Towards the operational cloud classification

in Finland

Otto Hyvärinen

COST 722 Expert Meeting, Helsinki, 9 June 2004

Contents• Cloud classification work with NOAA/AVHRR

– in FMI– in Nowcasting SAF (PPS)

• Problems• Future plans

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...

20 September 2001, 5:54 UTC

Cloud Classification

Goodness of Cloud/Surface Separation

Nowcasting SAF approachwith NOAA/AVHRR

• Developed mostly in SMHI• Traditional thresholding

– Thresholds computed with the help of the radiative transfer models (RTTOV)

• Uncertainty handled more ad hoc

An example from 8 June 2004, 06:20 UTC

Cloud Mask Cloud Classification

How do they compare?

• Comparison against SYNOP observations of total cloudiness

All stations Stations from "the training area"

Problems?

• Common problems– Twilight!– AVHRR

• FMI problems– no physics should explore RTMs

• Nowcasting SAF problems– bad decision making methods should explore pattern

recognition methods

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?