development of amsu-a fundamental cdr’s
DESCRIPTION
Development of AMSU-A Fundamental CDR’s. Huan Meng 1 , Wenze Yang 2 , Ralph Ferraro 1 1 NOAA/NESDIS/STAR/CoRP/Satellite Climate Studies Branch 2 NOAA Corporate Institute for Climate and Satellites [email protected]. Overview. Background: - PowerPoint PPT PresentationTRANSCRIPT
Development of AMSU-A Development of AMSU-A Fundamental CDR’sFundamental CDR’s
Huan MengHuan Meng11, Wenze Yang, Wenze Yang22, Ralph , Ralph FerraroFerraro11
11NOAA/NESDIS/STAR/CoRP/Satellite Climate Studies BranchNOAA/NESDIS/STAR/CoRP/Satellite Climate Studies Branch22NOAA Corporate Institute for Climate and SatellitesNOAA Corporate Institute for Climate and Satellites
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Background: Background: Part of a project supported by the NOAA Climate Data Part of a project supported by the NOAA Climate Data
Record (CDR) programRecord (CDR) program Goals:Goals:
Develop Develop Advanced Microwave Sounding Unit-AAdvanced Microwave Sounding Unit-A and – and –B (AMSU-A/-B) and Microwave Humidity Sounder (MHS) B (AMSU-A/-B) and Microwave Humidity Sounder (MHS) FCDR’s for “window” and water vapor channelsFCDR’s for “window” and water vapor channels
AMSU-A: 23.8, 31.4, 50.3, 89.0 GHzAMSU-A: 23.8, 31.4, 50.3, 89.0 GHzAMSU-B/MHS: 89, 150/157; 183AMSU-B/MHS: 89, 150/157; 183++1, 1831, 183++3, 1833, 183++7/190.3 7/190.3
GHzGHzDevelop TCDR’s for hydrological products (rain, snow, Develop TCDR’s for hydrological products (rain, snow,
etc.)etc.) Source DataSource Data
NOAA-15,16,17,18,19 & MetOp-A L1B dataNOAA-15,16,17,18,19 & MetOp-A L1B data
OverviewOverview
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AMSU-A SensorsAMSU-A Sensors Polar orbiting; cross track scan with 30 FOVs; 48 Polar orbiting; cross track scan with 30 FOVs; 48
km at nadir; “mixed” polarizationskm at nadir; “mixed” polarizations POES Satellites (carry AMSU-A, -B/MHS):POES Satellites (carry AMSU-A, -B/MHS):
=> NOAA-17 Channels 3 & 15 only have 1 year record=> NOAA-15 with large geolocation error since March 2010
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AMSU-A SDR BiasesAMSU-A SDR Biases Across scan asymmetryAcross scan asymmetry
Changes over orbit (ASC/DSC)Changes over orbit (ASC/DSC)Changes over life of sensorChanges over life of sensor
Warm target contaminationWarm target contamination ((ZouZou et al., et al., to be submitted)to be submitted)Orbital drift + Sun heating + Instrument nonlinear calibration Orbital drift + Sun heating + Instrument nonlinear calibration
errorerror Reflector emission Reflector emission Orbital decayOrbital decay Diurnal driftDiurnal drift Antenna pattern (Antenna pattern (sidelobe)sidelobe) effecteffect Geolocation errorGeolocation error Pre-launch calibration offsetPre-launch calibration offset
No SI-traceable standardsNo SI-traceable standards
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ChallengesChallenges Corrections of known biases (last slide)Corrections of known biases (last slide) Metadata (sensor degradation, satellite Metadata (sensor degradation, satellite
maneuver, etc.), data QCmaneuver, etc.), data QC Impacts from both Impacts from both surfacesurface and atmosphere and atmosphere
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Data collectionData collectionAMSU L1B data (1998 – present)AMSU L1B data (1998 – present)AMSU L2 data (2000 – present)AMSU L2 data (2000 – present)ECMWF Interim (1998 – 2008)ECMWF Interim (1998 – 2008)PATMOS-x cloud data (NOAA-15 & -18 2007 - 2009, soon to be PATMOS-x cloud data (NOAA-15 & -18 2007 - 2009, soon to be
complete)complete)
MetadataMetadataMSPPS, legacy project logMSPPS, legacy project logNOAA/NESDIS/OSDPD, operational collectionNOAA/NESDIS/OSDPD, operational collection
Asymmetry characterizationAsymmetry characterization
ProgressProgress (since April 2010)(since April 2010)
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AMSU-A TAMSU-A Tbb across scan asymmetry across scan asymmetry NOAA-18 Ascending TNOAA-18 Ascending Tbb
AMSU-A Asymmetry (1/3)AMSU-A Asymmetry (1/3)
Bia
s
Asymmetry
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Impact of TImpact of Tbb asymmetry on products asymmetry on productsAMSU-A Asymmetry (2/3)AMSU-A Asymmetry (2/3)
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Possible CausesPossible CausesReflector misalignmentReflector misalignmentBias in polarization vector orientationBias in polarization vector orientationSidelobe effectsSidelobe effectsAsymmetric atmosphere and surfaceAsymmetric atmosphere and surface
CharacterizationCharacterizationComparison of observation with CRTM simulationComparison of observation with CRTM simulationClear sky, over tropical and sub-tropical oceans (40N – Clear sky, over tropical and sub-tropical oceans (40N –
40S) 40S) Cloud screening approachesCloud screening approaches
AMSU L2 cloud productsAMSU L2 cloud productsPATMOS-x (AVHRR) cloud probabilityPATMOS-x (AVHRR) cloud probabilityERA Interim cloud probabilityERA Interim cloud probability
AMSU-A Asymmetry (3/3)AMSU-A Asymmetry (3/3)
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Asymmetry Characterization – L2 (1/5) Asymmetry Characterization – L2 (1/5) “Clear Sky” Definition“Clear Sky” Definition
L2 products: MSPPS AMSU-A Cloud Liquid Water (CLW) L2 products: MSPPS AMSU-A Cloud Liquid Water (CLW) and AMSU-B/MHS Ice Water Path (IWP)and AMSU-B/MHS Ice Water Path (IWP)
Clear-sky is identified when CLW = 0.0 and IWP = 0Clear-sky is identified when CLW = 0.0 and IWP = 0
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AMSU-A 1b raw count
Ta
Tb
Clear sky AMSU-A FOV determined by L2 productsOver tropical/subtropical oceans
ERA Interim T, q, O3 profiles; ERA interim SST, 10m U & V;
AMSU-A LZA, scan angle
Tb
Compare collocated Tb’s with same atmospheric condition for each beam position
CRTM
Asymmetry Characterization – L2 (2/5) Asymmetry Characterization – L2 (2/5) ProcedureProcedure
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OceansOceans40 S – 40 N40 S – 40 NClear skyClear sky
Jan & Apr 2008Jan & Apr 2008NOAA-18NOAA-18
ASC/DSC NodesASC/DSC Nodes
Small discrepancies Small discrepancies between ASC and DES between ASC and DES nodesnodes Channel-1 and -15 Asc Channel-1 and -15 Asc TTbb < Des T < Des Tbb
NOAA-18 is a PM NOAA-18 is a PM satellite, Asc Tsatellite, Asc Tbb < Des T < Des Tbb
Asymmetry Characterization – L2 (3/5) Asymmetry Characterization – L2 (3/5) Observed TObserved Tbb
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ASC and DES ASC and DES discrepancies mostly discrepancies mostly towards limbtowards limb Ch-1 asymmetry is Ch-1 asymmetry is basically linear, bias basically linear, bias (-1K, 0.6K)(-1K, 0.6K) Ch-2 has double peak, Ch-2 has double peak, bias (-0.9K, 0.6K)bias (-0.9K, 0.6K) Ch-3 has concave Ch-3 has concave shape, bias (0K, 2.9K)shape, bias (0K, 2.9K) Ch-15 is basically Ch-15 is basically linear, bias (-1.1K, 0.3K)linear, bias (-1.1K, 0.3K)
Asymmetry Characterization – L2 (4/5) Asymmetry Characterization – L2 (4/5) TTb b Bias and AsymmetryBias and Asymmetry
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All channels show All channels show asymmetry seasonalityasymmetry seasonality Consistent asymmetry Consistent asymmetry patternspatterns Ch-1 and -15 show the Ch-1 and -15 show the largest seasonality, up largest seasonality, up to 1Kto 1K Dec is upper bound Dec is upper bound and Aug is lower bound and Aug is lower bound for most channelsfor most channels
Asymmetry Characterization – L2 (5/5) Asymmetry Characterization – L2 (5/5) Asymmetry SeasonalityAsymmetry Seasonality
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PATMOS-x (AVHRR) cloud cover: 0.1 deg gridPATMOS-x (AVHRR) cloud cover: 0.1 deg grid Each AMSU-A FOV covers 14 to 100+ PATMOS-x pixels. Each AMSU-A FOV covers 14 to 100+ PATMOS-x pixels. Clear-sky is identified when every PATMOS-x pixel within the Clear-sky is identified when every PATMOS-x pixel within the
FOV is less than a certain cloud probability thresholdFOV is less than a certain cloud probability threshold Two thresholds are used: 10% and 50%Two thresholds are used: 10% and 50%
Cloud probability Cloud probability ≤≤ 50%, NOAA-18, 06/21/2008 50%, NOAA-18, 06/21/2008ASC DES
Asymmetry Characterization – PATMOS-x (1/2) Asymmetry Characterization – PATMOS-x (1/2) “Clear Sky” Definition“Clear Sky” Definition
More cloud in DES than in ASC
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Asymmetry Characterization – PATMOS-x (2/2) Asymmetry Characterization – PATMOS-x (2/2) ResultsResults
Similarities to L2 approachSimilarities to L2 approach Observed ASC TObserved ASC Tbb < DES T < DES Tbb
Across scan asymmetry patternsAcross scan asymmetry patterns Seasonality, Dec upper bound and Aug lower bound.Seasonality, Dec upper bound and Aug lower bound.
DifferencesDifferences Asymmetry magnitudesAsymmetry magnitudes Less linearity in ch-1 and -15Less linearity in ch-1 and -15 Less agreement between ASC and DES TLess agreement between ASC and DES Tbb
Impact of cloud probability threshold:Impact of cloud probability threshold:
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Asymmetry Characterization – ERA (1/2) Asymmetry Characterization – ERA (1/2) “Clear Sky” Definition“Clear Sky” Definition
ERA Interim cloudsERA Interim clouds High cloud (> 6.38 km)High cloud (> 6.38 km) Mid-cloud Mid-cloud Low cloud (< 1.78 km)Low cloud (< 1.78 km)
Clear skyClear sky When cloud cover probability is 0 at all three levelsWhen cloud cover probability is 0 at all three levels
Collocation of AMSU-A and ERA InterimCollocation of AMSU-A and ERA Interim ERA Interim has 0.703 deg spatial and 6-hr temporal ERA Interim has 0.703 deg spatial and 6-hr temporal
resolutions resolutions Nearest neighbor in space and linear interpolation in timeNearest neighbor in space and linear interpolation in time
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Asymmetry Characterization – ERA (2/2) Asymmetry Characterization – ERA (2/2) ResultsResults
Similarity to L2 approachSimilarity to L2 approach Across scan asymmetry patternsAcross scan asymmetry patterns
DifferencesDifferences Observed ASC TObserved ASC Tbb > DES T > DES Tbb
Asymmetry magnitudesAsymmetry magnitudes Less linearity in ch-1 and -15Less linearity in ch-1 and -15 Less agreement between ASC and DES TLess agreement between ASC and DES Tbb
Seasonality, Apr upper bound and Jul lower Seasonality, Apr upper bound and Jul lower
bound.bound.
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All show consistent All show consistent across scan asymmetry across scan asymmetry patternspatterns Different bias Different bias magnitudes magnitudes
Asymmetry ComparisonAsymmetry ComparisonNOAA-18, 2008, ASCNOAA-18, 2008, ASC
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Next StepsNext Steps Correction of asymmetryCorrection of asymmetry
Better understanding of the various cloud data sets, Better understanding of the various cloud data sets, achieve better agreement in asymmetry pattern with achieve better agreement in asymmetry pattern with the different approachesthe different approaches
Stratify data by SST and wind to remove asymmetry Stratify data by SST and wind to remove asymmetry caused by heterogeneous surfacecaused by heterogeneous surface
Analyze reflector misalignment and polarization Analyze reflector misalignment and polarization issues and correct the corresponding biases by issues and correct the corresponding biases by adjusting scan angle adjusting scan angle
Inter-satellite calibrationInter-satellite calibrationSimultaneous Nadir Overpass (SNO) techniqueSimultaneous Nadir Overpass (SNO) techniqueDouble Difference Technique (DDT)Double Difference Technique (DDT)Vicarious calibrationVicarious calibration
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SummarySummary AMSU-A TAMSU-A Tbb measurements suffer from many bias sources measurements suffer from many bias sources
such as warm target contamination and across scan such as warm target contamination and across scan asymmetry.asymmetry.
CRTM and three cloud screening methods were used to CRTM and three cloud screening methods were used to analyze the across scan asymmetry. They show similar Tanalyze the across scan asymmetry. They show similar Tbb
asymmetry patterns but different magnitudes.asymmetry patterns but different magnitudes. Cloud screening method plays a critical role in characterizing Cloud screening method plays a critical role in characterizing
the across scan asymmetry of AMSU-A Tthe across scan asymmetry of AMSU-A Tbb. More study is . More study is
required torequired to achieve better agreement in asymmetry patterns achieve better agreement in asymmetry patterns
obtained with the different approaches.obtained with the different approaches. SNO, DDT, and/or vicarious calibration will be used to perform SNO, DDT, and/or vicarious calibration will be used to perform
inter-satellite calibration in the near future.inter-satellite calibration in the near future.