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 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.
The Verification of the Origins of Rotation in Tornadoes Experiment -Southeast (VORTEX-SE) provides a wealth of long-duration, high-resolution, vertically pointing observations from active and passive ground-based remote sensing systems enabling characterization of the Atmospheric Boundary Layer (ABL) development over distinct regions that are well known for their relatively high tornado frequency. Application of the Extended Kalman Filter (EKF) to BL height estimation in the convective regime (CBLH) of the diurnal cycle from S-band radar reflectivity observations 1 has shown to yield accurate results under simple CBL conditions. In this work, we revisit the radar-EKF technique and investigate its main limitations. For example, during daytime clear-sky conditions such as those prevailing in the BL morning transition, weak turbulence leads to very low reflectivity returns, limiting application of this technique. Additionally, turbulent mixing layers capped with a residual layer, and/or multi-layer scenarios can lead the filter to lose track of the BL signature over time. Doppler Wind Lidar (DWL) observations of the vertical wind velocity variance 2 provide complementary CBLH estimates to those of the radar-EKF combination, providing potential to disambiguate more complex convective cases. DWL estimates are, however, strongly influenced by the variance threshold selected. The complementarity of radar and DWL for CBLH estimation is studied in reference to radiosoundings.
<p>This study describes a method to estimate the nocturnal stable boundary layer height (SBLH) by means of lidar observations. The method permits two approaches which yield independent retrievals through either spatial or temporal variance vertical profiles of the attenuated backscatter. Then, the minimum variance region (MVR) on this profile is identified. Eventually, when multiple MVRs are detected, a temperature-based SBLH estimation derived from radiosonde, launched within the searching time, is used to disambiguate the initial guess. In order to test the method, two study cases employing lidar-ceilometer (Jenoptik CHM 15k Nimbus) measurements are investigated. Temperature-based estimates from a collocated microwave radiometer permitted validation, using either temporal or spatial backscatter variances. The dataset was collected during the HD(CP)2 Observational Prototype Experiment (HOPE) [1]. &#160;&#160;</p><p>[1] U. Saeed, F. Rocadenbosch, and S. Crewell, &#8220;Adaptive Estimation of the Stable Boundary Layer Height Using Combined Lidar and Microwave Radiometer Observations,&#8221; IEEE Trans. Geosci. Remote Sens., 54(12), 6895&#8211;6906 (2016), DOI: 10.1109/TGRS.2016.2586298.</p><p>[2] U. L&#246;hnert, J. H. Schween, C. Acquistapace, K. Ebell, M. Maahn, M. Barrera-Verdejo, A. Hirsikko, B. Bohn, A. Knaps, E. O&#8217;Connor, C. Simmer, A. Wahner, and S. Crewell, &#8220;JOYCE: J&#252;lich Observatory for Cloud Evolution,&#8221; Bulletin of the American Meteorological Society, 96(7), 1157-1174 (2015). DOI: 10.1175/BAMS-D-14-00105.1</p>
South America covers a large area of the globe and plays a fundamental function in its climate change, geographical features, and natural resources. However, it still is a developing area, and natural resource management and energy production are far from a sustainable framework, impacting the air quality of the area and needs much improvement in monitoring. There are significant activities regarding laser remote sensing of the atmosphere at different levels for different purposes. Among these activities, we can mention the mesospheric probing of sodium measurements and stratospheric monitoring of ozone, and the study of wind and gravity waves. Some of these activities are long-lasting and count on the support from the Latin American Lidar Network (LALINET). We intend to pinpoint the most significant scientific achievements and show the potential of carrying out remote sensing activities in the continent and show its correlations with other earth science connections and synergies. In Part I of this chapter, we will present an overview and significant results of lidar observations in the mesosphere and stratosphere. Part II will be dedicated to tropospheric observations.
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