCAT. Red: QuikSCAT h-pol σ o at 46º Green: QuikSCAT v-pol σ o at 45º Blue: ASCAT v-pol σ o at 40º Open ocean is blue/green. Dark purple is young first year sea ice. Older first year and multi-year sea ice are yellow/gold. Glacial ice that has melted/refrozen is white, with unmodified firn showing as browns and golds. Icebergs show up a as white. Dual-frequency offers more discrimination capability than single frequency
16 UHR ASCAT Wind Retrieval Single-pass processing of ASCAT data enables production of ultrahigh-resolution (UHR) winds AVE enhanced resolution sigma-0 fields are generated separately for each flavor (fore / mid / aft) Winds are retrieved for each UHR pixel using KNMI algorithm Fine scale wind features visible 1.25 km/pixel WVCs Effective resolution lower, estimated to be ~10-12 km Ambiguity selection: closest to EPS 12.5 km winds Improved UHR selection algorithms in development, as is ASCAT UHR SWR ASCAT UHR wind much less noisier than QuikSCAT UHR winds Effective resolution of ASCAT UHR coarser than QuikSCAT UHR Postage stamp processing similar to QuikSCAT UHR Postage stamp processing for NOAA invest areas and named storms Code now being installed at NOAA/NESDIS Sample results below
17 ASCAT UHR Hurricane Observation Example Parma (rev 15334, 23 Oct 2009)
18 ASCAT UHR Hurricane Observation Example Nvida (rev 16094, 25 Nov :00)
19 QuikSCAT* Simultaneous Wind/Rain Retrieval Rain affects 4 to 10% of observations Several estimators Wind-only (W-O) (conventional wind retrieval) Good wind performance Severe bias during rain Simultaneous Wind-Rain (SWR) Noisy in non-raining cases Good during low to moderate wind and rain Rain-only (R-O) Good during high to extreme rain with low wind How can we optimally choose which estimator to use when true conditions are unknown? Ideal choice: Chose estimator with minimum squared error, e.g. Cramer-Rao lower bound (CRB) Bayes algorithm for regime selection developed (paper in review) *This also applies to ASCAT which is also sensitive to rain. ASCA can retrieve rain using simultaneous wind/rain retrieval, see C. Nie and D.G. Long, A C-Band Scatterometer Simultaneous Wind/Rain Retrieval Method, IEEE Transactions on Geoscience and Remote Sensing, Vol. 46, No. 11, pp , 2008.
20 W-O Speed CRB Cramer-Rao bound for various estimators Rain Rate SWR Rain CRB Estimator Selection Regimes (Minimum CRB) R-O SWR SWR Speed CRB R-O Rain CRB Wind Speed W-O Using Monte Carlo simulation, best estimator (which has the smallest error for a given wind and rain) is mapped above
21 QuikSCAT UHR Case Study QuikSCAT W-O speed Wind and rain estimates from each retrieval algorithm (estimator) QuikSCAT SWR speed m/s QuikSCAT R-O rain Now choose one estimator True TRMM PR Rain QuikSCAT SWR rain db km-mm/hr QuikSCAT/TRMM-PR collocated with 5 mins
22 *rain-only selection results in no-speed Case Study Estimator Selections Ideal selector R-O Ideal selection based on TRMM-PR rain QuikSCAT Bayes speed* SWR Bayes algorithm for selection based on QuikSCAT measurements a new type of rain impact flag m/s W-O QuikSCAT estimate selector True TRMM PR Rain QuikSCAT Bayes rain db km-mm/hr
23 Global Overall Wind Performance (averaged over hundred s of QuikSCAT/TRMM-PR collocations Conventional wind retrieval Conventional wind retrieval Bayes estimator selection* Bayes estimator selection* Bayes estimator selection (between W-O, SWR, R-O) has reduced error compared to conventional wind-only retrieval Substantially reduced bias Smaller RMS error * rain-only retrieval results in discarding of high error winds
24 Summary Enhanced resolution processing effective for ASCAT High resolution land/ice SZF-based images now available from the Scatterometer Climate Record Pathfinder web/ftp site ASCAT Ultra-High-Resolution (UHR) wind products now going operational at NOAA/NESDIS In time for 2010 hurricane season Custom postage stamp regions available on demand Validation of QuikSCAT Bayes estimator selection between wind-only (conventional), simultaneous wind/rain, and rain-only retrieval An effective rain impact flag Papers in review
25 Greenland Dual Frequency Scatterometry Single day (JD 217, 2008) false color enhanced resolution image of Greenland from QuikSCAT and ASCAT Red: QuikSCAT h-pol Green: QuikSCAT v-pol Blue: ASCAT v-pol Purple corresponds to land. Summer melt on the ice sheet periphery is the darker region between the white and purple regions. Refrozen melt-zone is bright white. Unmelted firn in central Greenland is brown and gold (Texturing in the lower left portion of the melt zone is an artifact of the diurnal melt cycle due to using passes at different times of the day) Combined, the two scatterometers offer more discrimination capability than either alone
26 Backup Slides
27 Linear model for sigma-0 vs incidence angle Model appropriate for regions with no azimuth anisotropy Amazon Rain Forest Example
28 Backscatter Anisotropy Due to sastrugi and topography, some polar regions exhibit anisotropic backscatter response - Corrections methods have been developed and will be applied to Scatterometer Climate Record Pathfinder images Wilkes Land Example
29 ASCAT Local Time-of-Day Images ASCAT observes the poles many times each day Local time of each pass varies in one of two general times Multiple measurements combined to make images Diurnal features are averaged together, leading to loss in temporal resolution Solution: combine only measurements from similar local-time-of-day Local Time [min] = UTC [min] + 4 [min/deg] x longitude [deg] Two images each 24 hour period Optionally combine several days separately for each local time of day Histogram of time of measurements in the polar regions
30 All-Day Images
31 Morning LTOD Images
32 Evening LTOD Images
33 2 Day LTOD Images
34 Full SZF data Incidence Angle Trimming SZR (25 km egg ) data incidence angles: Center beams restricted to Applied same restriction to SZF (slice) data (Raw data covers broader incidence angle range) Trimmed incidence angles JD 214, 2008
35 Tuning SIR for ASCAT SZF Simulation used to select optimum SIR algorithm parameters Number of iterations N its = 35 (slices) Initial values A init = -15 db B init = db/deg B weighting B weight = 50 Incidence angle clipping Fore/aft: Mid: Median filtering optional
36 ASCAT & QuikSCAT Comparison A Images of the Amazon (sigma-0 in db) QuikSCAT h-pol QuikSCAT v-pol ASCAT SIR Gridded single day of data
37 ASCAT UHR Hurricane Observation Example Melor (rev 15348, 24 Oct 2009)
38 Case Study Rain Comparison Ideal Selection** Rain Rate Selected Estimates* * SWR rain estimates less than 1.5 km-mm/hr (light mist) are discarded to reduce noise Wind Speed ** Over TRMM-PR swath
39 QuikSCAT Speed Raining versus non-raining Overall Wind Performance (averaged over hundred s of QuikSCAT/TRMM-PR collocations) Wind-Only Raining NCEP Speed Wind-Only Non-Raining Bayes Raining Bayes Non-Raining SWR Raining SWR Non-Raining
40 Resolution Enhancement The spatial response function and sampling define the effective resolution exploited by SIR reconstruction Spatial overlap required AVE response is the weighted average of measurement responses covering each pixel First iteration of the SIR algorithm Combined response 3 db contour shown in black AVE Response Fore Aft Individual measurement spatial responses = product of antenna pattern and Doppler/range filtering
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