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

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

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?

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)

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

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

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 200508071800

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

Thick clouds – ceilometer’s active beam is completely attenuated

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

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

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

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

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

Intercomparison at Chilbolton and Oklahoma sites

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

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

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

Example – cirrus cloud (Oklahoma) Reflectivity Attenuated backscatter coefficient 20071122 SGP from ct25K Time (UTC)

Retrievals difference could be up to 30% if using a wrong cloud phase Cloud optical depth ice phase (D60) ice phase (D180) 20071122 SGP from ct25K water phase Time (UTC)

Ice water paths derived from various empirical relationships Ice water path (g/m2) ? 20071122 SGP from ct25K Time (UTC)

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

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

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

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

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

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