1. Emma Hopkin University of Reading
EMS
4-8 September 2017
Calibration of the Met Office ceilometer network using liquid water cloud
Emma Hopkin
University of Reading
Supervisors: Anthony Illingworth, Chris Westbrook, Sue Ballard,
Cristina Charlton-Perez, Lee Hawkness-Smith

2. Overview
Observations of the boundary layer and the presence of clouds and aerosols are key in furthering the understanding of air pollution and its health impacts, cloud and aerosol interactions, aerosol mixing and transport, and in reducing the error and uncertainty in numerical weather prediction.
Ceilometer networks provide a cheap, reliable and continuous data source which many national meteorological services already have in place.
These new potential applications of ceilometers have highlighted the need to ensure they are accurately calibrated.
A simple and robust method has been devised to calibrate ceilometers based on the cloud calibration technique originally developed by O’Connor et al. (2004).
The Met Office ceilometer network has been calibrated using this new technique with typical calibration coefficients accurate to within 8-10%.

3. UK Met Office Network
Single wavelength, low power lidar

4. Cloud Calibration technique
Using filtering thresholds/ratios, only profiles with liquid water cloud are used.
Step 1:
The integral below the cloud must be less than 5% of the whole profile integral – excludes rain, drizzle, high aerosol events.
The max β must be 20x the β 300m above and below – ensure the cloud is optically ‘thick’ and the beam attenuates.
Step 2:
The apparent S should not fluctuate by more than 10% of its nearest neighbours – ensure cloudy is not patchy or broken.
𝐼𝑛𝑡𝑒𝑔𝑟𝑎𝑡𝑒𝑑 𝐵𝑎𝑐𝑘𝑠𝑐𝑎𝑡𝑡𝑒𝑟 𝐵= 𝛽 𝑎𝑡𝑡 𝑑𝑧= 1 2𝜂𝑆 𝑠𝑟 −1
Eta is wavelength dependent – Ewan’s website for scatter correction
C = Sapp/Strue
βtrue = βapp*C

5. independency of calibration to range
Over 100,000 profiles included
For the period September 2014 to December 2015
Multiple scattering and water vapour attenuation below the cloud accounted for
The mean and standard deviation shown at 100m intervals that the value of the integrated attenuated backscatter, when corrected for multiple scattering, is not dependent on height
2D histogram of integrated attenuated backscatter with range, with height dependent multiple scattering correction applied.. Darker colours (towards red) indicate a higher density of profiles. The values show the mean +/- the standard deviation of the integrated attenuated backscatter (units sr-1) at 100m intervals.

6. Middle Wallop Example C = 1.36 ± 0.11
mode
mean
Calibration Coefficient (C) for Middle Wallop CL31 from September 2014-December Each black cross represents a single day, calculated from profiles deemed suitable by the calibration algorithm. The top panel shows the mode of C for each individual day and the bottom panel shows the mean of C for each day, with the standard deviation shaded in grey. The average of these daily modes is ± 0.11, the average of the daily medians is 1.38 ± 0.11
16 months of data– September 2014 – December 2015
Stable, no drift, standard deviation less than 10%

7. Causes of Variable calibration
Transmitter failing; laser power reducing
Window transmission reduced

8. Calibration of the Vaisala CL31s

9. Water Vapour Correction for 910nm
Ref: Markowicz et al., 2008
UK climate has a relatively small range of temperature extremes - it is assumed that the effect of the laser wavelength fluctuation due to temperature is small in comparison to other instrumental uncertainties.

10. Vaisala CL31 Calibration
Broad coverage of the UK.
Gibraltar shows application of calibration in a Mediterranean climate.
Similar calibration coefficient for majority of the network.
: Calibration coefficient for each of the CL31 ceilometers in the UK Met Office network. 3 months of data (January-March 2015) have been used for each instrument. The number of suitable calibration profiles will be dependent on occurrences of cloud and therefore will vary for each instrument. The box outline represents 50 % of the calibration profiles and the whiskers extend to include 95% of the profiles (outliers have been excluded from plot). The red line in the box shows the median calibration coefficient and the smaller, filled box shows the mean.

11. Lufft ceilometer calibration using the cloud method

12. Evidence of Saturation: Single profile comparison
Two liquid cloud profiles of attenuated backscatter from the Lufft CHM15k ceilometer at Aberporth on 20th March 2015 (second panel shows same plot on different scale). The profile in blue has a negative overshoot above the cloud whereas the red profile does not.
When saturation occurs, the backscatter reported for this profile is false – it is too low
It is possible to detect the majority of saturated profiles because the saturation of the receiver usually causes the instrument background noise to drop, making the signal appear negative just above the cloud layer (blue profile).

13. Evidence of Saturation: A 16 month comparison
Received power at the ceilometer is a function of range – the inverse power law.
This is corrected for in the calculation of attenuated backscatter.
As a result, the magnitude of the maximum attenuated backscatter in cloud should not be dependent on the height of the cloud.
CL31
CHM15k
4km
0.5km
2km
Vaisala C – no range dependency
Side note – can anyone explain the shift at 2km..?

14. Lufft Calibration examples Aberporth 0.60 ± 0.07
Calibration period of 15 months, Sept 2014 – June 2016
Stable and consistent for entire period – no annual cycle
Standard deviation of ~10%

15. Collocated, calibrated ceilometers: some comparisons

16. Collocated Ceilometers
1:1 correlation of Jenoptik CHM15k and Vaisala CL31 situated at Aberporth

17. Thank you for listening, any questions?
Summary
Calibration of the Met Office Vaisala ceilometers using the Cloud Method is stable and consistent for periods greater than a year.
Calibration of the Met Office Lufft ceilometers using the Cloud Method has been achieved, using cloud above 1.5 km.
When the collocated Vaisala and Lufft ceilometers are calibrated with the cloud method, the profiles are in agreement.
The Met Office therefore has a network of 43 calibrated ceilometers reporting full vertical profiles of attenuated backscatter,
Thank you for listening, any questions?

18. Profile Filtering
Thinner cloud, not being caught by step 1 filters. Step 2 filter removes it.
Minimal fluctuation in S

19. Collocated Ceilometers
Free of saturation region
Indication of saturation

20. Ceilometer overviews Vaisala CL31 Wavelength 910 nm
Temporal resolution 30 s
Spatial resolution 20 m
Coaxial lens design
Overlap < 70 m
Signal obtainable up to 7.5 km
Attenuation due to water vapour must be corrected, which results in a reduction of the calibration coefficient by approximately 20%.
Lufft CHM15k nimbus
Wavelength 1064 nm
Temporal resolution 30 s
Spatial resolution 15 m
Biaxial lens design
Overlap ~1500 m
Signal obtainable up to 15 km
Saturation of signal in liquid water cloud makes cloud calibration more challenging