2. 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

3. 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. 2002 AIRS Focus Day 17 Sep. 2003

4. 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.

5. 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)

6. 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 22 3.95 microns MODIS Band 22 3.95 microns

7. 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 22 3.95 microns Q.C. filtered most of the unreliable data as well as some good data.

8. 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 28 7.3 microns MODIS Band 28 7.3 microns

9. 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 28 7.3 microns Q.C. filtered most of the unreliable data as well as some good data.

10. 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 33 13.33 microns MODIS Band 33 13.33 microns

11. 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 33 13.33 microns Q.C. filtered most of the unreliable data as well as some good data.

12. 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

13. 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

14. 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

15. 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

16. 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 !

17. 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 Single-band N*31or 2222 24 25 28 30 31 32 33 34 MODIS/AIRS Synergistic N* Cloud Clearing

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

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

20. 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 8 5 4 3 2 16 7 MODIS/AIRS Synergistic N* Cloud Clearing AIRS Two-FOVs (Pair) Strategy

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

22. 1 23 4 567 8 8 possible AIRS pairs (2 FOVs) 1 MODIS/AIRS Synergistic N* Cloud Clearing Over Sampling Strategy 1 Pseudo Single AIRS FOV

23. 23 4 567 8 8 possible AIRS pairs (2 FOVs) 1 2 MODIS/AIRS Synergistic N* Cloud Clearing Over Sampling Strategy 2 Pseudo Single AIRS FOV 1

24. 23 4 567 8 8 possible AIRS pairs (2 FOVs) 1 2 3 MODIS/AIRS Synergistic N* Cloud Clearing Over Sampling Strategy 3 Pseudo Single AIRS FOV 1

25. Single-Channel Vs. Multi-Channel N* C.C. Error Comparison South Africa Granule

26. Single-Channel Vs. Multi-Channel N* C.C. Error Comparison Wisconsin Granule

27. Single-Channel Vs. Multi-Channel N* C.C. Error Comparison Hurricane Isabel Granules

28. 3.96 um 4.52 um 6.7 um 12.0 um Single-Channel Vs. Multi-Channel N* C.C. Error Comparison

29. Single-Channel N* Channel Selection (22 Vs. 31) C.C. Error Comparison Australia Granule

30. Single-Channel N* Channel Selection (22 Vs. 31) C.C. Error Comparison Wisconsin Granule

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

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

33. Single-Channel N* Different Q.C. (0.5K vs. 1.0K) C.C. Yield & Error Comparison Wisconsin Granule

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

35. 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

36. 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

37. 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

38. AIRS BT (All) AIRS BT (Clear Only) AIRS BT (Cloud-Cleared)

39. AIRS BT (All) AIRS BT (Clear Only) AIRS BT (Cloud-Cleared)

46. Cloud-Cleared Vs. Cloud-Contaminated Retrieval Details see Wu/Li Retrieval presentation

47. 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