Statistical study of coherent turbulent structures properties observed by a Doppler lidar over Paris during two months

2020 ◽  
Author(s):  
Ioannis Cheliotis ◽  
Elsa Dieudonné ◽  
Hervé Delbarre ◽  
Anton Sokolov ◽  
Egor Dmitriev ◽  
...  
Keyword(s):  
Wind Speed ◽  
Wind Field ◽  
Elevation Angle ◽  
Horizontal Surface ◽  
City Centre ◽  
Physical Parameters ◽  
Wind Fields ◽  
Turbulent Structures ◽  
Short Period ◽  
Synoptic Wind

<p>Pulsed Doppler wind lidars (PDWL) have been extensively used in order to study the atmospheric turbulence. Their ability to scan large areas in a short period of time is a substantial advantage over in-situ measurements. Furthermore, PDWL are capable to scan horizontally as well as vertically thus providing observations throughout the atmospheric boundary layer (ABL). By analysing PDWL observations it is possible to identify large turbulent structures in the ABL such as thermals, rolls and streaks. Even though several studies have been carried out to analyse such turbulent structures, these studies examine peculiar cases spanning over short periods of time.</p><p>For this study we analysed the turbulent structures (thermals, rolls, streaks) over Paris during a two-months period (4 September – 6 October 2014, VEGILOT campaign) observed with a PDWL installed on a 70 m tower in Paris city centre. The turbulent radial wind field was reconstructed from the radial wind field of the horizontal surface scans (1° elevation angle) by using the velocity azimuth display method. The VEGILOT campaign provided 4577 horizontal surface scans, hence for the classification of the turbulent structures we developed an automatic method based on texture analysis and machine learning of the turbulent radial wind fields. Thirty characteristic cases of each turbulent structure types were selected at the learning step after an extensive examination of the meteorological parameters. Rolls cases were selected at the same time that cloud streets were visible on satellite images, streaks cases were selected during high wind shear development near the surface and thermals case were selected when solar radiation measurements in the area were high. In addition, sixty cases of “others”, representing any other type of turbulence, were added to the training ensemble. The analysis of errors estimated by the cross-validation shows that the K-nearest neighbours’ algorithm was able to classify accurately 96.3% of these 150 cases. Subsequently the algorithm was applied to the whole dataset of 4577 scans. The results show 52% of the scans classified as containing turbulent structures with 33% being coherent turbulent structures (22% streaks, 11% rolls).</p><p>Based on this classification, the physical parameters associated with the different types of turbulent structures were determined, e.g. structure size, ABL height, synoptic wind speed, vertical wind speed. Range height indicator and line of sight scans provided vertical observations that illustrate the presence of vertical motions during the observation of turbulent structures. The structure sizes were retrieved from the spectral analysis in the transverse direction relative to the synoptic wind, and are in agreement with the commonly observed sizes (a few 100 m for streaks, a few km for rolls).</p>

Simulation of the wind fields over complex terrain with coupling of CFD and WRF

2021 ◽  
pp. 1-12
Author(s):  
Xiaoyu Luo ◽  
Yiwen Cao
Keyword(s):  
Wind Speed ◽  
Wind Field ◽  
Complex Terrain ◽  
Civil Engineering ◽  
Meteorological Data ◽  
Mass Conservation ◽  
Coupling Method ◽  
Wind Fields ◽  
Civil Structures ◽  
Civil Engineers

In the field of civil engineering, the meteorological data available usually do not have the detailed information of the wind near a certain site. However, the detailed information of the wind field during typhoon is important for the wind-resistant design of civil structures. Furthermore, the resolution of the meteorological data available by the civil engineers is too coarse to be applicable. Therefore it is meaningful to obtain the detailed information of the wind fields based on the meteorological data provided by the meteorological department. Therefore, in the present study, a one-way coupling method between WRF and CFD is adopted and a method to keep the mass conservation during the simulation in CFD is proposed. It is found that using the proposed one-way coupling method, the predicted wind speed is closer to the measurement. And the curvature of the wind streamline during typhoon is successfully reproduced.

Quantification of NOX Emissions Based on Car MAX-DOAS Measurements over Beijing and Impacts of Wind Field

2020 ◽  
Author(s):  
Xinghong Cheng
Keyword(s):  
Spatial Distribution ◽  
Wind Speed ◽  
Wind Field ◽  
Meteorological Condition ◽  
Emission Rates ◽  
Wind Fields ◽  
Vertical Column ◽  
Wind Speeds ◽  
South Central ◽  
The Mean

<p>We carried out 14 days of Car MAX-DOAS experiments on the 6th Ring Rd of Beijing in January, September and October, 2014. The tropospheric vertical column densities (VCD) of NO<sub>2</sub> are retrieved and used to estimate the emissions of NO<sub>x</sub>. The offline LAPS-WRF-CMAQ model system is used to simulate wind fields by assimilation of observational data and calculate the NO<sub>2</sub> to NO<sub>x</sub> concentration ratios. The NO<sub>X</sub> emissions in Beijing for different seasons derived from Car MAX-DOAS measurements are compared with the multi-resolution emission inventory in China for 2012 (MEIC 2012), and impacts of wind field on estimated emissions and its uncertainties are also investigated. Results show that the NO<sub>2</sub> VCD is higher in January than other two months and it is typically larger at the southern parts of the 6th Ring Road than the northern parts of it. Wind field has obvious impacts on the spatial distribution of NO<sub>2</sub> VCD, and the mean NO<sub>2</sub> VCD with south wind at most sampling points along the 6th Ring Rd is higher than north wind. The journey-to-journey variation pattern of estimated NO<sub>X</sub> emissions rates (E<sub>NOX</sub>) is consistent with that of the NO<sub>2</sub> VCD, and E<sub>NOX </sub>is mainly determined by the NO2 VCD. In addition, the journey-to-journey E<sub>NOX</sub> in the same month is different and it is affected by wind speed, the ratio of NO<sub>2</sub> and NOx concentration and the decay rate of NO<sub>X</sub> from the emission sources to measured positions under different meteorological condition. The E<sub>NOX</sub> ranges between 6.46×10<sup>25</sup> and 50.05×10<sup>25</sup> molec s<sup>-1</sup>. The averaged E<sub>NOX</sub> during every journey in January, September and October are respectively 35.87×10<sup>25</sup>, 20.34×10<sup>25</sup>, 8.96×10<sup>25</sup> molec s<sup>-1</sup>. The estimated E<sub>NOX</sub> after removing the simulated error of wind speed and observed deviation of NO<sub>2</sub> VCD are found to be mostly closer to the MEIC 2012, but sometimes E<sub>NOX </sub>is lower or higher and it indicates that the MEIC 2012 might be overestimate or underestimate the true emissions. The estimated E<sub>NOX</sub> on January 27 and September 19 are obviously higher than other journeys in the same month because the mean NO<sub>2</sub> VCD and Leighton ratio during these two periods are larger, and corresponding wind speeds are smaller. Additionally, because south wind may affect the spatial distribution of mean NO<sub>2</sub> VCD in Beijing which is downwind of south-central regions of Hebei province with high source emission rates, the uncertainty of the estimated E<sub>NOX</sub> with south wind will be increased.</p>

Wind tunnel tests on the characteristics of wind fields over a simplified gorge

2016 ◽  
Vol 20 (10) ◽  
pp. 1599-1611 ◽  
Author(s):  
Peng Hu ◽  
Yongle Li ◽  
Yan Han ◽  
CS Cai ◽  
Guoji Xu
Keyword(s):  
Wind Speed ◽  
Wind Tunnel ◽  
Wind Direction ◽  
Wind Field ◽  
Small Range ◽  
Wind Fields ◽  
Wind Speeds ◽  
Mean Wind Speed ◽  
Wind Characteristics ◽  
The Mean

Characteristics of wind fields over the gorge or valley terrains are becoming more and more important to the structural wind engineering. However, the studies on this topic are very limited. To obtain the fundamental characteristics information about the wind fields over a typical gorge terrain, a V-shaped simplified gorge, which was abstracted from some real deep-cutting gorges where long-span bridges usually straddle, was introduced in the present wind tunnel studies. Then, the wind characteristics including the mean wind speed, turbulence intensity, integral length scale, and the wind power spectrum over the simplified gorge were studied in a simulated atmospheric boundary layer. Furthermore, the effects of the oncoming wind field type and oncoming wind direction on these wind characteristics were also investigated. The results show that compared with the oncoming wind, the wind speeds at the gorge center become larger, but the turbulence intensities and the longitudinal integral length scales become smaller. Generally, the wind fields over the gorge terrain can be approximately divided into two layers, that is, the gorge inner layer and the gorge outer layer. The different oncoming wind field types have remarkable effects on the mean wind speed ratios near the ground. When the angle between the oncoming wind and the axis of the gorge is in a certain small range, such as smaller than 10°, the wind fields are very close to those associated with the wind direction of 0°. However, when the angle is in a larger range, such as larger than 20°, the wind fields in the gorge will significantly change. The research conclusions can provide some references for civil engineering practices regarding the characteristics of wind fields over the real gorge terrains.

scholarly journals Detecting turbulent structures on single Doppler lidar large datasets: an automated classification method for horizontal scans

2020 ◽  
Author(s):  
Ioannis Cheliotis ◽  
Elsa Dieudonné ◽  
Hervé Delbarre ◽  
Anton Sokolov ◽  
Egor Dmitriev ◽  
...  
Keyword(s):  
Learning Algorithm ◽  
Large Datasets ◽  
Supervised Machine Learning ◽  
Classification Method ◽  
City Centre ◽  
Classification Error ◽  
Doppler Lidar ◽  
Automated Classification ◽  
Wind Fields ◽  
Turbulent Structures

Abstract. Turbulent structures can be observed using horizontal scans from single Doppler lidar or radar systems. Despite the ability to detect the structures manually on the images, this method would be time-consuming on large datasets, thus limiting the possibilities to perform studies of the turbulent structures properties over more than a few days. In order to overcome this problem, an automated classification method was developed, based on the observations recorded by a scanning Doppler lidar (LEOSPHERE WLS100) and installed atop a 75-m tower in Paris city centre (France) during a 2-months campaign (September-October 2014). The lidar recorded 4577 quasi-horizontal scans for which the turbulent component of the radial wind speed was determined using the velocity azimuth display method. Three turbulent structures types were identified by visual examination of the wind fields: unaligned thermals, rolls and streaks. A learning ensemble of 150 turbulent patterns was classified manually relying on in-situ and satellite data. The differences between the three types of structures were highlighted by enhancing the contrast of the images and computing four texture parameters (correlation, contrast, homogeneity and energy) that were provided to the supervised machine learning algorithm (quadratic discriminate analysis). Using the 10-fold cross validation method, the classification error was estimated to be about 9.2 % for the training ensemble and 3.3 % in particular for streaks. The trained algorithm applied to the whole scan ensemble detected turbulent structures on 54 % of the scans, among which 34 % were coherent turbulent structures (rolls, streaks).

scholarly journals Numerical Investigation of Typhoon Waves Generated by Three Typhoons in the China Sea

2019 ◽  
Author(s):  
Qing Shi ◽  
Jun Tang ◽  
Yongming Shen ◽  
Yuxiang Ma
Keyword(s):  
Wind Speed ◽  
Wind Field ◽  
Wave Model ◽  
Satellite Observations ◽  
Altimeter Data ◽  
Correction Coefficient ◽  
Wind Fields ◽  
China Sea ◽  
Wave Heights ◽  
Typhoon Waves

Abstract. The typhoon waves generated in the China Sea during the Chan-hom (1509), Linfa (1510) and Nangka (1511) typhoons that occurred in 2015 were numerically investigated. The wave model was based on the a third generation spectral wind-wave model SWAN, in which the wind fields for driving waves were derived from the ERA-interim (ECMWF), CFSv2 (The NCEP Climate Forecast System Version 2) and CCMP (Cross-Calibrated Multi-Platform) datasets. The numerical results were validated using buoy data and satellite observation data. The simulation results under the three types of wind fields were in good agreement with the observed data. The CCMP wind data was the best in simulating waves overall, and the wind speeds pertaining to ERA and CCMP were notably smaller than those observed near the typhoon centre. The Holland wind model was used to revise and optimize the wind speed pertaining to the CCMP near the typhoon centre, and the wind speed correction coefficient, correction formula and corresponding parameters were determined. Based on these findings, the CCMP and CCMP/Holland blended wind fields were used to simulate the typhoon waves generated during the Meranti (1614), Rai (1615) and Malakas (1616) typhoons that occurred in September 2016. A comparison between the simulated wave heights and those obtained from the Jason-2 altimeter data indicated that all correlation coefficients between the simulated values and the satellite observations were greater than 0.75. The blended wind field was better overall in simulating the wave heights. The simulated maximum wave heights were more similar to the satellite observations, and the root mean square error of the blended wind field was 0.223 m lower than that of the CCMP. The results demonstrated that the CCMP wind-driven SWAN model could appropriately simulate the typhoon waves generated by three typhoons in China Sea, and the use of the CCMP/Holland blended wind field could effectively improve the accuracy of typhoon wave simulations.

scholarly journals Application of Variational Analysis of Wind Field Based on Lidar Conical Scans to Air Quality Monitoring

2010 ◽  
Vol 4 (1) ◽  
pp. 64-77 ◽  
Author(s):  
P. W. Chan ◽  
Frank Yu
Keyword(s):  
Wind Field ◽  
Variational Analysis ◽  
Elevation Angle ◽  
Quality Monitoring ◽  
Plume Dispersion ◽  
Doppler Lidar ◽  
Air Quality Monitoring ◽  
Velocity Data ◽  
Wind Fields ◽  
Radial Velocity Data

Conical scans of Doppler LIDAR were made at a specific elevation angle to monitor the wind fields in cases of plume dispersion in western Australia. To better visualize the airflow patterns in relation to the plume direction, variational analysis is performed on the radial velocity data of the LIDAR to retrieve the 2D wind fields. Compared to the 4DVAR method, the 2D variational analysis as adopted in the present paper is computationally more efficient yet provides sufficient details of the flow patterns. Examples of the plume dispersion are shown with the 2D analyzed wind fields as presented in the paper. In general, the analyzed wind fields are consistent with the plume directions as observed from the backscattered power data of the LIDAR.

scholarly journals Application of SAR Data for Tropical Cyclone Intensity Parameters Retrieval and Symmetric Wind Field Model Development

2021 ◽  
Vol 13 (15) ◽  
pp. 2902
Author(s):  
Yuan Gao ◽  
Jie Zhang ◽  
Jian Sun ◽  
Changlong Guan
Keyword(s):  
Wind Speed ◽  
Wind Field ◽  
Maximum Wind Speed ◽  
Wind Fields ◽  
Maximum Wind ◽  
Wind Field Model ◽  
Wind Speeds ◽  
Central Surface ◽  
Intensity Parameters ◽  
Wind Retrievals

The spaceborne synthetic aperture radar (SAR) is an effective tool to observe tropical cyclone (TC) wind fields at very high spatial resolutions. TC wind speeds can be retrieved from cross-polarization signals without wind direction inputs. This paper proposed methodologies to retrieve TC intensity parameters; for example, surface maximum wind speed, TC fullness (TCF) and central surface pressure from the European Space Agency Sentinel-1 Extra Wide swath mode cross-polarization data. First, the MS1A geophysical model function was modified from 6 to 69 m/s, based on three TC samples’ SAR images and the collocated National Oceanic and Atmospheric Administration stepped frequency microwave radiometer wind speed measurements. Second, we retrieved the wind fields and maximum wind speeds of 42 TC samples up to category 5 acquired in the last five years, using the modified MS1A model. Third, the TCF values and central surface pressures were calculated from the 1-km wind retrievals, according to the radial curve fitting of wind speeds and two hurricane wind-pressure models. Three intensity parameters were found to be dependent upon each other. Compared with the best-track data, the averaged bias, correlation coefficient (Cor) and root mean-square error (RMSE) of the SAR-retrieved maximum wind speeds were –3.91 m/s, 0.88 and 7.99 m/s respectively, showing a better result than the retrievals before modification. For central pressure, the averaged bias, Cor and RMSE were 1.17 mb, 0.77 and 21.29 mb and respectively, indicating the accuracy of the proposed methodology for pressure retrieval. Finally, a new symmetric TC wind field model was developed with the fitting function of the TCF values and maximum wind speeds, radial wind curve and the Rankine Vortex model. By this model, TC wind field can be simulated just using the maximum wind speed and the radius of maximum wind speed. Compared with wind retrievals, averaged absolute bias and averaged RMSE of all samples’ wind fields simulated by the new model were smaller than those of the Rankine Vortex model.

scholarly journals Evaluation and Post-Processing of Reanalysis Wind Speeds for Renewable Energy Applications

2021 ◽  
Author(s):  
Sebastian Brune ◽  
Jan D. Keller ◽  
Sabrina Wahl
Keyword(s):  
Boundary Layer ◽  
Wind Speed ◽  
Wind Turbine ◽  
Wind Field ◽  
Lower Boundary ◽  
Horizontal Resolution ◽  
Lower Atmosphere ◽  
Wind Fields ◽  
Wind Model ◽  
Lower Boundary Layer

<p>The correct spatio-temporal representation of wind speed is of large interest for the wind energy sector. Therefore, this study compares wind measurements in different heights from several locations in Central Europe with two global (ERA5, MERRA-2) and one regional reanalysis (COSMO-REA6). Employing a two-parameter Weibull distribution, the shape and scale parameters as well as mean, standard deviation and RMSE are investigated at and around common wind turbine hub height. We find that COSMO-REA6 best describes wind fields closer to the surface possibly due to its high horizontal resolution. Here, it also exhibits a good alignment with the diurnal cycle. However, for common wind turbine hub heights and above, ERA5 outperforms the other two reanalyses possibly due to its higher vertical resolution. MERRA-2 overestimates wind speed in the lower boundary layer at nearly all sites.</p><p>In the next step, a diagnostic and mass-consistent wind model is applied to the COSMO-REA6 wind field. The resolution of the wind field will be increased by a factor of 8 from originally 6 km to approximately 800 m. In addition to the vertical stability of the lower atmosphere, the orography on the finer grid and the corresponding effects are taken into account. We expect that especially in complex terrain the wind field will be corrected and thus should fit better to the observations. Channeling effects, shadowing and increased wind speed in exposed locations can be better represented. The new high-resolution wind field forms the basis for a statistical wind model to obtain post-processed wind estimates in the lower boundary layer. This approach will utilize generalized linear model and/or an artificial neural network techniques.</p>

Hindcasting Hurricane Waves in the Gulf of Mexico

1972 ◽  
Vol 12 (04) ◽  
pp. 321-328 ◽  
Author(s):  
M. M. Patterson
Keyword(s):  
Gulf Of Mexico ◽  
Wave Height ◽  
Wind Field ◽  
Design Theory ◽  
Time History ◽  
Wind Fields ◽  
Platform Design ◽  
Synoptic Wind ◽  
Storm Wave ◽  
Wave Heights

Abstract An estimate of wave heights is needed for risk and venture analysis, for platform design, and for operational planning. Very little reliable data on hurricane waves have been available for a number of years. The present hindcast system uses a moving, two-dimensional wind field to generates and propagate waves to a location of interest. The propagate waves to a location of interest. The wind-wave model is based on work reported in the literature by Wilson. Wave Program I uses a synoptic wind field based on measurements or observations. Wave Program II generates its own wind field based on the track, the time history of the radius to maximum Winds, and the barometric pressure of the storm. Wave Program III also pressure of the storm. Wave Program III also generates its own wind fields, but the storm is moved along a predetermined path. The results of all three hindcast methods have been compared with data gathered from Hurricane Carla. Other hurricanes have also been studied and each of the programs gives comparable results. programs gives comparable results Introduction The most critical environmental factor in deepwater platform design is the selection of wave heights to which the platform will be subjected. Regardless of the design theory, wave loading contributes a major portion of the environmental force on a deep-water platform. To date there has been little sound historical evidence of the magnitude of wave heights that could occur in the Gulf of Mexico. To overcome this problem the offshore oil industry has sought an answer by two related methods. The first method consists of several measuring programs to gather both wave force and wave height information. Since reliable measuring techniques have existed for only a short time, the second method consists of developing techniques to predict historical waves that probably occurred in the Gulf of Mexico. The purpose of this paper is to document Shell's efforts in hindcasting paper is to document Shell's efforts in hindcasting waves for hurricanes that have passed through the Gulf since 1900. In order to hindcast waves, it was necessary to find a mathematical simulation model that would generate waves from a moving wind field. Such wind fields may be taken from synoptic charts or developed from empirical equations based on hurricane data such as radius to maximum winds, central pressure, and forward speed. WAVES FROM A MOVING WIND FIELDTHE BASIC WILSON MODEL Wilson, a consultant in the field of oceanography, has developed a mathematical model that would generate and propagate waves based on a moving wind field. We shall discuss the basic equations for this technique, but shall not go into detail concerning how the equations were developed. INITIATION OF THE WAVE The first wave height generated by a moving wind field can be calculated from Eq. 1 below (1) H1 = 0 .0636U In the above equation Ui is the wind vector in the direction of propagation at time zero and location (x1) where the wave is to start. The distance x1 over which the wave will move is described in Eq. 2. (2) =  0 .761 x1 is the distance the wave travels in nautical miles before it is to be modified by another value of wind velocity. The celerity is defined by Eq. 3. (3) C1  =  2 .498 Finally, the period and wave length of this initial wave are described below. (4) T1  =  C1/3 (5)1 2L1  =  5 .12T SPEJ P. 321

scholarly journals Measurement of the Sea Surface Height with Airborne GNSS Reflectometry and Delay Bias Calibration

2021 ◽  
Vol 13 (15) ◽  
pp. 3014
Author(s):  
Feng Wang ◽  
Dongkai Yang ◽  
Guodong Zhang ◽  
Jin Xing ◽  
Bo Zhang ◽  
...  
Keyword(s):  
Wind Speed ◽  
Arrival Time ◽  
Elevation Angle ◽  
Satellite System ◽  
Sea Surface Height ◽  
Antenna Pattern ◽  
Sea Surface ◽  
Observation Method ◽  
Global Navigation Satellite ◽  
The Impact

Sea surface height can be measured with the delay between reflected and direct global navigation satellite system (GNSS) signals. The arrival time of a feature point, such as the waveform peak, the peak of the derivative waveform, and the fraction of the peak waveform is not the true arrival time of the specular signal; there is a bias between them. This paper aims to analyze and calibrate the bias to improve the accuracy of sea surface height measured by using the reflected signals of GPS CA, Galileo E1b and BeiDou B1I. First, the influencing factors of the delay bias, including the elevation angle, receiver height, wind speed, pseudorandom noise (PRN) code of GPS CA, Galileo E1b and BeiDou B1I, and the down-looking antenna pattern are explored based on the Z-V model. The results show that (1) with increasing elevation angle, receiver height, and wind speed, the delay bias tends to decrease; (2) the impact of the PRN code is uncoupled from the elevation angle, receiver height, and wind speed, so the delay biases of Galileo E1b and BeiDou B1I can be derived from that of GPS CA by multiplication by the constants 0.32 and 0.54, respectively; and (3) the influence of the down-looking antenna pattern on the delay bias is lower than 1 m, which is less than that of other factors; hence, the effect of the down-looking antenna pattern is ignored in this paper. Second, an analytical model and a neural network are proposed based on the assumption that the influence of all factors on the delay bias are uncoupled and coupled, respectively, to calibrate the delay bias. The results of the simulation and experiment show that compared to the meter-level bias before the calibration, the calibrated bias decreases the decimeter level. Based on the fact that the specular points of several satellites are visible to the down-looking antenna, the multi-observation method is proposed to calibrate the bias for the case of unknown wind speed, and the same calibration results can be obtained when the proper combination of satellites is selected.

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