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).

This study presents a wind retrieval simulator of a floating Doppler Wind Lidar (DWL) with 6 Degrees of Freedom (DoF) motion. The simulator considers a continuous-wave conical-scanning floating DWL which retrieves the wind vector from 50

This work presents an analytical formulation to assess the six-degrees-of-freedom-motion-induced error in floating Doppler wind LiDARs (FDWLs). The error products derive from the horizontal wind speed bias and apparent turbulence intensity. Departing from a geometrical formulation of the FDWL attitude and of the LiDAR retrieval algorithm, the contributions of the rotational and translational motion to the FDWL-measured total error are computed. Central to this process is the interpretation of the velocity–azimuth display retrieval algorithm in terms of a first-order Fourier series. The obtained 6 DoF formulation is validated numerically by means of a floating LiDAR motion simulator and experimentally in nearshore and open-sea scenarios in the framework of the Pont del Petroli and IJmuiden campaigns, respectively. Both measurement campaigns involved a fixed and a floating ZephIRTM 300 LiDAR. The proposed formulation proved capable of estimating the motion-induced FDWL horizontal wind speed bias and returned similar percentiles when comparing the FDWL with the fixed LiDAR. The estimations of the turbulence intensity increment statistically matched the FDWL measurements under all motional and wind scenarios when clustering the data as a function of the buoy’s mean tilt amplitude, mean translational-velocity amplitude, and mean horizontal wind speed.

In this work, the 2D parametric-solver algorithm [1] used to assess atmospheric stability from floating Doppler wind lidar (FDWL) measurements is revisited. The algorithm performance is studied using data This research is part of the projects PGC2018-094132-B-I00 and MDM-2016-0600 ("CommSensLab" Excellence Unit) funded by Ministerio de Ciencia e Investigación (MCIN)/ Agencia Estatal de Investigación (AEI)/ 10.13039/501100011033/ FEDER "Una manera de hacer Europa". The work of M.P Araújo da Silva was supported under Grant PRE2018-086054 funded by MCIN/AEI/10.13039/501100011033 and FSE "El FSE invierte en tu futuro". The work of A. Salcedo-Bosch was supported under grant 2020 FISDU 00455 funded by Generalitat de Catalunya-AGAUR. The European Commission collaborated under projects H2020 ACTRIS-IMP (GA-871115) and H2020 ATMO-ACCESS (GA-101008004).

<p>A wind retrieval simulator of a floating Doppler Wind Lidar (DWL) with six Degrees of Freedom (DoF) in its motion is presented. The simulator considers a continuous-wave, conically scanning, floating DWL which retrieves the local wind profile from 50 line of sight (LoS) radial velocity measurements per scan. Rotational and translational motion effects over horizontal wind speed (HWS) measurements are studied parametrically. The 6 DoF motion framework as well as the most important buoy motion equations are based on the model presented in [1].</p><p>Each rotational and translational motion is simulated as 1 second sinusoidal signal defined by an amplitude, frequency and motion phase. In order to study the problem of motion-induced error on the retrieved HWS, a dimension reduction is needed (22 variables). A consideration followed in the literature [2] to alleviate the problem is to set the same motional frequency (f=0.3 Hz) for all DoF, a wind vector with constant HWS and null vertical wind speed (VWS). Moreover, the parametric study is carried out under certain constraints in order to finally reduce the problem dimensionality to three, which enables the generation of tri-dimensional colorplots of the error on the retrieved HWS.</p><p>Simulation results show that in the presence of motion, HWS error has a strong dependency on FDWL initial scan phase. Moreover, the directions of the rotation axis and translational velocity vector (with respect to wind direction, WD) show great impact on HWS error. For translational motion, a 3 DoF superposition principle is corroborated.</p><p>The simulator is as a useful tool for understanding particular lidar motion scenarios and their contributions to HWS measurements error. However, further analysis of the effect of lidar initial scan phase is needed. Additionally, these simulations are conducted under idealized assumptions of horizontally homogeneous wind profiles in the vicinity of the FDWL. Simulations using non-homogeneous wind fields (e.g., turbulence, air mass boundaries) would give insights on how well floating lidars can be expected to retrieve the wind profile in these common scenarios.</p><p><strong>Acknowledgements</strong></p><p>This work was supported via Spanish Government–European Regional Development Funds project PGC2018-094132-B-I00 and H2020 ACTRIS-IMP (GA-871115). The European Institute of Innovation and Technology (EIT), KIC InnoEnergy project NEPTUNE (Offshore Metocean Data Mea-suring Equipment and Wind, Wave and Current Analysis and ForecastingSoftware, call FP7) supported measurements campaigns. CommSensLab isa María-de-Maeztu Unit of Excellence funded by the Agencia Estatal de Investigación (Spanish National Science Foundation). The work of Andreu Salcedo-Bosch was supported by the “Agència de Gestió d’Ajuts Universitaris i de la Recerca (AGAUR)”, Generalitat de Catalunya, under Grant no. 2020 FISDU 00455.</p><p><strong>References</strong></p><p>[1] F. Kelberlau, V. Neshaug, L. Lønseth, T. Bracchi, and J. Mann, “Taking the Motion out of Floating Lidar: Turbulence Intensity Estimates with a Continuous-Wave Wind Lidar,” Remote Sens., vol. 12, no. 898, 2020.</p><p>[2] J. Tiana-Alsina, F. Rocadenbosch, and M. A. Gutierrez-Antunano, “Vertical Azimuth Display simulator for wind-Doppler lidar error assessment,” in 2017 IEEE Int. Geosci. Remote. Se. (IGARSS). IEEE, Jul. 2017.</p>