A novel post-processing algorithm for Halo Doppler lidars
Abstract. Commercially available Doppler lidars have now been
proven to be efficient tools for studying winds and turbulence in the
planetary boundary layer. However, in many cases low signal-to-noise ratio
is still a limiting factor for utilising measurements by these devices.
Here, we present a novel post-processing algorithm for Halo Stream Line
Doppler lidars, which enables an improvement in sensitivity of a factor of
5 or more. This algorithm is based on improving the accuracy of the
instrumental noise floor and it enables longer integration times or
averaging of high temporal resolution data to be used to obtain signals down to −32  dB.
While this algorithm does not affect the measured radial velocity, it
improves the accuracy of radial velocity uncertainty estimates and
consequently the accuracy of retrieved turbulent properties. Field
measurements using three different Halo Doppler lidars deployed in Finland,
Greece and South Africa demonstrate how the new post-processing algorithm
increases data availability for turbulent retrievals in the planetary
boundary layer, improves detection of high-altitude cirrus clouds and
enables the observation of elevated aerosol layers.