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Aerosol class selected

Aerosol class selected. No coarse mode; 62.5:37.5 weak:strong 50:50 dust:sea-salt ; 87.5:12.5 weak:strong 100% sea-salt; 100% weak 100% dust; 50:50 weak:strong For most points, there is a real mixture of classes selected throughout the month

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Aerosol class selected

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  1. Aerosol class selected No coarse mode; 62.5:37.5 weak:strong 50:50 dust:sea-salt; 87.5:12.5 weak:strong 100% sea-salt; 100% weak 100% dust; 50:50 weak:strong • For most points, there is a real mixture of classes selected throughout the month • Reminder: Coarse to fine ratio is controlled by the effective radius retrieval

  2. × × Uncertainty evaluation by Kirsten Stebel

  3. Experience setting up orac community code within the cloud cci Caroline Poulsen and Cloud CCI team especially: Gareth Thomas, Chris Arnold, Matthias Jerg, Stefan Stapleberg, Don Grainger

  4. ORACOptimal retrieval of Aerosol and Cloud • Optimal estimation code to retrieve cloud parameters, optical depth, effective radius, cloud top pressure, phase

  5. Complexity • Code needed to be tested with multiple compilers on multiple platforms • Code is written in Fortran and C • Many different libraries required to read/produce data • Code needs to work with 3 instruments AATSR/MODIS/AVHRR

  6. Uncertainty estimates – coast/ocean 14% of points agree with AERONET within the average uncertainty estimate (For an ideal error budget, it should be 66%)

  7. Uncertainty estimates - land 76% of points agree with AERONET within the average uncertainty estimate (For an ideal error budget, it should be 66%)

  8. Validation Visible (11 um) Census • Principles of stereo • Obtain observations from two different viewing angles to obtain a stereo image pair • Use a stereo matching algorithm to locate corresponding image pixels. • The displacement between the pixels (the parallax) can be used to estimate height through application of a camera model. • Stereo relies upon image texture to derive height rather than abolsute radiances and thermal profiles and therefore performs effectively over Greenland Parallax

  9. Uncertainty on ATSR measurements Figure 10: Intercomparisons using direct matchups, nadir BRF and full BRF model including a correction for systematic uncertainties. Error bars represent the k=1 standard deviation of the differences between the measurements and reference. No corrections for systematic biases have been included in this plot.

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