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Published bySandra Hubbard Modified over 9 years ago
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Overview WP3000 Arnout Feijt AVHRR and AMSU analysis Data acquisition Standard processing Cloud Type Classifications AMSU AVHRR Quantitative Cloud Analysis Comparing / Combining with Ground Based -wave data Comparison with Atmospheric Models
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Data acquisition and standard processing Adam Dybbroe Problems Area definitions, Antenna failures Formats (hdf5, phyton, KNMI) Failure NOAA-15 (AMSU) Delayed launch NOAA-16 Upgrades ANA
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Goal: Give overview of synoptic cloud classes Products: All overpasses analyzed Monthly statistics of cloud characteristics Time series of cloud characteristics per station Cloud Type Classifications Adam Dybbroe
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AMSU Heike Hausschildt Goal Provide reference LWP values for AVHRR retrievals Problems Radiative Transfer Theory ----- large gap ------ Real Life Results Literature approach ===> unsatisfactory Neural Network-approach ===>? presentation
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AVHRR Quantitative Cloud Analysis Dominique Jolivet Goal Spatial distribution of LWP Problems Calibration NOAA-15 Retrieval assumptions Number of cases (Supervized mode)
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AVHRR Quantitative Cloud Analysis Dominique Jolivet Number of cases Selection, Help from University Kiel Extentions + Adaptions of KLAROS High speed access LUTs, Multiple viewing geometries, Area averages, 1.6micron images, Unexpected usefulness of the 1.6micron channel (N-16) Particle size, Phase discrimination (not part of KLAROS) Quality LWP fields is better than was expected for cloud fields of low variability
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AVHRR versus -wave radiometers Dominique Jolivet, Heike Hausschildt Supervized Lot of work and subjective Russian doll method Comparing average and variance at increasingly larger scales The Heike method..?
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AVHRR versus -wave radiometers
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Comparison with Atmospheric Models
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ProgramWP3000 Adam Dybbroe –Data acquisition –Standard processing –Cloud Type Classifications Heike Hausschildt –AMSU radiances into a go Neural Network Dominique Jolivet –AVHRR Quantitative Cloud Analysis Heike Hausschildt –Comparing AVHRR with Ground Based -wave data
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