Assessing Obukhov Length and Friction Velocity from Floating Lidar Observations: A Data Screening and Sensitivity Computation Approach

Abstract

This work presents a parametric-solver algorithm for estimating atmospheric stability and friction velocity from floating Doppler wind lidar (FDWL) observations close to the mast of IJmuiden in the North Sea. The focus of the study was two-fold: (i) to examine the sensitivity of the computational algorithm to the retrieved variables and derived stability classes (the latter through confusion-matrix theory), and (ii) to present data screening procedures for FDWLs and fixed reference instrumentation. The performance of the stability estimation algorithm was assessed with reference to wind speed and temperature observations from the mast. A fixed-to-mast Doppler wind lidar (DWL) was also available, which provides a reference for wind-speed observations free from sea-motion perturbations. When comparing FDWL- and mast-derived mean wind speeds, the obtained determination coefficient was as high as that of the fixed-to-mast DWL against the mast (ρ2=0.996) with a root mean square error (RMSE) of 0.25 m/s. From the 82-day measurement campaign at IJmuiden (10,833 10 min records), the parametric algorithm showed that the atmosphere was neutral (31% of the cases), stable (28%), or near-neutral stable (19%) during most of the campaign. These figures satisfactorily agree with values estimated from the mast measurements (31%, 27%, and 19%, respectively).

On the Retrieval of Surface-Layer Parameters from Lidar Wind-Profile Measurements

“…During the last decade, floating Doppler wind lidars (FDWLs) have emerged as the wind-energy-industry preferred solution to replace the metmast because of their accuracy and attractive cost-benefit of installation and maintenance. Many studies have shown that 10 min averaged wind-speed measurements from FDWLs are numerically equivalent to reference observations from anemometers or fixed Doppler wind lidar (DWL) [4][5][6]. However, FDWLs cannot measure a number of the atmospheric parameters that instruments mounted on meteorological masts can, which restrains commercial acceptance of FDWLs as stand-alone sensing instrument.…”

“…Other sensors can provide air-pressure and air-humidity observations. However, alternative methods are needed in scenarios with limited instrumentation [5,[15][16][17][18][19][20]. A good number of these methods use Monin-Obukhov similarity theory (MOST).…”

“…The methods for estimation of surface fluxes of momentum and heat (i.e., surface-layer parameters) by [16,20] require both temperature and wind-speed measurements, and that by Klug [17] the aerodynamic roughness length in addition. When looking for studies utilising only wind-speed measurements as a feasible alternative to be applied using FDWL observations, the number of surface-layer-retrieval methods are limited to four [5,15,18,19]. Nevertheless, the reliability of the optimisation method proposed by Lo [19] can be considered questionable because of different mathematical issues reported by Zhang [25].…”

“…Nevertheless, the reliability of the optimisation method proposed by Lo [19] can be considered questionable because of different mathematical issues reported by Zhang [25]. Of the remaining three methods, the recent one by Basu [15] (2019)-the so-called Hybrid-Wind (HW) method-is an enhanced version of the Swinbank [18] (1964), in which the surface-layer wind profile follows an exponential profile instead of MOST [5,8,[26][27][28]. HW estimates the Obukhov length from three levels of wind speed measurements.…”

“…Once the Obukhov length is obtained, the friction velocity and surface heat flux can be derived. In contrast to HW, the 2D method by Araújo da Silva et al [5] (2022) enables a simultaneously retrieval of the Obukhov length and friction velocity by using a two-dimensional (2D) parametric-solver algorithm. Moreover, the 2D algorithm can be extended to any number of measurement heights describing the wind profile.…”