Validation of SAFNWC/MSG cloud products

1. Validation of SAFNWC/MSG cloud products 17th October 2005 Madrid Hervé Le Gléau and Marcel Derrien Météo-France / CMS lannion

2. Plan of presentation SAFNWC context Validation of Cloud Mask (CMa) with SYNOP Validation of Dust flag (CMa) with interactive targets Info on volcanic ash clouds (CMa) Validation of Cloud type (CT) with interactive targets Validation of Cloud Top Pressure (CTTH) with radiosondes Validation of Cloud Top Height (CTTH) with lidar/radar Outlook

3. SAFNWC context -SAFNWC/MSG software v1.2 available since May 2005 -Includes three cloud products (CMa, CT, CTTH) developed by Météo-France/Lannion -Detailed description of cloud algorithms available from http://nwcsaf.inm.es or www.meteorologie.eu.org/safnwc -v1.2 cloud products validated with one year of data. Detailed results available on http://nwcsaf.inm.es or www.meteorologie.eu.org/safnwc -This presentation summarizes CMa CT CTTH validation results

4. Validation of CMa with SYNOP (1) • Comparison of cloudiness observed in SYNOP and computed from SEVIRI (CMa): • 1st November 2003 - 28th February 2005 • 302 manned continental stations over Europe • Possibility to reprocess SAFNWC/CMa on database • Following cloudiness are compared: • SEVIRI: average cloudiness in a 5x5 target (no account of fractional cloudiness in pixel) • SYNOP: total observed cloudiness • Results stratified in mid-latitude (lat<55 degree) or nordic

6. Validation of CMa with SYNOP (2) -at twilight: cloud underestimation (low clouds) -at night: cloud free areas confused with cloud Good agreement at midlatitude, but

7. Detected Validation of CMa with SYNOP (3) yes no Observed yes  yy yn yy+yn no ny nn ny+nn yy+ny yn+nn Total Cloudy event Cloudy event: yes if total cloudiness > 5 octas no if total cloudiness < 3 octas 1-PODcloud: yn/(yy+yn) rate of missed cloud observations 1-PODclear: ny/(ny+nn) rate of missed clear observations

8. Validation of CMa with SYNOP (4) Nordic: general cloud overestimation Nordic: no strong cloud underestimation at twilight

9. Validation of CMa with SYNOP (5) period: 25th August 2004-28th February 2005 • SAFNWC/CMa significantly better than MPEF/CLM : • better cloud detection with less cloud free areas confused as clouds • less sensitive to latitude effects

10. Validation of CMa with SYNOP (6) At daytime POD Snow cannot be detected and is classified as clouds in 37% of cases in mid-latitude regions (50% in nordic areas) At night-time Evaluation of CMa snow cover identification FAR: 0.03%

11. Validation of CMa with SYNOP (7) mid-latitude or nordic 1-PODcloud Decrease of the number of cloud-free detected pixels Impact of CMa quality on cloud free detection for land remote-sensing cover identification Poor quality cloud free pixels are merged with cloudy pixels.

12. Validation of CMa with SYNOP (8) • Summary of CMa validation with SYNOP: • Best quality in mid-latitude regions and in daytime conditions • Most striking effect of illumination in mid-latitude: • cloud cover underestimation at twilight (low clouds) • cloud free may be confused with snow at night-time • Effect of latitude for nordic areas: • less problematic cloud detection at twilight (8.7mm) • trend to overestimate cloud cover in all illumination • SAFNWC/CMa significantly better than MPEF cloud mask

13. Visual verification of CMa • Major problems observed by CMa visual inspection : • Low clouds are frequently undetected at low solar elevation • Low clouds may be occasionaly undetected at night-time: • Oceanic rather warm Sc advected above not too cold ground (mainly in spring and autumn) • Low clouds surmounted by very thin cirrus clouds • Snow is not detected at night-time and may be confused with clouds

14. Dust flag (CMa) validation with interactive targets Validation done from dust manually labelled (interactive targets): Over land (2212 dust targets): Only at daytime Not successful over Europe (too low signature) Over Africa: POD: 60.5% FAR: 1.9 %. Less efficient detection in morning and evening Over sea (1311 dust targets): Only at daytime POD: 36.3%; FAR: 3.8% Easier detection in case high level dust layer

15. Dust flag (CMa) illustration

16. Information on volcanic ash flag (CMa) (1) Two main events: Nyaragongo (Africa, started 8th mai 2004) Grimsvotn (Island, started 1st November 2004) Volcanic ash flag not successful: Certainly due to ice/water vapour contamination which counterbalance the main volcanic ash negative signature in 10.8mm-T12.0mm

17. Information on volcanic ash flag (CMa) (2) Promising volcanic activity detection: mapping SO2 emission with 8.7mm channel

18. Validation of CT with interactive targets (1) • Comparison of cloud type manually labelled (interactive targets) and computed from SEVIRI (CT): • 22 600 targets scattered in MSG full disk over 18 months • Possibility to reprocess SAFNWC/CT on database • Following cloudiness are compared: • SEVIRI: most frequent type in a 5x5 target • interactive target: manually labelled

19. Validation of CT with interactive targets (2) User accuracy : probability of a pixel classified into a category to really belong to this category DayNightTwilight

20. Validation of CT with interactive targets (3) Repartition of targets classified as medium clouds SeaLand

21. Validation of CT with interactive targets (4) Repartition of targets classified as fractional clouds Over sea Over land DayNight

22. Validation of CT with interactive targets (5) Summary of CT validation with interactive targets: • Stability of CT classifier to illumination, except for snow (not detected by CMa at nighttime) • Tendency to classify semi-transparents as medium clouds • Over land, still a tendency to classify low clouds as medium • Fractional clouds corresponds to semi-transparent or low clouds, respective percentage depending on illumination and land/sea

23. Visual verification of CT • Major problems observed by CT visual inspection : • Very thin cirrus are classified as fractionnal clouds • Very low clouds may be classified as medium clouds in case strong thermal inversion • Low clouds surmounted by thin cirrus clouds may be classified as medium clouds

24. Validation of CTTH with radiosounding (1) • Comparison of cloud top pressure derived from RS and computed from SEVIRI: • March 2004-February 2005 • All European meteorological stations with radiosoundings • Only homogeneous low / medium cloud layers • Cloud top pressures extracted as follow are compared: • SEVIRI: averaged on 9x9 pixel targets • RS: automatically analysed according stability/saturation criteria

25. Validation of CTTH with radiosounding (2) In general, a cloud top pressure underestimation is observed

26. Validation of CTTH with radiosounding (3) In case strong thermal inversion, a cloud top pressure overestimation is usually observed

27. Validation of CTTH with radar/lidar (1) • Comparison of cloud top height derived from radar/lidar and • computed from SEVIRI: • September 2003-October 2004 • SIRTA instrumented site (LMD, Palaiseau, near Paris): -Lidar: 532 and 1064 nm linearly polarized Not appropriate for thick water clouds or thin clouds over thick water clouds -Radar: 95Ghz Not appropriate for thin clouds above 10km or fair weather cumulus

28. Validation of CTTH with radar/lidar (2) • Only homogeneous cloud cover type in 11x7 pixels target; • either low / medium, or high / semi-transparent clouds • Manual analysis of suspect cases indicates thin layer over thick • cloud not well analysed with radar/lidarmultilayer rejected • Cloud Top Height extracted as follows are compared: • SEVIRI: CTH spatially averaged using 5x3 pixels target • Radar/lidar: CTH temporally averaged over 30 minutes • opaque clouds: with radar • ½ transparent clouds: with lidar

29. Validation of CTTH with radar/lidar (3) Opaque medium/high clouds ½ transparents clouds (intercept method)

30. Validation of CTTH with radar/lidar (4) Score for CTH_SEVIRI - CTH_radar/lidar

31. Summary of objective validation of CTTH • Summary of CTTH validation: • General underestimation of cloud top height except for low opaque clouds, stronger for high clouds or ½ transparent clouds • For low clouds, on average cloud top height overestimation with large scatter. Cloud top heigh underestimation observed if strong thermal inversion. • If radiance ratioing used (only applied to nearly opaque ½ transparent clouds), no bias observed (but still large scatter).

32. Visual verification of CTTH • Major problems observed by CTTH visual inspection : • CTTH is not available for clouds classified as fractionnal • CTTH may be not available for thin cirrus clouds • CTTH will be wrong if the cloud is wrongly classified: • Cloud top height underestimation for semi-transparent clouds classified as low/medium • CTTH for cirrus may have a square-like appearance • Retrieved low cloud top height may still be overestimated

33. Outlook • Perspective for algorithm improvement: • Validation results and users’ experience have been analysed; • This workshop should help us: • to settle priorities for improvement, • keeping in mind algorithm development feasibility