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Hyperspectral Cloud Top Retrievals. Robert E. Holz, Steve Ackerman, Matthew McGill, Paolo Antonelli and Fred Nagle. Overview. Part 1. CO 2 Sorting + Slicing cloud height retrieval validation Part 2. Night time polar cloud height detection using AIRS hyperspectral measurements.
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Hyperspectral Cloud Top Retrievals Robert E. Holz, Steve Ackerman, Matthew McGill, Paolo Antonelli and Fred Nagle
Overview Part 1. CO2 Sorting + Slicing cloud height retrieval validation Part 2. Night time polar cloud height detection using AIRS hyperspectral measurements
The Sorted Clear Sky Spectrum CO2 Channel Selection Algorithm (CO2 Sorting)
Low Cloud Thinner Cloud Thinner Cloud High and Thick Cloud High and Thick Cloud High and Thick Cloud CO2 Sorting: Sensitivity to Brightness Temperature
Mid Level Cloud Selected CO2 Channels High Cloud
CPL OD Contours SHIS Cloud Top Retrieval 0.2 SHIS - CPL 0.4 0.6 0.8 1.0 1.2 S-HIS Cloud Top OD Sensitivity . Altitude
Distribution of S-HIS Cloud Level Optical Depth February 22 CPL optical depth at the S-HIS cloud height
Part 2: Night Time Polar Cloud Height Retrievals Using AIRS Hyperspectal Measurements
One BT could be 3 different cloud heights Polar Cloud Height Retrieval Problem
AIRS Polar Cloud Height Retrieval 22:00 UTC AIRS Polar Cloud Height Retrieval 14:00 UTC
Conclusions and Future Plans • The combined CO2 slicing + sorting cloud top retrieval improves the CO2 slicing results for optically thin clouds • Lidar retrieved integrated cloud optical depth is a more representative measure of cloud top retrieval performance. • It is possible to detect temperature inversions above arctic stratus using hyperspectral measurements • The inversion information reduces the uncertainty in the arctic stratus IR cloud top retrievals • Future: • Apply the CO2 sorting + slicing retrieval to AIRS satellite data • Integrate the CO2 sorting + slicing retrieval with the arctic inversion detection