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Cloud Detection HIRDLS Team Meeting Oxford Steven Massie NCAR June 24-27, 2008

Cloud Detection HIRDLS Team Meeting Oxford Steven Massie NCAR June 24-27, 2008. Outline. Radiance profiles and cloud types 12 µm channel Cloud detection algorithm Retrieval methodology Based on Massie et al., HIRDLS Observations of

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Cloud Detection HIRDLS Team Meeting Oxford Steven Massie NCAR June 24-27, 2008

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  1. Cloud DetectionHIRDLS Team MeetingOxford Steven MassieNCARJune 24-27, 2008

  2. Outline Radiance profiles and cloud types 12 µm channel Cloud detection algorithm Retrieval methodology Based on Massie et al., HIRDLS Observations of PSCs and Subvisible Cirrus, J. Geophys. Res., 112, D24S31, doi:10.1029/2007JD008788, 2007.

  3. Radiance Profiles Examples of 12 µm radiance profiles of different cloud types are presented

  4. The dotted curve is the “clear sky” average for a single day

  5. The dotted curve is the “clear sky” average for a single day

  6. Cloud Detection Algorithm Calculate average “clear sky” radiance profile for each day Compare individual radiance profiles to the clear sky profile Determine the topmost altitude for which a cloud is detected Specify an “icloud” integer at each altitude for each radiance profile “icloud” = 0 , 1, 2, 3, 4 (no cloud, unknown cloud, cirrus layer, PSC, opaque cloud) Detection is determined before the pressure-temperature (PT) retrieval Cloud top pressure is specified after the PT retrieval

  7. Obs |Obs – Clear Sky| dR/dz(obs) / dR/dz(clear) 100 (Obs – Clear Sky)/ Clear Sky

  8. Cloud Top Adjustment

  9. Cloud Top Selection Apply algorithms on Channel 6 (12 µm “infrared window) and Channel 12 (one of the O3 channels) The highest cloud top becomes the selected cloud top for all of the channels (except Channel 6)

  10. General Capability Cloud detection can be carried out for All 21 HIRDLS channels Non-uniform altitude grid Radiance profile statistics are calculated

  11. Retrieval Methodology Retrieve the Pressure-Temperature profile for the full altitude grid Specify the O3 and H2O mixing ratio profiles from Climatology Apply the Level 2 processor

  12. Solution methodology – slightly modified X(i+1) = X(i)+ ( F(i) dx) dx = (Sxa-1 +KTSy-1K)-1 { KTSy-1 [y-f(x(i))] – Sxa-1(x(i) - xa) } F(i) is a scalar F(i) = 0.1 for iterations i=1,4 F(i) =1.0 for iterations i=5,6,7,.. This is done only for the aerosol-cloud extinction solution

  13. Cirrus Profile Example -6 -5 -4 -3 -2 log10 (Extinction)

  14. Example: HIRDLS and CALIPSO Cloud Fields

  15. Data Usage Pressure range : 20 – 177 hPa Extinction range : 1 10-5 to 0.01 km-1 Precision range: 0 – 100 % 14 day temporal averaging improves cloud spatial distributions Use extinction data in a qualitative manner, i.e. data can be used to indicate the geographical distributions of clouds

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