Hyperspectral Cloud-Clearing Allen Huang, Jun Li, Chian-Yi Liu, Kevin Baggett, Li Guan, & Xuebao Wu SSEC/CIMSS, University of Wisconsin-Madison AIRS/AMSU.

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Presentation transcript:

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 5 th Workshop on Hyperspectral Science of UW-Madison MURI, Airborne, LEO, and GEO Activities The Pyle Center University of Wisconsin  Madison 7 June 2005

Case Granule Dataset Used 4 Granules of Collocated AIRS & MODIS Data MODIS 1-km Cloud Mask AIRS C.M. (from MODIS) No ancillary data used Australia GranuleWisconsin GranuleSouth Africa Granule Hurricane Isabel Granule 2 Sep AIRS 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 Collocated AIRS & MODIS Data MODIS 1-km Cloud Mask AIRS C.M. (from MODIS) No ancillary data used AIRS Global Window Channel Brightness Temp. Images Ascending 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 circle V4.0 C.C. Bt. – Red cross Y-axis: Clear MODIS Bt. Without Q.C. MODIS Band microns MODIS Band microns

AIRS/AMSU (3 by 3 AIRS FOV) V3.5 Vs V4.0 C.C. Comparison X-axis: V3.5 C.C. Bt.- Blue circle V4.0 C.C. Bt. – Red Cross Y-axis: Clear MODIS Bt. With Q.C. MODIS Band 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 Circle V4.0 C.C. Bt. – Red Cross Y-axis: Clear MODIS Bt. Without Q.C. MODIS Band microns MODIS Band microns

AIRS/AMSU (3 by 3 AIRS FOV) V3.5 Vs V4.0 C.C. Comparison X-axis: V3.5 C.C. Bt.- Blue Circle V4.0 C.C. Bt. – Red Cross Y-axis: Clear MODIS Bt. With Q.C. MODIS Band 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 Circle V4.0 C.C. Bt. – Red Cross Y-axis: Clear MODIS Bt. Without Q.C. MODIS Band microns MODIS Band microns

AIRS/AMSU (3 by 3 AIRS FOV) V3.5 Vs V4.0 C.C. Comparison X-axis: V3.5 C.C. Bt.- Blue Circle V4.0 C.C. Bt. – Red Cross Y-axis: Clear MODIS Bt. With Q.C. MODIS Band microns Q.C. filtered most of the unreliable data as well as some good data.

Estimated AIRS/AMSU C.C. Bias and RMSE Without (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 RMSE Without (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 RMSE Without (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 – Blue V4.0 – 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* Single-band N*31or MODIS/AIRS Synergistic N* Cloud Clearing

MODIS/AIRS Synergistic Single-Channel N* Cloud-Clearing General Principal After Smith Or Q.C.

MODIS/AIRS Synergistic Multi-Channel N* Cloud Clearing General Principal Li et al, 2005, IEEE-GRS

Step 1: Get cloud-cleared AIRS radiances for Principal and supplementary footprints. Step 2: Find best R cc 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 MODIS/AIRS Synergistic N* Cloud Clearing AIRS Two-FOVs (Pair) Strategy

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

possible AIRS pairs (2 FOVs) 1 MODIS/AIRS Synergistic N* Cloud Clearing Over Sampling Strategy 1 Pseudo Single AIRS FOV

possible AIRS pairs (2 FOVs) 1 2 MODIS/AIRS Synergistic N* Cloud Clearing Over Sampling Strategy 2 Pseudo Single AIRS FOV 1

possible AIRS pairs (2 FOVs) MODIS/AIRS Synergistic N* Cloud Clearing Over 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 um 12.0 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 - Blue AIRS/MODIS C.C. (1 by 2 AIRS FOV) Multi-Ch. - Black Single-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. - Black Single-Ch.: Band 31 – Green Band 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. - Black Single-Ch.: Band 31 – Green Band 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 Retrieval Details 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