Climatological Features of the Weakly and Very Stably Stratified Nocturnal Boundary Layers. Part I: State Variables Containing Information about Regime Occupation

Abstract The atmospheric nocturnal stable boundary layer (SBL) can be classified into two distinct regimes: the weakly SBL (wSBL) with sustained turbulence and the very SBL (vSBL) with weak and intermittent turbulence. A hidden Markov model (HMM) analysis of the three-dimensional state-variable space of Reynolds-averaged mean dry static stability, mean wind speed, and wind speed shear is used to classify the SBL into these two regimes at nine different tower sites, in order to study long-term regime occupation and transition statistics. Both Reynolds-averaged mean data and measures of turbulence intensity (eddy variances) are separated in a physically meaningful way. In particular, fluctuations of the vertical wind component are found to be much smaller in the vSBL than in the wSBL. HMM analyses of these data using more than two SBL regimes do not result in robust results across measurement locations. To identify which meteorological state variables carry the information about regime occupation, the HMM analyses are repeated using different state-variable subsets. Reynolds-averaged measures of turbulence intensity (such as turbulence kinetic energy) at any observed altitude hold almost the same information as the original set, without adding any additional information. In contrast, both stratification and shear depend on surface information to capture regime transitions accurately. Use of information only in the bottom 10 m of the atmosphere is sufficient for HMM analyses to capture important information about regime occupation and transition statistics. It follows that the commonly measured 10-m wind speed is potentially a good indicator of regime occupation.

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Field intercomparison of prevailing sonic anemometers

Atmospheric Measurement Techniques ◽

10.5194/amt-11-249-2018 ◽

2018 ◽

Vol 11 (1) ◽

pp. 249-263 ◽

Cited By ~ 13

Author(s):

Matthias Mauder ◽

Matthias J. Zeeman

Keyword(s):

Wind Speed ◽

Sonic Anemometer ◽

Three Dimensional ◽

Buoyancy Flux ◽

Horizontal Wind ◽

Horizontal Wind Speed ◽

Sonic Anemometers ◽

Adjacent Structures ◽

Mean Wind Speed ◽

Field Intercomparison

Abstract. Three-dimensional sonic anemometers are the core component of eddy covariance systems, which are widely used for micrometeorological and ecological research. In order to characterize the measurement uncertainty of these instruments we present and analyse the results from a field intercomparison experiment of six commonly used sonic anemometer models from four major manufacturers. These models include Campbell CSAT3, Gill HS-50 and R3, METEK uSonic-3 Omni, R. M. Young 81000 and 81000RE. The experiment was conducted over a meadow at the TERENO/ICOS site DE-Fen in southern Germany over a period of 16 days in June of 2016 as part of the ScaleX campaign. The measurement height was 3 m for all sensors, which were separated by 9 m from each other, each on its own tripod, in order to limit contamination of the turbulence measurements by adjacent structures as much as possible. Moreover, the high-frequency data from all instruments were treated with the same post-processing algorithm. In this study, we compare the results for various turbulence statistics, which include mean horizontal wind speed, standard deviations of vertical wind velocity and sonic temperature, friction velocity, and the buoyancy flux. Quantitative measures of uncertainty, such as bias and comparability, are derived from these results. We find that biases are generally very small for all sensors and all computed variables, except for the sonic temperature measurements of the two Gill sonic anemometers (HS and R3), confirming a known transducer-temperature dependence of the sonic temperature measurement. The best overall agreement between the different instruments was found for the mean wind speed and the buoyancy flux.

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Method for airborne measurement of the spatial wind speed distribution above complex terrain

Wind Energy Science ◽

10.5194/wes-6-427-2021 ◽

2021 ◽

Vol 6 (2) ◽

pp. 427-440

Author(s):

Christian Ingenhorst ◽

Georg Jacobs ◽

Laura Stößel ◽

Ralf Schelenz ◽

Björn Juretzki

Keyword(s):

Wind Speed ◽

Complex Terrain ◽

Wind Farm ◽

Three Dimensional ◽

High Sensitivity ◽

Spatial And Temporal Variability ◽

Speed Increase ◽

Airborne Measurement ◽

Ultrasonic Anemometer ◽

Mean Wind Speed

Abstract. Wind farm sites in complex terrain are subject to local wind phenomena, which have a relevant impact on a wind turbine's annual energy production. To reduce investment risk, an extensive site evaluation is therefore mandatory. Stationary long-term measurements are supplemented by computational fluid dynamics (CFD) simulations, which are a commonly used tool to analyse and understand the three-dimensional wind flow above complex terrain. Though under intensive research, such simulations still show a high sensitivity to various input parameters like terrain, atmosphere and numerical setup. In this paper, a different approach aims to measure instead of simulate wind speed deviations above complex terrain by using a flexible, airborne measurement system. An unmanned aerial vehicle is equipped with a standard ultrasonic anemometer. The uncertainty in the system is evaluated against stationary anemometer data at different heights and shows very good agreement, especially in mean wind speed (< 0.12 m s−1) and mean direction (< 2.4∘) estimation. A test measurement was conducted above a forested and hilly site to analyse the spatial and temporal variability in the wind situation. A position-dependent difference in wind speed increase of up to 30 % compared to a stationary anemometer is detected.

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Spreadsheet solution for the computation of the mean wind speed and turbulence intensity profiles according to the Romanian standard

E3S Web of Conferences ◽

10.1051/e3sconf/20198503002 ◽

2019 ◽

Vol 85 ◽

pp. 03002

Author(s):

Elena-Alexandra Chiulan ◽

Andrei-Mugur Georgescu ◽

Costin-Ioan Coşoiu ◽

Anton Anton

Keyword(s):

Wind Speed ◽

Turbulence Intensity ◽

Structural Design ◽

Input Data ◽

Wind Speed Profile ◽

Wind Action ◽

Design Engineers ◽

Mean Wind Speed ◽

Wind Characteristics ◽

The Mean

The presented paper focuses on the computation of the mean wind speed and turbulence intensity profiles for all the cities from Romania. The calculation of both, the mean wind speed profile and the turbulence intensity profile, had as mathematical support the equations presented in the Romanian design standard for wind action CR 1-1-4/2012. The main objective of this paper was to provide a tool for the computation of the two wind action features. This method was based on creating a spreadsheet in Excel with which, in just a few seconds, a user could correctly obtain the two wind characteristics. This Excel dashboard can be used as a teaching material for students as well as input data for structural design engineers in the process of modelling and observing the behaviour of a building excited by wind action on a particular city in Romania.

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Improving the Model Convective Storm Quantitative Precipitation Nowcasting by Assimilating State Variables Retrieved from Multiple-Doppler Radar Observations

Monthly Weather Review ◽

10.1175/mwr-d-13-00315.1 ◽

2014 ◽

Vol 142 (11) ◽

pp. 4017-4035 ◽

Cited By ~ 9

Author(s):

Yu-Chieng Liou ◽

Jian-Luen Chiou ◽

Wei-Hao Chen ◽

Hsin-Yu Yu

Keyword(s):

Data Assimilation ◽

Doppler Radar ◽

Scale Up ◽

Three Dimensional ◽

Radar Data ◽

State Variables ◽

Weather System ◽

Additional Information ◽

Convective Scale ◽

Fine Resolution

Abstract This research combines an advanced multiple-Doppler radar synthesis technique with the thermodynamic retrieval method, originally proposed by Gal-Chen, and a moisture/temperature adjustment scheme, and formulates a sequential procedure. The focus is on applying this procedure to improve the model quantitative precipitation nowcasting (QPN) skill in the convective scale up to 3 hours. A series of (observing system simulation experiment) OSSE-type tests and a real case study are conducted to investigate the performance of this algorithm under different conditions. It is shown that by using the retrieved three-dimensional wind, thermodynamic, and microphysical parameters to reinitialize a fine-resolution numerical model, its QPN skill can be significantly improved. Since the Gal-Chen method requires the horizontal average properties of the weather system at each altitude, utilization of in situ radiosonde(s) to obtain this additional information for the retrieval is tested. When sounding data are not available, it is demonstrated that using the model results to replace the role played by observing devices is also a feasible choice. The moisture field is obtained through a simple, but effective, adjusting scheme and is found to be beneficial to the rainfall forecast within the first hour after the reinitialization of the model. Since this algorithm retrieves the unobserved state variables instantaneously from the wind measurements and directly uses them to reinitialize the model, fewer radar data and a shorter model spinup time are needed to correct the rainfall forecasts, in comparison with other data assimilation techniques such as four-dimensional variational data assimilation (4DVAR) or ensemble Kalman filter (EnKF) methods.

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Intercomparisons of Tropospheric Wind Velocities Measured by Multi-Frequency Wind Profilers and Rawinsonde

Atmosphere ◽

10.3390/atmos12101284 ◽

2021 ◽

Vol 12 (10) ◽

pp. 1284

Author(s):

Zhao-Yu Chen ◽

Yen-Hsyang Chu ◽

Ching-Lun Su

Keyword(s):

Wind Speed ◽

Three Dimensional ◽

Meridional Wind ◽

Horizontal Wind ◽

Wind Component ◽

Horizontal Wind Speed ◽

Order Of Magnitude ◽

Wind Velocities ◽

Mean Square Difference ◽

Wind Profilers

Concurrent measurements of three-dimensional wind velocities made with three co-located wind profilers operated at frequencies of 52 MHz, 449 MHz, and 1.29 GHz for the period 12–16 September 2017 are compared for the first time in this study. The velocity–azimuth display (VAD) method is employed to estimate the wind velocities. The result shows that, in the absence of precipitation, the root mean square difference (RMSD) in the horizontal wind speed velocities U and wind directions D between different pairs of wind profilers are, respectively, in the range of 0.94–0.99 ms−1 and 7.7–8.3°, and those of zonal wind component u and meridional wind component v are in the respective ranges of 0.91–1.02 ms−1 and 1.1–1.24 ms−1. However, the RMSDs between wind profilers and rawinsonde are in the range of 2.89–3.26 ms−1 for horizontal wind speed velocity and 11.17–14.48° for the wind direction, which are around 2–3 factors greater than those between the wind profilers on average. In addition to the RMSDs, MDs between wind profilers and radiosonde are around one order of magnitude larger than those between wind profilers. These results show that the RMSDs, MDs, and Stdds between radars are highly consistent with each other, and they are much smaller than those between radar and rawinsonde. This therefore suggests that the wind profiler-measured horizontal wind velocities are much more reliable, precise, and accurate than the rawinsonde measurement.

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More accurate aeroelastic wind-turbine load simulations using detailed inflow information

10.5194/wes-2018-4 ◽

2018 ◽

Author(s):

Mads Mølgaard Pedersen ◽

Torben Juul Larsen ◽

Helge Aagaard Madsen ◽

Gunner Christian Larsen

Keyword(s):

Wind Speed ◽

Turbulence Intensity ◽

Atmospheric Stability ◽

Pitot Tube ◽

Aerodynamic Model ◽

Mean Wind Speed ◽

Fatigue Loads ◽

Aeroelastic Simulations ◽

The One ◽

Measured Wind Speed

Abstract. In this paper, inflow information is extracted from a measurement database and used for aeroelastic simulations to investigate if using more accurate inflow descriptions improves the accuracy of the simulated fatigue loads. The inflow information is extracted from the nearby met masts and a blade-mounted five-hole pitot tube. The met masts provide measurements of the inflow at fixed positions some distance away, whereas the pitot tube measures the inflow while rotating with the rotor. The met mast measures the free-inflow velocity, but the measured turbulence may evolve on its way to the turbine, pass besides the turbine, or the mast may be in the wake of the turbine. The inflow measured by the pitot tube, on the other hand, is very representative of the wind that acts on the turbine as it is measured close to the blades and includes variations within the rotor plane. This inflow is, however, affected by the presence of the turbine, and therefore an aerodynamic model is used to estimate the free-inflow velocities that would have been at the same time and position without the presence of the turbine. The inflow information used for the simulations includes the mean wind speed and trend, the turbulence intensity, wind shear profile, atmospheric stability dependent turbulence parameters, and azimuthal variations within the rotor plane. In addition, the instantly measured wind speed is used to constrain the turbulence. It is concluded that the period-specific turbulence intensity must be included in the aeroelastic simulations to make the range of the simulated fatigue loads representative for the range of the measured fatigue loads. Furthermore, it is found that the one-to-one correspondence between the measured and simulated fatigue loads is improved considerably by using inflow characteristics extracted from the pitot tube instead of the met-mast-based sensors as input for the simulations. Finally, the use of pitot-tube wind speed to constrain the turbulence is found to decrease the variation of the simulated loads due to different turbulence realisations (seeds), such that the need for multiple simulations is reduced.

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Characteristics of Typhoon “Fung-Wong” Near Earth Pulsation

Shock and Vibration ◽

10.1155/2021/9972981 ◽

2021 ◽

Vol 2021 ◽

pp. 1-12

Author(s):

Xiujun Li ◽

Yongguang Li ◽

Jianting Zhou ◽

Qian Wang ◽

Xu Wang

Keyword(s):

Wind Speed ◽

Turbulence Intensity ◽

Wind Field ◽

Coherence Function ◽

Intensity Attenuation ◽

Gust Factor ◽

Peak Factor ◽

Mean Wind Speed ◽

Wind Characteristic ◽

Empirical Curve

To study the wind field characteristics near the ground pulsation in typhoon conditions, wind field conditions in the area affected by Typhoon “Fung-Wong” were monitored using wind field instruments installed in the construction building of Wenzhou University, China. Real-time wind field data were collected during typhoons. Wind characteristic parameters such as mean wind speed, wind direction angle, turbulence intensity, gust factor, peak factor, coherence function, and autocorrelation were analyzed, and the wind field characteristics during the typhoon were summarized. The results indicated that the longitudinal and lateral turbulence intensities decreased with an increase in the mean wind speed, and there was an obvious linear relationship between them. The vertical and horizontal gust factor and peak factor decreased with an increase in mean wind speed, and the trend was more obvious in the horizontal direction. There was a significant correlation between the gust factor and the peak factor. The turbulence intensity and gust factor decreased with time, and the turbulence intensity attenuation speed increased with time. The empirical curve presented by Davenport (1961) can simulate the correlation characteristics of the fluctuating wind speed components of Typhoon Fung-Wong at some measuring points. With an increase in the time difference, the dependence of the instantaneous values at the two time points gradually decreased.

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Aero-elastic load validation in wake conditions using nacelle-mounted lidar measurements

10.5194/wes-2020-8 ◽

2020 ◽

Author(s):

Davide Conti ◽

Nikolay Dimitrov ◽

Alfredo Peña

Keyword(s):

Wind Speed ◽

Wind Turbine ◽

Turbulence Intensity ◽

Sensor Data ◽

Wave System ◽

Horizontal Shear ◽

Reference Case ◽

Elastic Load ◽

Lidar Measurements ◽

Mean Wind Speed

Abstract. We propose a method for carrying out wind turbine load validation in wake conditions using measurements from forward-looking nacelle lidars. Two lidars, a pulsed and a continuous wave system, were installed on the nacelle of a 2.3 MW wind turbine operating in free-, partial- and full-wake conditions. The turbine is placed within a straight row of turbines with a spacing of 5.2 rotor diameters and wake disturbances are present for two opposite wind direction sectors. We account for wake-induced effects by means of wind field parameters commonly used as inputs for load simulations, which are reconstructed using lidar measurements. These include mean wind speed, turbulence intensity, vertical and horizontal shear, yaw error and turbulence-spectra parameters. The uncertainty and bias of aero-elastic load predictions are quantified against wind turbine on-board sensor data. We consider mast-based load assessments in free wind as a reference case and assess the uncertainty in lidar-based power and load predictions when the turbine is operating in partial- and full-wake. Compared to the reference case, the simulations in wake conditions lead to an increase of the relative error as low as 4 %. It is demonstrated that the mean wind speed, turbulence intensity and turbulence length scale have a significant impact on the predictions. Finally, the experiences from this study indicate that characterizing turbulence inside the wake as well as defining a rotor equivalent wind speed model are the most challenging aspects of load validation in wake conditions.

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