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

CO2 Channel Selection Algorithm (CO2 Sorting) The Sorted Clear Sky Spectrum These figures show the channels used for the CO2 sorting (Left figure) and the effect of sorting the channels (right figure) for clear scene case -Sort from coldest to warmest BT -creat the sorted index which his aplied to all scene including clouds

CO2 Sorting: Sensitivity to Brightness Temperature High and Thick Cloud Thinner Cloud Low Cloud High and Thick Cloud Thinner Cloud High and Thick Cloud Major points to talk about: Effect of adding clouds to the sorted spectrum Information about the cloud height (inflection point) and optical thickness (slope) This figure demonstrates the signature of different cloud scenes. The first channel that “sees” the cloud will start to diverge from the sorted clear sky scene. For the high thick cloud this occurs at approximately 230 K. The slope of the sorted spectrum also has information about the cloud optical thickness. A sorted spectrum that quickly diverges from the clear sky scene represents a thick cloud. In contrast, a thin high cloud will have a more gradual slope is demonstrated in the figure. The cloud high algorithm looks to see if there is a divergence from the clear sky spectrum. The brightness temperature of the first channel that diverges beyond a pre-set threshold is determined the cloud top temperature. Using a pressure and temperature profile the cloud pressure level can be determined. Will talk about the problems with this approach.

Selected CO2 Channels High Cloud Mid Level Cloud

February 22, 2003

S-HIS - CPL February 22, 2003

S-HIS - CPL Cloud OD < 1.0 (km)

S-HIS Cloud Top OD Sensitivity 0.2 0.4 0.6 0.8 1.0 1.2 CPL OD Contours . SHIS - CPL SHIS Cloud Top Retrieval Altitude

S-HIS Cloud Top OD

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

Polar Cloud Height Retrieval Problem One BT could be 3 different cloud heights

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