Corrections for deriving reliable turbulent properties from Doppler lidar

Description

Doppler lidars are capable of providing winds and turbulent parameters, such as dissipation rate or relative turbulent intensity at high spatial and temporal resolution. The implications for boundary-layer retrieval are very exciting as this will allow the diagnosis of various aspects of the dynamical boundary layer, such as boundary layer type and height, multiple internal layers or regions of mixing and their specific properties. It is also possible to identify the source of mixing, whether it is surface or cloud-top driven, a product of wind shear or changes in surface roughness. The dissipation rate of turbulent kinetic energy within the boundary layer can be derived at high temporal and spatial resolution from Doppler lidar using a method that explicitly provides uncertainty estimates. Vertical velocity variance and skewness, calculated over longer time periods from 20-60 minutes from the same Doppler lidar dataset can be used to identify other dynamical processes responsible for turbulence in the boundary layer. We then integrate both methods, together with measurements of surface fluxes and Doppler lidar measurements of horizontal wind shear, to classify different boundary layers, and identify the extent of coupling with cloud layers. This will be realized through the creation of a boundary layer classification product as a VAP, and will be created for each ARM Doppler lidar deployment, including the fixed sites (SGP, Darwin), and Mobile Facility sites. The deployments cover a wide range of climatic zones with very different boundary layer structures, including marine, continental, arctic, tropical and orographic. Deriving high-quality operational retrievals from long-term datasets necessitates a thorough review of the corrections to be applied to raw output from the Doppler lidar instrument, taking into account instrumental and retrieval artefacts, to provide a comprehensive uncertainty analysis. The improvement in the radial Doppler velocity uncertainty estimate propagates directly through to wind retrievals and is vital for deriving reliable higher order velocity statistics such as variance, skewness and dissipation rates; for example, the observed variance contains contributions from both the true variance and the error variance. In this poster we present our progress in developing a Doppler lidar toolbox dedicated to characterising Doppler lidar uncertainties and providing operational Doppler lidar turbulent retrievals.