Hyperspectral Cloud-Clearing

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Hyperspectral Cloud-Clearing Allen Huang, Jun Li, Chian-Yi Liu, Kevin Baggett, Li Guan, & Xuebao Wu SSEC/CIMSS, University of Wisconsin-Madison. AIRS/AMSU V3.5 &V4.0 Cloud-Clearing Characteristic AIRS/AMSU Additional C.C. QC Using MODIS AIRS/MODIS Over Sampling Single-FOV N* C.C. - PowerPoint PPT Presentation

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  • Hyperspectral Cloud-Clearing

    Allen Huang, Jun Li, Chian-Yi Liu, Kevin Baggett, Li Guan, & Xuebao WuSSEC/CIMSS, University of Wisconsin-MadisonAIRS/AMSU V3.5 &V4.0 Cloud-Clearing CharacteristicAIRS/AMSU Additional C.C. QC Using MODISAIRS/MODIS Over Sampling Single-FOV N* C.C.AIRS/MODIS 2-FOV Vs. AIRS/AMSU 9-FOV C.C. Comparison5th Workshop on Hyperspectral Science of UW-Madison MURI, Airborne, LEO, and GEO ActivitiesThe Pyle CenterUniversity of WisconsinMadison7 June 2005

  • Case Granule Dataset Used 4 Granules of CollocatedAIRS & MODIS DataMODIS 1-km Cloud MaskAIRS C.M. (from MODIS)No ancillary data used2 Sep. 2002AIRS Focus Day17 Sep. 2003

  • Why cloud_clearing?AIRS clear footprints are less than 5% globally.Why use MODIS for AIRS cloud-clearing?Many AIRS cloudy footprints contain clear MODIS pixels; it is effective for N* calculation and Quality Control for CC radiancesCloud-clearing can be achieved on a single footprint basis (hence maintaining the spatial gradient information); There is a direct relationship between MODIS and AIRS radiances because they see the same spectra region.AIRS All ObservationsAIRS Clear Only Obs.

  • Case Global Dataset Used 240 Granules of CollocatedAIRS & MODIS DataMODIS 1-km Cloud MaskAIRS C.M. (from MODIS)No ancillary data usedAIRS Global Window Channel Brightness Temp. ImagesAscending Daytime Passes (Upper Left)Descending Nighttime Passes (Lower Right)

  • AIRS/AMSU (3 by 3 AIRS FOV) V3.5 Vs V4.0 C.C. ComparisonX-axis:V3.5 C.C. Bt.- Blue circleV4.0 C.C. Bt. Red crossY-axis: Clear MODIS Bt.Without Q.C.MODIS Band 223.95 micronsMODIS Band 223.95 microns

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  • AIRS/AMSU (3 by 3 AIRS FOV) V3.5 Vs V4.0 C.C. ComparisonX-axis:V3.5 C.C. Bt.- Blue circleV4.0 C.C. Bt. Red CrossY-axis: Clear MODIS Bt.With Q.C.MODIS Band 223.95 micronsQ.C. filtered most of the unreliable data as well as some good data.

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  • AIRS/AMSU (3 by 3 AIRS FOV) V3.5 Vs V4.0 C.C. ComparisonX-axis:V3.5 C.C. Bt.- Blue CircleV4.0 C.C. Bt. Red CrossY-axis: Clear MODIS Bt.Without Q.C.MODIS Band 287.3 micronsMODIS Band 287.3 microns

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  • AIRS/AMSU (3 by 3 AIRS FOV) V3.5 Vs V4.0 C.C. ComparisonX-axis:V3.5 C.C. Bt.- Blue CircleV4.0 C.C. Bt. Red CrossY-axis: Clear MODIS Bt.With Q.C.MODIS Band 287.3 micronsQ.C. filtered most of the unreliable data as well as some good data.

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  • AIRS/AMSU (3 by 3 AIRS FOV) V3.5 Vs V4.0 C.C. ComparisonX-axis:V3.5 C.C. Bt.- Blue CircleV4.0 C.C. Bt. Red CrossY-axis: Clear MODIS Bt.Without Q.C.MODIS Band 3313.33 micronsMODIS Band 3313.33 microns

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  • AIRS/AMSU (3 by 3 AIRS FOV) V3.5 Vs V4.0 C.C. ComparisonX-axis:V3.5 C.C. Bt.- Blue CircleV4.0 C.C. Bt. Red CrossY-axis: Clear MODIS Bt.With Q.C.MODIS Band 3313.33 micronsQ.C. filtered most of the unreliable data as well as some good data.

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  • Estimated AIRS/AMSU C.C. Bias and RMSEWithout (Green) and With (Blue) MODIS as Q.C.Australia Granule Use MODIS data as AIRS/AMSU C.C. Q.C. can enhance yields & performance

  • Estimated AIRS/AMSU C.C. Bias and RMSEWithout (Green) and With (Blue) MODIS as Q.C.South Africa Granule Use MODIS data as AIRS/AMSU C.C. Q.C. can enhance yields & performance

  • Estimated AIRS/AMSU C.C. Bias and RMSEWithout (Green) and With (Blue) MODIS as Q.C.Wisconsin Granule Use MODIS data as AIRS/AMSU C.C. Q.C. can enhance yields & performance

  • AIRS/MODIS Synergistic C.C. can Supplement AIRS/AMSU C.C.Especially over Desert RegionAIRS/AMSU C.C.(3 by 3 AIRS FOV)V3.5 BlueV4.0 Green

    AIRS/MODIS C.C.(1 by 2 AIRS FOV)Red

  • Aqua MODIS IR SRF Overlay on AIRS SpectrumDirect spectral relationship between IR MODIS and AIRS provides unique application of MODIS in AIRS cloud_clearing !

  • Threshold for AIRS Pair C.C. Retrieval:Each AIRS footprint within the C.C. pair (2 by 1 ) must have at least 15 MODIS confident clear (P=99%) pixel (partly cloudy)MODIS/AIRS Synergistic N* Cloud Clearing

    MODIS Bands Used in C.C.MODIS Bands Used in Q.C.Multi-band N*22 24 25 28 30 31 32 33 3422 24 25 28 30 31 32 33 34Single-band N*31or 2222 24 25 28 30 31 32 33 34

  • MODIS/AIRS Synergistic Single-Channel N* Cloud-ClearingGeneral PrincipalAfter SmithOr Q.C.

    ( { srf [ R c ( ( ( j ) ] R c ( ( ( j ) } 2 ( (

  • MODIS/AIRS Synergistic Multi-Channel N* Cloud ClearingGeneral PrincipalLi et al, 2005, IEEE-GRS

  • Step 1: Get cloud-cleared AIRS radiances for Principal and supplementary footprints.Step 2: Find best Rcc by comparing with MODIS clear radiances observations in the principal footprint.Principal footprint has to be partly cloudy, while the supplementary footprint can be either partly cloudy or full cloudy.The 3 by 3 box moves by single AIRS footprint, therefore each partly cloudy footprint has chance to be cloud-clearedMODIS/AIRS Synergistic N* Cloud ClearingAIRS Two-FOVs (Pair) Strategy

  • June issue of IEEE Trans. on Geoscience and Remote Sensing, 2005

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    23456788 possible AIRS pairs (2 FOVs)1MODIS/AIRS Synergistic N* Cloud ClearingOver Sampling Strategy1Pseudo Single AIRS FOV

  • 23456788 possible AIRS pairs (2 FOVs)12MODIS/AIRS Synergistic N* Cloud ClearingOver Sampling Strategy2Pseudo Single AIRS FOV1

  • 23456788 possible AIRS pairs (2 FOVs)123MODIS/AIRS Synergistic N* Cloud ClearingOver Sampling Strategy3Pseudo Single AIRS FOV1

  • Single-Channel Vs. Multi-Channel N* C.C. Error ComparisonSouth Africa Granule

  • Single-Channel Vs. Multi-Channel N* C.C. Error ComparisonWisconsin Granule

  • Single-Channel Vs. Multi-Channel N* C.C. Error ComparisonHurricane Isabel Granules

  • 3.96 um4.52 um6.7 um12.0 umSingle-Channel Vs. Multi-Channel N* C.C. Error Comparison

  • Single-Channel N* Channel Selection (22 Vs. 31) C.C. Error ComparisonAustralia Granule

  • Single-Channel N* Channel Selection (22 Vs. 31) C.C. Error ComparisonWisconsin Granule

  • Multi-Channel N* Desert vs. Land C.C. Error Comparison

  • Single-Channel N* Different Q.C. (0.5K vs. 1.0K) C.C. Yield & Error ComparisonSouth Africa Granule

  • Single-Channel N* Different Q.C. (0.5K vs. 1.0K) C.C. Yield & Error ComparisonWisconsin Granule

  • Single-Channel N* Different Q.C. (0.5K vs. 1.0K) C.C. Yield & Error ComparisonHurricane Isabel Granules

  • Wisconsin GranuleAIRS/AMSU C.C. (3 by 3 AIRS FOV) V4.0 - BlueAIRS/MODIS C.C. (1 by 2 AIRS FOV)Multi-Ch. - BlackSingle-Ch.:Band 31 Green; Band 22 - Red

  • AIRS/MODIS Synergistic C.C. can Supplement AIRS/AMSU C.C.Especially over Desert RegionAIRS/AMSU C.C.(3 by 3 AIRS FOV)V4.0 - Blue

    AIRS/MODIS C.C.(1 by 2 AIRS FOV)Multi-Ch. - BlackSingle-Ch.:Band 31 GreenBand 22 - RedAustralia Granule

  • AIRS/MODIS Synergistic C.C. can Supplement AIRS/AMSU C.C.Especially over Desert RegionAIRS/AMSU C.C.(3 by 3 AIRS FOV)V4.0 - Blue

    AIRS/MODIS C.C.(1 by 2 AIRS FOV)Multi-Ch. - BlackSingle-Ch.:Band 31 GreenBand 22 - RedSouth Africa Granule

  • AIRS BT(All)AIRS BT(Clear Only)AIRS BT(Cloud-Cleared)

  • AIRS BT(All)AIRS BT(Clear Only)AIRS BT(Cloud-Cleared)

  • Cloud-Cleared Vs. Cloud-Contaminated RetrievalDetails see Wu/Li Retrieval presentation

  • Synergistic AIRS/MODIS C.C. SummarySynergistic AIRS/MODIS C.C. could provide cloud-cleared radiances over non-oceanic scenes with good yield and performance at high spatial resolution (pseudo single AIRS FOV)

    AIRS/MODIS C.C. is one of the promising GOES-R risk reduction research for future HES cloudy sounding processing

    Since no Geo-microwave sensor is been planned, synergistic HES/ABI C.C. might become one of the baseline processing approach that worthy of further study