1. Proposed new uses for the Ceilometer Network
Christine Chiu
Ewan O’Conner, Robin Hogan, James Holmes
University of Reading

2. Outline What we propose to observe and why this is new
How we retrieve cloud optical depth from ceilometer data
How well the method performs and how we can work together

3. Ceilometers have been used to observe aerosols and clouds
Cloud base height for all cloud cases
Cloud optical depth for thin clouds
How about thick clouds?

4. Cloud optical depth is the great unknown
Differences between climate models: factor 2-4 (Zhang et al., JGR, 2005)
Differences between ground-based methods: factor 2-4 (Turner et al., BAMS, 2007)

5. Multi-filter rotating shadowband radiometer (MFRSR)
works only for overcast cases

6. AERONET cloud mode provides routine cloud optical depth measurements
Normal aerosol mode
(sun-seeking)
Cloud mode
(zenith-pointing)
Chiu et al. (JGR, 2010)

7. Ceilometers measure zenith radiance too!
“solar background light”
(a lidar noise source)
Signal no
lidar
Sun
shoots
Fractional day
Zenith Radiance (arbitrary unit)
cloudy
clear
lidar
shoots

8. 1-channel zenith radiance measurements are ambiguous for cloud retrievals in a 1D radiative transfer world
Cloud optical depth
Zenith Radiance
3D simulations
Cloud’s optical influence extends far beyond the borders of the cloud
plane-parallel

9. Thick clouds – ceilometer’s active beam is completely attenuated

10. Use known overcast and clear-sky cases to develop our classification scheme
Overcast thick clouds
Cloud optical depth > 10 continuously at least for 1 hour
Clear-sky
Cloud optical depth < 3 continuously at least for 1hour
Cloud’s optical influence extends far beyond the borders of the cloud

11. Determine if ceilometer’s active beam is completely attenuated
Find the cloud top layer using cloud flags in Cloudnet products
Backscatter signal (sr-1 m-1)
Range (km)
Calculate the mean backscatter signal from the cloud top to 1 km above
cloud top

12. Histogram of mean backscatter for clear-sky cases
100
counts
clear-sky cases
Altitude (km)
cloudy
clear
This threshold properly indentifies 97% of clear-sky cases
mean backscatter (log scale)
between cloud top and 1km above

13. Histogram of mean backscatter for overcast clouds
clear
cloudy
100
counts
Altitude (km)
This threshold properly indentifies 86% of cloudy cases
mean backscatter (log scale)
between cloud top and 1km above

14. Evaluate our classification scheme using cloud mode retrievals
Cloud optical depth from ceilometer
drizzling
thin clouds
time/spatial resolution
examples are May 3, 19 UTC
Cloud optical depth from AERONET cloud mode

15. Intercomparison at Chilbolton and Oklahoma sites

16. Comparison to other instruments
AERONET cloud mode observations
Microwave radiometer
Cloud radar
reff in μm,
Liquid Water Path in g/m2

17. Example from Chilbolton 2010/08/17
Reflectivity
Attenuated backscatter coefficient

18. Retrievals from ceilometer, cloud mode and MWR agree well
Cloud optical depth
MWR
ct75K
Aeronet
ct75K
Time (UTC)

19. Example – cirrus cloud (Oklahoma)
Reflectivity
Attenuated backscatter coefficient
SGP from ct25K
Time (UTC)

20. Retrievals difference could be up to 30% if using a wrong cloud phase
Cloud optical depth
ice phase (D60)
ice phase (D180)
SGP from ct25K
water phase
Time (UTC)

21. Ice water paths derived from various empirical relationships
Ice water path (g/m2) ?
SGP from ct25K
Time (UTC)

22. A more complex case – water cloud and thick ice cloud (Oklahoma)
Reflectivity
Attenuated backscatter coefficient

23. Agreement is shown again for water clouds
Retrieved cloud optical depth
AERONET
ceilometer
MWR
Time (UTC)

24. Cloud optical depth could differ 30 –40% due to cloud phase
Retrieved cloud optical depth
Time (UTC)

25. Water clouds at the Oklahoma site in 2007 May-November
Occurrence counts
cloud optical depth

26. Difference between ceilometer and lidar applications
Pros
Seem easier to cross-calibrate ceilometer solar background light data
Smaller impact from aerosol and Rayleigh scattering at ceilometer wavelengths
Cons
Surface albedo could fluctuate quite significantly at 905 nm
A few weak water vapor absorption lines around 905 nm

27. Summary
The use of solar background light can greatly enhance current cloud products of ceilometer networks
Confident about cloud optical depth retrievals for water clouds
Continue testing our classification algorithm that distinguishes optically thin and thick clouds
A lot of work needs to be done for retrieving ice- and mixed-phase clouds