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OSI-SAF VIIRS SST Pierre Le Borgne, Gérard Legendre, Anne Marsouin, Sonia Péré, Hervé Roquet Centre de Météorologie Spatiale, Météo-France, Lannion, France With contribution of Alexander Ignatov, NOAA
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SPIE Defense, Security and Sensing, Baltimore, 29 April-3 May 2013 2 Outline Objectives Operational chain overview and status Quality Level definition Algorithm determination Validation results Conclusions
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SPIE Defense, Security and Sensing, Baltimore, 29 April-3 May 2013 3 Objectives CMS is commited to produce SST over the NAR area for the EUMETSAT/OSISAF We aim to start delivering operational L3C products (GDSV2.0 compliant in netcdf 4) in mid 2013 The VIIRS SST chain will be a test chain for our next operational METOP/AVHRR SST chain
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SPIE Defense, Security and Sensing, Baltimore, 29 April-3 May 2013 4 The OSI SAF VIIRS SST chain overview Experimental OE SST Radiometric data Maia cloud mask Cloud mask control No masking! Multispectral SST calculations Granule workfile Algorithm correction NWP profiles Every 86 s granule Remapping and format NAR SST product MDB
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SPIE Defense, Security and Sensing, Baltimore, 29 April-3 May 2013 5 From radiom. data To workfile From workfile to NAR MDB extraction Buoy!
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SPIE Defense, Security and Sensing, Baltimore, 29 April-3 May 2013 6 Adjacency algorithm VIIRS pixel neighborhood is needed for: –T11-T12 smoothing –Gradient computation –Matchup Database extraction Trimmed pixels and scan overlapping must be taken into account -> adjacency algorithm needed! JPSS OAD document for Common Adjacency Software describes the common Adjacency algorithm An extended algorithm has been derived to allow neighborhood determination to extend beyond adjacent scans
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SPIE Defense, Security and Sensing, Baltimore, 29 April-3 May 2013 7 Raw data Pixel of interest
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SPIE Defense, Security and Sensing, Baltimore, 29 April-3 May 2013 8 After local adjacency has been determined Pixel of interest
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SPIE Defense, Security and Sensing, Baltimore, 29 April-3 May 2013 9 OSI-SAF VIIRS SST chain: status Preoperational since mid October 2012 Cloud mask control completed Final product ready (GDSV2.0 in netcdf4 ) Operational delivery to start in mid 2013 NWP derived correction will be introduced afterwards
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SPIE Defense, Security and Sensing, Baltimore, 29 April-3 May 2013 10 Quality levels?
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SPIE Defense, Security and Sensing, Baltimore, 29 April-3 May 2013 11 Quality levels ?
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SPIE Defense, Security and Sensing, Baltimore, 29 April-3 May 2013 12 Indicators ? Error as a function of Ts-clim. Minimum, On the MDB Gradient indicator Aerosol indicator Ice indicator ….. Mask indicator= mean of all indicators Limit value Critical value Indicators defined between 0=clear et 100=cloudy By limit and critical values such as: Tlimit-Ts Temp. Indicator= -------------- x 100 Tlimit-Tcritical
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SPIE Defense, Security and Sensing, Baltimore, 29 April-3 May 2013 13 Quality levels Cloud mask indicator : mean of all indicators –Temperature indicator (distance to minimum SST clim) –Gradient indicator (distance to maximum SST gradient clim) –Dust indicator (derived from SEVIRI SDI) –Ice indicator (derived from OSI SAF ice information) Algorithm risk: –Derived from algorithm potential problems Mask indicator Algorithm risk
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SPIE Defense, Security and Sensing, Baltimore, 29 April-3 May 2013 14 VIIRS SST field on the 20 March 2013 at 02:00
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SPIE Defense, Security and Sensing, Baltimore, 29 April-3 May 2013 15 Undetected cloudiness VIIRS SST – Minimum SST Climatology (OSTIA) 20 March 2013 at 02:00
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SPIE Defense, Security and Sensing, Baltimore, 29 April-3 May 2013 16 Cloudiness detected by low SST values Temperature indicator derived from the SST- mini clim difference 20 March 2013 at 02:00
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SPIE Defense, Security and Sensing, Baltimore, 29 April-3 May 2013 17 Cloudiness detected by high gradient values VIIRS SST gradients on the 20 March 2013 at 02:00
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SPIE Defense, Security and Sensing, Baltimore, 29 April-3 May 2013 18 Univ. Rhode Island Pathfinder derived maximum gradient climatology
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SPIE Defense, Security and Sensing, Baltimore, 29 April-3 May 2013 19 Climatology missing Erroneous location of max gradients Gradient indicator
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SPIE Defense, Security and Sensing, Baltimore, 29 April-3 May 2013 20 Mask indicator (mean of all indicators) 0= no risks; 100=critical
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SPIE Defense, Security and Sensing, Baltimore, 29 April-3 May 2013 21 SST confidence levels: Increasing quality from 2 to 5
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SPIE Defense, Security and Sensing, Baltimore, 29 April-3 May 2013 22 VIIRS SST field on the 22 September 2012 at 13:00
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SPIE Defense, Security and Sensing, Baltimore, 29 April-3 May 2013 23 VIIRS SST – Mean SST Climatology (OSTIA) 22 September 2012 at 13:00
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SPIE Defense, Security and Sensing, Baltimore, 29 April-3 May 2013 24 SEVIRI derived SDI
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SPIE Defense, Security and Sensing, Baltimore, 29 April-3 May 2013 25 Dust indicator
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SPIE Defense, Security and Sensing, Baltimore, 29 April-3 May 2013 26 Algorithm determination RTTOV-10 applied on the SAFREE (radiosonde profiles) data base Daytime algorithms NLC : SST = (a + b S ) T 11 + (c + d T s clim + e S ) (T 11 - T 12 ) + f S + g(1) Night-time algorithms T37_1 :SST = (a + b S ) T 37 + (c + d S ) (T 11 - T 12 ) + e S + f (2) where : –T S clim = first guess climatologic SST –S = 1/cos ( ) – 1 In practice T11-T12 are smoothed in a 11x11 pixel box
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SPIE Defense, Security and Sensing, Baltimore, 29 April-3 May 2013 27 Overall validation results NAR area; 15 October 2012 till 15th March 2013 Qual levels 3-5 Daytime qual. 3-5 Daytime qual. 5 Nighttime qual. 3-5 Nighttime qual. 5 number of cases 308899036481678 bias-0.13-0.10-0.050.03 standard- deviation 0.460.340.370.29
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SPIE Defense, Security and Sensing, Baltimore, 29 April-3 May 2013 28 NPP/VIIRS cloud detection is more efficient than the equivalent NOAA-A9/AVHRR
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SPIE Defense, Security and Sensing, Baltimore, 29 April-3 May 2013 29 Overall validation results: Daytime Qual 5: =-0.10; =0.34
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SPIE Defense, Security and Sensing, Baltimore, 29 April-3 May 2013 30 Overall validation results: Nighttime Qual 5: =0.03; =0.29
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SPIE Defense, Security and Sensing, Baltimore, 29 April-3 May 2013 31 Conclusion A VIIRS SST chain has been run in preoperational mode since mid October 2012 Validation results are OK –Cloud free coverage significantly larger than NOAA-19 –Daytime and nighttime standard deviation: 0.46 and 0.37 K resp. Next phases: –Starting operational delivery (mid 2013) –NWP derived BT simulations and bias correction/Optimal Estimation
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SPIE Defense, Security and Sensing, Baltimore, 29 April-3 May 2013 32 Example of a granule over NE Atlantic…..
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SPIE Defense, Security and Sensing, Baltimore, 29 April-3 May 2013 33 THE END ….Remapped at 1 km resolution over Brittany
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