1. Validation of Cloud Top Temperature with CLOUDNET cloud radar data during the BBC2 Period Erwin Wolters (D. Donovan Presenting)

2. Cluster 19 meeting, 21/09/2004 Short outline of CTT satellite algorithm Used methods (satellite and ground data) Results Some cases Summary Introduction

3. Cluster 19 meeting, 21/09/2004 Satellite Cloud Top Temperature Emissivity is calculated: Then, CTT is calculated :

4. Cluster 19 meeting, 21/09/2004 BBC2 ground stations CabauwChilbolton NOAA16, April 24 th 2003, 12:01 UTC

5. Cluster 19 meeting, 21/09/2004 Methods: satellite data 44 NOAA16 and NOAA17 overpasses during April and May 2003 Pixel area of 81 pixels around Chilbolton and Cabauw Cloud cover in pixel area > 50% Result: 53 mean satellite CTT values

6. Cluster 19 meeting, 21/09/2004 Methods: cloud radar data Cabauw: 35 GHz cloud radar, sample time 15s Chilbolton: 94 GHz cloud radar, sample time 30s Data in NET-CDF format Averaging time for Cloud Top Height 30 min

7. Cluster 19 meeting, 21/09/2004 Methods: cloud radar data (2) Cloud cover > 50%. Time period centered on satellite overpass 53 mean Cloud Top Height values

8. Cluster 19 meeting, 21/09/2004 Methods: cloud radar data (2) ChilboltonCabauw April 24 th 2003, 12:01 UTC, NOAA16 (left), cloud radar Cabauw (right) Satellite overpass

9. Cluster 19 meeting, 21/09/2004 ECMWF model data Cloud Top Height Cloud Top Temperature Only sounding data of de Bilt Use of ECMWF model data allowed? Model temperatures vs sounding temperatures

10. Cluster 19 meeting, 21/09/2004 ECMWF data vs sounding data Correlation=0.9916

11. Cluster 19 meeting, 21/09/2004 Results (1) 24-4-2003,12:01,CA 28-4-2003,9:45, CA Correlation=0.7497

12. Cluster 19 meeting, 21/09/2004 Results (2): Cases with  satt >5 Correlation=0.8437

13. Cluster 19 meeting, 21/09/2004 Ice clouds: April 24 th and 28 th 2003 Satellite overpass

14. Cluster 19 meeting, 21/09/2004 Brightness temperature differences BTD10.8-11.9 calculated for each pixel 81 pixel values for each case Plotted against: 1) pixel values of . 2) pixel values of temperature 10.8  m Are cases separated?

15. Cluster 19 meeting, 21/09/2004 BTD vs   =1.3   =9.6

16. Cluster 19 meeting, 21/09/2004 BTD vs T10.8  m

17. Cluster 19 meeting, 21/09/2004 BTD10.8  m-11.9  m  Cabauw

18. Cluster 19 meeting, 21/09/2004 Summary/conclusions CPP algorithm works good Weakness: - optically thin cases - clouds containing ice BTD10.8-11.9 for detecting ice clouds Possible tool for improvement of algorithm However, further research needed…

19. Cluster 19 meeting, 21/09/2004 Thanks for the attention… …any questions?