Hyperspectral Cloud-Clearing
date post
23-Jan-2016Category
Documents
view
26download
0
Embed Size (px)
description
Transcript of Hyperspectral Cloud-Clearing
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
22/21
32
33
34
35
36
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.
22/21
32
33
34
35
36
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
22/21
32
33
34
35
36
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.
22/21
32
33
34
35
36
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
22/21
32
33
34
35
36
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.
22/21
32
33
34
35
36
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
1
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