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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 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.
•AIRS/MODIS 2-FOV Vs. AIRS/AMSU 9-FOV C.C. Comparison
5th Workshop on Hyperspectral Science of UW-Madison MURI, Airborne, LEO, and GEO Activities
The Pyle Center
University of WisconsinMadison
7 June 2005
Case Granule Dataset Used
•4 Granules of CollocatedAIRS & MODIS Data•MODIS 1-km Cloud Mask•AIRS C.M. (from MODIS)•No ancillary data used
Australia Granule
Wisconsin Granule
South Africa Granule Hurricane Isabel Granule
2 Sep. 2002AIRS Focus Day
17 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 radiances
• Cloud-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 Observations
AIRS Clear Only Obs.
Case Global Dataset Used
•240 Granules of CollocatedAIRS & MODIS Data•MODIS 1-km Cloud Mask•AIRS C.M. (from MODIS)•No ancillary data used
AIRS 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. Comparison
X-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 microns
MODIS Band 223.95 microns
AIRS/AMSU (3 by 3 AIRS FOV) V3.5 Vs V4.0 C.C. Comparison
X-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 microns
Q.C. filtered most of the unreliable data as well as some good data.
AIRS/AMSU (3 by 3 AIRS FOV) V3.5 Vs V4.0 C.C. Comparison
X-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 microns
MODIS Band 287.3 microns
AIRS/AMSU (3 by 3 AIRS FOV) V3.5 Vs V4.0 C.C. Comparison
X-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 microns
Q.C. filtered most of the unreliable data as well as some good data.
AIRS/AMSU (3 by 3 AIRS FOV) V3.5 Vs V4.0 C.C. Comparison
X-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 microns
MODIS Band 3313.33 microns
AIRS/AMSU (3 by 3 AIRS FOV) V3.5 Vs V4.0 C.C. Comparison
X-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 microns
Q.C. filtered most of the unreliable data as well as some good data.
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 Region
AIRS/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 Spectrum
Direct 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 Bands
Used in C.C.
MODIS Bands Used in Q.C.
Multi-band N* 22 24 25 28 30 31 32 33 34
22 24 25 28 30 31 32 33 34
Single-band N* 31or 22 22 24 25 28 30 31 32 33 34
MODIS/AIRS Synergistic N* Cloud Clearing
MODIS/AIRS Synergistic Single-Channel N* Cloud-ClearingGeneral Principal
After Smith
Or Q.C.
MODIS/AIRS Synergistic Multi-Channel N* Cloud ClearingGeneral Principal
2)]([(1
*)( cci
clrM
i i
RfRNJi
2*
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([(1
*)(N
NRRfRNJ i
clrM
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*
*
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clrMi
i
iii
clrMi
i
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2112
*
Li 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.
(1) Principal footprint has to be partly cloudy, while the supplementary footprint can be either partly cloudy or full cloudy.
(2) The 3 by 3 box moves by single AIRS footprint, therefore each partly cloudy footprint has chance to be cloud-cleared
85
4
3
2
1 6
7
1ccR
2ccR
3ccR
4ccR
5ccR
6ccR
7ccR
8ccR
MODIS/AIRS Synergistic N* Cloud ClearingAIRS Two-FOVs (Pair) Strategy
June issue of IEEE Trans. on Geoscience and Remote Sensing, 2005
1 2 3
4
567
8
8 possible AIRS pairs (2 FOVs)
1
MODIS/AIRS Synergistic N* Cloud ClearingOver Sampling Strategy
1
Pseudo Single AIRS FOV
2 3
4
567
8
8 possible AIRS pairs (2 FOVs)
1 2
MODIS/AIRS Synergistic N* Cloud ClearingOver Sampling Strategy
2
Pseudo Single AIRS FOV
1
2 3
4
567
8
8 possible AIRS pairs (2 FOVs)
1 2 3
MODIS/AIRS Synergistic N* Cloud ClearingOver Sampling Strategy
3
Pseudo Single AIRS FOV
1
Single-Channel Vs. Multi-Channel N* C.C. Error Comparison
South Africa Granule
Single-Channel Vs. Multi-Channel N* C.C. Error Comparison
Wisconsin Granule
Single-Channel Vs. Multi-Channel N* C.C. Error Comparison
Hurricane Isabel Granules
3.96 um 4.52 um
6.7 um12.0 um
Single-Channel Vs. Multi-Channel N* C.C. Error Comparison
Single-Channel N* Channel Selection (22 Vs. 31) C.C. Error Comparison
Australia Granule
Single-Channel N* Channel Selection (22 Vs. 31) C.C. Error Comparison
Wisconsin 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 Comparison
South Africa Granule
Single-Channel N* Different Q.C. (0.5K vs. 1.0K) C.C. Yield & Error Comparison
Wisconsin Granule
Single-Channel N* Different Q.C. (0.5K vs. 1.0K) C.C. Yield & Error Comparison
Hurricane Isabel Granules
Wisconsin Granule
AIRS/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 Region
AIRS/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 - Red
Australia Granule
AIRS/MODIS Synergistic C.C. can Supplement AIRS/AMSU C.C.Especially over Desert Region
AIRS/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 - Red
South 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. Summary
• Synergistic 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