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

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%.

UK Met Office Network Single wavelength, low power lidar

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

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.

Middle Wallop Example C = 1.36 ± 0.11 mode mean Calibration Coefficient (C) for Middle Wallop CL31 from September 2014-December 2015. 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 1.36 ± 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%

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

Calibration of the Vaisala CL31s

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.

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.

Lufft ceilometer calibration using the cloud method

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).

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..?

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%

Collocated, calibrated ceilometers: some comparisons

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

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?

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

Collocated Ceilometers Free of saturation region Indication of saturation

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