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CAMELOT Observation Techniques and Mission Concepts for Atmospheric Chemistry Task 4:

CAMELOT Observation Techniques and Mission Concepts for Atmospheric Chemistry Task 4: Assessment of Cloud Contamination Caroline Poulsen & Richard Siddans PM5, RAL, 28 th -29 th January 2009. Task 4. Generate a reference set of basic cloud statistics

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CAMELOT Observation Techniques and Mission Concepts for Atmospheric Chemistry Task 4:

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  1. CAMELOT Observation Techniques and Mission Concepts for Atmospheric Chemistry Task 4: Assessment of Cloud Contamination Caroline Poulsen & Richard Siddans PM5, RAL, 28th-29th January 2009

  2. Task 4 • Generate a reference set of basic cloud statistics • Generate statistics on cloud as a function of • geographical region • season and time of day, • pixel size and observation geometry, • A key objectives are to trade of the relative benefits of • GEO vs LEO • LEO at different local times or non sun-synch

  3. Data • We have Selected SEVIRI data from Climate Monitoring SAF • The data was uploaded to RAL on a daily basis • To date, we are storing data from May 2007-April 2008 and have requested 1 year of data

  4. Locations

  5. Generation of simulated polar orbit information from SEVIRI • Statistics have been generated for a selection of polar orbit times resolutions and inclinations • 98 degree inclinations • Local orbit times • anxt=9.30,13.30,17.30 • anxt=9.30 • anxt=10.30 (MODIS) • anxt=9.30,13.30,15.30 • 57 degree inclination • anxt=0.30,06.30,12.30,18.30 • Resolutions • 10, 20, 50km

  6. FOR REGION P1, likelihood of at least one “cloud-unaffected” observation within a “field-of-regard”, within a time-window.

  7. FOR REGION When Pixels are larger than the FOR they are only counted once

  8. Results for varying pixel size

  9. Results for varying location

  10. Different threshold scenarios applied • Optical depth • 0, 1, 5, 10 • Cloud fraction • 0, 5%, 10%, 20% • Cloud height • 3km threshold

  11. Results for varying cloud thresholdsKampala July

  12. Variation with cloud threshold London July

  13. Polar cloud mask 1145 1245 1345 1445 polar_20070703_1p5_10_98

  14. Results for varying orbit scenario

  15. Variation of pixel size with across track distance Complete coverage each day Complete coverage every 3 days

  16. Bold lines show 24 hour probabilities Dashed lines show day light probabilities

  17. 15/12/2007 10:45 Clear benefit of smaller pixel size!

  18. Primary conclusions • By combining up to 4 polar orbiters, the cloud-unaffected sampling probability approaches that available from geostationary orbit • However, geostationary orbit generally samples more often during the day, and, especially for small field of regard, has higher probability of 1 pixel cloud free during the day. • Pixel size strongly affects sampling. Geostationary sampling is only advantageous compared to polar orbit if the geostationary pixel size is comparable over the region of interest.

  19. Factors that are less important • Increasing the cloud optical depth threshold will increase significantly the number of valid pixels • Location and meteorology significant effects on valid cloud pixels • Increasing the cloud fraction increased the number of valid pixels but not by much. • No surprise, the difference in the different orbit scenarios most significant during winter, when daylight hours are short • Changing the height threshold increased the number of valid pixels increased the cloud free probability over London.

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