1. Towards the operational cloud classification in Finland Otto Hyvärinen COST 722 Expert Meeting, Helsinki, 9 June 2004

2. Contents Cloud classification work with NOAA/AVHRR –in FMI –in Nowcasting SAF (PPS) Problems Future plans

3. FMI approach to cloud classification with NOAA/AVHRR The statistical pattern recognition approach –Collect a lot of training data –Approximate posterior probabilities with neural networks –Use a principled way of handling the uncertainty No physics, only data! –Different models for day, night and twilight Unfortunately, the development has stalled...

4. 20 September 2001, 5:54 UTC

5. Cloud Classification

6. Goodness of Cloud/Surface Separation

7. Nowcasting SAF approach with NOAA/AVHRR Developed mostly in SMHI Traditional thresholding –Thresholds computed with the help of the radiative transfer models (RTTOV) Uncertainty handled more ad hoc

8. An example from 8 June 2004, 06:20 UTC Cloud MaskCloud Classification

9. How do they compare? Comparison against SYNOP observations of total cloudiness All stationsStations from "the training area"

10. Problems? Common problems –Twilight! –AVHRR FMI problems – no physics  should explore RTMs Nowcasting SAF problems – bad decision making methods  should explore pattern recognition methods

11. Towards future Is Nowcasting SAF method for AVHRR "good enough" for us? From AVHRR to MODIS, VIIRS, etc –how to make this as least painful as possible? –SEVIRI, how useful is it in Finland, really? From the satellite cloud classification to the cloud analysis –how to combine remote sensing and in-situ observations with the model data to real 3D analysis of clouds, fog, and visibility?