Robin HoganEwan O’Connor

Changes to the Instrument Synergy/

Target Categorization product

Overview of changes• Melting layer identification using Doppler velocity

– Previously used only model wet-bulb temperature– Melting bit in “category_bits” variable is now used

• Sensitivity and error variables– Notably Z_sensitivity and lwp_error

• Will work without rain gauge data– Uses radar for rain detection

• Microwave brightness temperatures if available– Enables LWP to be recalculated using better algorithm if required

• Lidar molecular scattering bit for visible lidars– Enables molecular to be used to estimate optical depth in some

studies– Lidar beam divergence and field of view now held as variables

• Works with ARM data– Tested on SGP and NSA data so far

• Documentation!– http://www.met.rdg.ac.uk/radar/doc/categorization.html

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Melting layer identification• Previously rain was often diagnosed as ice

because the melting layer height was taken purely from the model wet-bulb temperature

Melting layer identification

• Look within 5ºC of Tw=0ºC isotherm in model– Melting layer is where

greatest divergence in radar Doppler velocity

Z v

Classification

Divergence

Melting ice

Radar sensitivity• Z_sensitivity variable is

estimated as a function of height– Includes range-squared

law, mean gas attenuation and ground clutter

– Used for iwc_sensitivity and to modify model cloud fraction

• Currently susceptible to erroneous Z values below the real radar sensitivity

Z_sensitivity

A day of Z values

1 year of CloudNet data• PDF of

dissipation rate for different types of cloud

• Note that aircraft measurements have lower limit of detectability of ~10–6 due to aircraft vibrations

Previous range for cirrus found from aircraft

Bouniol, Hogan and Illingworth (2004)