Simulation of Doppler Lidar Measurement Range and Data Availability

Abstract

The measurement range of a coherent wind Doppler lidar (CWDL) along a laser beam is the maximum distance from the lidar where wind speed data are accurately retrieved. It means that, at this distance, a sufficient number of emitted laser photons are backscattered and received by the lidar. Understanding of the propagation of the laser through the atmosphere, and particularly the backscattering and extinction processes from aerosols, is therefore important to estimate the metrological performances of a CWDL instrument. The range is directly related to specific instrument characteristics and atmospheric content, such as the aerosols type, size, and density distributions. Associated with the measurement range is the notion of data availability, which can be defined, at a given range and over a time period, as the percentage number of data retrieved correctly by the CWDL over the total number of measurement attempts. This paper proposes a new approach to predict the CWDL data availability and range of measurement using both instrumental simulation and atmospheric observations of aerosol optical properties from weather stations and simulations. This method is applied in several CWDL measurement campaigns during which estimated data availabilities and ranges are compared with the observations. It is shown that it is fairly possible to anticipate the data availability and the range coverage of CWDL technology at any site of interest where atmospheric data are available. The method also offers an additional way to diagnose the operation of the instrument and will help in the design of future instruments.

Dynamic Data Filtering of Long-Range Doppler LiDAR Wind Speed Measurements

“…By this, the data availability decreases continuously. We assume that the here shown behaviour of all CNR-threshold containing filters is similar to the theoretical and empirically stated data availability decay with increasing distance described by Boquet [34]. It appears that the combined filter by Newman et al [16] does not produce any visible deviation from the CNR-threshold filter even when they applied an addition iterative standard deviation filter that, when applied alone, provides an availability of 98.5%.…”

“…By this, the data availability decreases continuously. We assume that the here shown behaviour of all CNR-threshold containing filters is similar to the theoretical and empirically stated data availability decay with increasing distance described by Boquet [34].…”

“…The kernel-based dynamic data filter shows a drop of data availability in closer distances followed by a constant slight decrease over the distance. From this behaviour it cannot be confirmed that the data availability of the dynamic data filters follow the decay stated by Boquet [34]. We assume that the main reason for this is based on the temporal and spatial normalisation of the LiDAR data.…”

Monitoring Dust Events Using Doppler Lidar and Ceilometer in Iceland

“…The primary output of Leosphere WindCube lidar is the carrier to noise ratio (CNR), which is directly related to the received backscatter signal [42]. Besides CNR, the output also includes radial wind speed, relative backscatter coefficient (β), and depolarization ratio (δ).…”

Determination of eddy dissipation rate by Doppler lidar in Reykjavik, Iceland

“…In general, we use CNR as an indicator of the backscatter signal intensity. The CNR depends on the backscatter and extinction coefficient of atmospheric aerosols (Boquet et al, 2016), and a high CNR is expected with increasing aerosol load. Weather conditions, for example the mixing process, also impact the CNR level.…”