Errors in radial velocity variance from Doppler wind lidar

Abstract

Abstract. A high-fidelity lidar turbulence measurement technique relies on accurate estimates of radial velocity variance that are subject to both systematic and random errors determined by the autocorrelation function of radial velocity, the sampling rate, and the sampling duration. Using both statistically simulated and observed data, this paper quantifies the effect of the volumetric averaging in lidar radial velocity measurements on the autocorrelation function and the dependence of the systematic and random errors on the sampling duration. For current-generation scanning lidars and sampling durations of about 30 min and longer, during which the stationarity assumption is valid for atmospheric flows, the systematic error is negligible but the random error exceeds about 10 %.

The spectral signature of wind turbine wake meandering: A wind tunnel and field‐scale study

“…Lidar technology represents the best alternative to met towers for wind field experimentation and monitoring, with the exception of snow particle velocimetry measurements, which provide high‐resolution spatial (2‐D)–temporal (1‐D) flow fields in the turbine wake at field scale . While commercially available lidar has been accepted as a means for measuring first‐order statistics, inherent limitations of the technology, namely, low temporal and spatial resolution, lead to unreliable turbulence measurements . As a result, turbulent statistics derived from lidar measurements have been supplemented by, and verified against, high‐frequency point measurements such as met‐mounted sonic anemometry.…”

“…While the resulting variance values exclude turbulent energy in the smallest and largest scales of the flow, the sonic and Windcube measurements can more reliably be compared. However, the Windcube variance may still be overestimated (see above and other works). For instance, in the baseline periods where sonic anemometers and lidar were colocated (see Appendix B), the estimated variance of the streamwise velocity at hub height ranges from 0% to 10% higher for lidar than for sonic under various wind and thermal stability conditions.…”

“…technology, namely, low temporal and spatial resolution, lead to unreliable turbulence measurements. [17][18][19][20] As a result, turbulent statistics derived from lidar measurements have been supplemented by, and verified against, high-frequency point measurements such as met-mounted sonic anemometry.…”

Estimation of turbulence dissipation rate and its variability from sonic anemometer and wind Doppler lidar during the XPIA field campaign

“…As a general rule, we expect shorter timescales to be adequate for stable conditions, when the turbulent eddies in the boundary layer are smaller, while longer scales would be more suitable during unstable conditions, characterized by larger convective eddies that can be fully captured only when using larger scales. Moreover, different altitudes can also impact the extension of the inertial subrange, with a wider development expected at higher heights, as the integral length scale of turbulence increases (Wang et al, 2016). To estimate the appropriate timescales which best balance these competing factors, we calculate , at each height from each of the considered lidars, using several values for the number of samples N used in the calculation.…”

Response to Anonymous Referee #1

“…An accurate forecast of these quantities has a critical impact on a variety of socioeconomic activities, such as pollutant dispersion, air quality forecasting (Huang et al, 2013), and forest fire prediction and management (Coen et al, 2013). Wind energy production is also highly affected by turbulence in the boundary layer, as a lower power is generated when turbulence intensity is high (Wharton and Lundquist, 2012), and turbulence also reduces the lifetime of wind turbines (Kelley et al, 2006).…”