1. Status, Evaluation and New Developments of the Automated Cloud Observations in the Netherlands Wiel Wauben, Henk Klein Baltink, Marijn de Haij, Nico Maat, Han The KNMI, The Netherlands Introduction Status and Experiences New/recent developments  Aeronautical observations  Mixing layer height Nubiscope

2. Introduction Automated cloud observations for synop and climatological reports in MetNet since Nov. 2002. Observers at airports only for aeronautical observations. Vaisala LD-40 ceilometer in combination with cloud algorithm (30’ cloud base  cloud cover/amounts). Cloud information centrally available every 10 minutes. Currently 24 ceilometer locations in the Netherlands, + 4 air bases in 2006/2007, + 5 platforms in North Sea in 2006/2007. Changes for automation of aeronautical observations.

3. MetNet Ceilometer locations KNMI Navy Air Force 4 Nogepa

4. Experiences 6 stations /3 years of data for intercomparison manned/automated. Results /scores in general the same.

5. Experiences Missing high clouds vs moist layer reported as cloud. “Gaps” in cloud deck during precipitation. Missing information during shallow fog. Faulty isolated hits. Fewer cases with1 and 7 okta compared to observer. Missing spatial representativity.

6. Nubiscope Scanning IR radiometer 1080 measurements every 15 minutes Tested at KNMI Dec 2005 to Feb 2006 Technical report 291 www.knmi.nl/~waube n

7. Nubiscope parameters Measures 1080 sky temperatures (10° azimuth, 3° zenith) and ground temperature Stores raw and derived data Data extracted off-line Parameters available every 15 (  10) minutes: Total cloud cover Cloud cover and base for main cloud deck Cover and base for low, middle and high clouds Cloud mask Cloud base height for zenith measurements Ceiling

8. Ground temperature

9. Sky temperatures CS

10. Cloud cover

11. Nubiscope versus ceilometer

12. Conclusions Network of near real-time automated cloud observations in the Netherlands (17  34 locations). Fully automated synop, climatological and aeronautical (cloud) reports. Inclusion of CB/CTU cloud type for aviation requires improvement. Optimisation of automated cloud observations (sensor; cloud algorithm; combination of sensors e.g. multi-ceilometer, satellite, Nubiscope, validation). New mixing layer height product.

13. Aeronautical cloud observations Automated METAR/SPECI reports in mid 2005 during closing hours of regional airports. SYNOP 30 1’ data  METAR 50 12” data Allowed layer separation, METAR coding. Evaluation of ceiling (height of lowest cloud layer where cloud amount exceeds 4 okta). In 2006 evaluation of CB/TCU determination from lightning and radar reflectivity threshold.

14. Ceiling Rotterdam AP 2001

15. Mixing layer height determination LD-40 backscatter profile shows aerosol signal. Gradient between top of mixing layer and free troposphere.

16. Evolution convective ML MLH2 MLH1 h SNR C1 MLH profiler Quality Index Good> 0.50 Weak> 0.25 Poor≤ 0.25

17. Limited range for MLH estimation MLH profiler/radiosonde h SNR Quality Index Good> 0.50 Weak> 0.25 Poor≤ 0.25

18. diurnal cycle De Bilt 2000-2005 Monthly variability of MLH diurnal cycle captured Spring/summer: limited vertical range for MLH estimation LEGEND SNR stop level MLH1

19. Results: detection rates De Bilt 2000-2005 Overall detection rate: 45-70% ‘Good’ QI: 20-30 % Spring/summer: Largest contribution of ‘Poor’ estimations