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GERB-2 GEO 22/11/05 J. Hanafin Using IDL coastline information as independent check on L15 and L2 Geolocations Only SW and SWF day time radiances used.

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Presentation on theme: "GERB-2 GEO 22/11/05 J. Hanafin Using IDL coastline information as independent check on L15 and L2 Geolocations Only SW and SWF day time radiances used."— Presentation transcript:

1 GERB-2 GEO 22/11/05 J. Hanafin Using IDL coastline information as independent check on L15 and L2 Geolocations Only SW and SWF day time radiances used

2 Data Used the sum of 2 normalised data arrays to identify pixels with largest SW radiance gradients (  SW): North-South pix-pix SW radiance gradient (SWRad row(n-1) - SWRad row(n+1) ) (SWRad row(n-1) + SWRad row(n+1) ) East-West pix-pix SW radiance gradient (SWRad col(n-1) - SWRad col(n+1) ) (SWRad col(n-1) + SWRad col(n+1) )

3 Sample  SW over Libyan coastline

4 Shifting coastlines Retrieved IDL coast data within each GERB grid pixel Defined land, sea and coastal pixel mask Shifted mask relative to data arrays by -1, -0.5, 0, 0.5, 1 pixels in both directions: 25 different instances Stored mean and std dev of SW radiance gradient for each type of surface for each pixel shift

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6 Pixel shifts N S EW

7 Rank each pixel shift according to it’s quality of fit relative to the other pixel shifts: Maximise: Coastal mean and std dev: = 100*(  SW – min) (max – min) Minimise Land/sea mean and std dev: =100*(1 – (  SW – min)) (max – min)

8 Pixel shifts 13 and 14 score equally highly: 13: 0 N-S, 0 E-W 14: 0 N-S, 0.5 E

9 Results so far… Method good to checking GEO +/- 0.2 GERB pixel –Sensitivity was tested using L15N V001 and Vttt data (pre-reprocessing version). Method useful for checking diurnal/spatial patterns of GEO –No obvious diurnal patterns in limited amount of L15 GEO looked at so far –L2 ‘jumps’ seem to be fixed in V999.

10 L15/L2 ARG comparison V001 v V999 L15 ARG (with L2 cloud mask) V002 v V999 L2 ARG June/July/Dec 2004 Chose 8 regions around Africa/Med. Sea Analyzed times when regions were cloud- free: cloudy pixel = cloud cover > 20% –times when a region had more than 10% of cloudy pixels were excluded –cloudy pixels were excluded from analysis of scenes with less than 10% cloudy pixels

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12 L15/L2 V001/V999 comparisons Calculated  SW for each cloud-free instance of all 8 regions over June, July and Dec 2004 Used 2 pixel shift grids: –Low-res: 1.5, -1, -0.5, 0, 0.5, 1, 1.5 pixels –High-res: -0.6, -0.4, -0.2, 0, 0.2, 0.4, 0.6 pixels Calculated daily mean ‘quality of fit’ for each region

13 L2 V001L2 V999

14 L15 06/07 L15 L2 VersionV001V999 V002V999 Pix shift Spain/ Morocco 0.5 S0.5 E0.2 E0.5 S00.2 N S. Medit0.5 S0.5 E0.2 E, 0.2 S 0.5 S00 N. Medit0.5 S00.2 E0.5 S00 NW Africa0.5 S00.2 S0.5 S00 Red Sea0.5 S00.2 S0.5 S00 SW Africa0.5 S0.5 E0.2 E, 0.2 S 0.5 S00 S Africa0.5 S00.2 E0.5 S00.2 N, 0.2 E Summary of results of cloud-free coastline comparison

15 Effect of GEO on SW radiances Remapped filtered SW radiance image based on RGP GEO. Calculated minimum distance between GGSPS Reproc and RGP Reproc GEO for each pixel Replaced SW radiance of that pixel with that of the pixel closest to the RGP GEO location

16 Comparing GGSPS with different RGP GEO versions

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18 realtimereproc_ 2 reproc_ 5 reproc_ 10 reproc_ 15 reproc_ 20 reproc_ 30 opti (km) (Wm-2) (% pixels >2%)


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