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

Atmosphere ◽  
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.

scholarly journals Field intercomparison of prevailing sonic anemometers

2018 ◽  
Vol 11 (1) ◽  
pp. 249-263 ◽  
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.

scholarly journals Field intercomparison of prevailing sonic anemometers

2017 ◽  
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.

Wind Retrieval Algorithms for the IWRAP and HIWRAP Airborne Doppler Radars with Applications to Hurricanes

2014 ◽  
Vol 31 (6) ◽  
pp. 1189-1215 ◽  
Author(s):  
Stephen R. Guimond ◽  
Lin Tian ◽  
Gerald M. Heymsfield ◽  
Stephen J. Frasier
Keyword(s):  
Wind Speed ◽  
Least Squares ◽  
Meridional Wind ◽  
Solution Procedure ◽  
Measured Data ◽  
Horizontal Wind ◽  
Random Errors ◽  
Dual Frequency ◽  
Horizontal Wind Speed ◽  
Hurricane Wind

Abstract Algorithms for the retrieval of atmospheric winds in precipitating systems from downward-pointing, conically scanning airborne Doppler radars are presented. The focus is on two radars: the Imaging Wind and Rain Airborne Profiler (IWRAP) and the High-Altitude IWRAP (HIWRAP). The IWRAP is a dual-frequency (C and Ku bands), multibeam (incidence angles of 30°–50°) system that flies on the NOAA WP-3D aircraft at altitudes of 2–4 km. The HIWRAP is a dual-frequency (Ku and Ka bands), dual-beam (incidence angles of 30° and 40°) system that flies on the NASA Global Hawk aircraft at altitudes of 18–20 km. Retrievals of the three Cartesian wind components over the entire radar sampling volume are described, which can be determined using either a traditional least squares or variational solution procedure. The random errors in the retrievals due to the airborne radar geometry and noise in the Doppler velocities are evaluated using both an error propagation analysis with least squares theory and a numerical simulation of a hurricane. These analyses show that the vertical and along-track wind errors have strong across-track dependence with values ranging from 0.25 m s−1 at nadir to 2.0 and 1.0 m s−1 at the swath edges, respectively. The average across-track wind errors are ~2.5 m s−1 or 7% of the hurricane wind speed. For typical rotated figure-four flight patterns through hurricanes, the zonal and meridional wind speed errors are ~1.5–2.0 m s−1. Evaluations of both retrieval methods show that the variational procedure is generally preferable to the least squares procedure. Examples of measured data retrievals from IWRAP during an eyewall replacement cycle in Hurricane Isabel (2003) and from HIWRAP during the development of Tropical Storm Matthew (2010) are shown. Comparisons of IWRAP-measured data retrievals at nadir to flight-level data show errors of ~2.0 m s−1 for vertical winds and ~4.0 m s−1 for horizontal wind speed (~7% of the hurricane wind speed). Additional sources of error, such as hydrometeor fall speed uncertainties and a small height offset in the comparisons, are likely responsible for the larger vertical wind errors when compared to the simulated error analyses.

scholarly journals Winds in the Lower Cloud Level on the Nightside of Venus from VIRTIS-M (Venus Express) 1.74 μm Images

Atmosphere ◽  
2021 ◽  
Vol 12 (2) ◽  
pp. 186
Author(s):  
Dmitry A. Gorinov ◽  
Ludmila V. Zasova ◽  
Igor V. Khatuntsev ◽  
Marina V. Patsaeva ◽  
Alexander V. Turin
Keyword(s):  
Wind Speed ◽  
Meridional Wind ◽  
Equatorial Region ◽  
Hadley Cell ◽  
Horizontal Wind ◽  
Simultaneous Increase ◽  
Volcanic Area ◽  
Infrared Thermal Imaging ◽  
Latitude Range ◽  
Lower Cloud

The horizontal wind velocity vectors at the lower cloud layer were retrieved by tracking the displacement of cloud features using the 1.74 µm images of the full Visible and InfraRed Thermal Imaging Spectrometer (VIRTIS-M) dataset. This layer was found to be in a superrotation mode with a westward mean speed of 60–63 m s−1 in the latitude range of 0–60° S, with a 1–5 m s−1 westward deceleration across the nightside. Meridional motion is significantly weaker, at 0–2 m s−1; it is equatorward at latitudes higher than 20° S, and changes its direction to poleward in the equatorial region with a simultaneous increase of wind speed. It was assumed that higher levels of the atmosphere are traced in the equatorial region and a fragment of the poleward branch of the direct lower cloud Hadley cell is observed. The fragment of the equatorward branch reveals itself in the middle latitudes. A diurnal variation of the meridional wind speed was found, as east of 21 h local time, the direction changes from equatorward to poleward in latitudes lower than 20° S. Significant correlation with surface topography was not found, except for a slight decrease of zonal wind speed, which was connected to the volcanic area of Imdr Regio.

scholarly journals A Wind Study of Venus’s Cloud Top: New Doppler Velocimetry Observations

Atmosphere ◽  
2020 ◽  
Vol 12 (1) ◽  
pp. 2
Author(s):  
Ruben Gonçalves ◽  
Pedro Machado ◽  
Thomas Widemann ◽  
Francisco Brasil ◽  
José Ribeiro
Keyword(s):  
Spatial Variability ◽  
Local Time ◽  
Zonal Wind ◽  
Meridional Wind ◽  
Space Mission ◽  
Horizontal Wind ◽  
Doppler Velocimetry ◽  
Middle Latitudes ◽  
Wind Velocities ◽  
Wind Stability

At Venus’s cloud top, the circulation is dominated by the superroration, where zonal wind speed peaks at ∼100 ms−1, in the low-to-middle latitudes. The constraining of zonal and meridional circulations is essential to understanding the mechanisms driving the superrotation of Venus’s atmosphere, which are still poorly understood. We present new Doppler velocimetry measurements of horizontal wind velocities at Venus’s cloud top, around 70 km altitude. These results were based on March 2015 observations at the Canada–France–Hawaii Telescope (CFHT, Mauna Kea, Hawaii), using ESPaDOnS. The Doppler velocimetry method used has already successfully provided zonal and meridional results in previous works led by P. Machado and R. Gonçalves, proving to be a good reference ground-based technique in the study of the dynamics of Venus’s atmosphere. These observations were carried out between 27 and 29 March 2015, using the Echelle SpectroPolarimetric Device for the Observation of Stars (ESPaDOnS) which provides simultaneous visible-near IR spectra from 370 to 1050 nm, with a spectral resolution of 81000 allowing wind field characterization in the scattered Franuhofer solar lines by Venus’s cloud top on the dayside. The zonal velocities are consistent with previous results while also showing evidence of spatial variability, along planetocentric latitude and longitude (local-time). The meridional wind circulation presents a notably constant latitudinal structure with null velocities at lower latitudes, below 10∘ N–S, and peak velocities of ∼30 ms−1, centered around 35∘ N–S. The uncertainty of the meridional wind results from ground observations is of the same order as the uncertainty of meridional wind retrieved by space-based observations using cloud-tracking, as also shown by previous work led by R. Gonçalves and published in 2020. These March 2015 measurements present a unique and valuable contribution to the study of horizontal wind at the cloud top, from a period when Doppler velocimetry was the only available method to do so, since no space mission was orbiting Venus between Venus Express ending in January 2015 and Akatsuki’s orbit insertion in December 2015. These results from new observations provide (1) constraints on zonal wind temporal and spatial variability (latitude and local time), (2) constraints on the meridional wind latitudinal profile, (3) additional evidence of zonal and meridional wind stability for the period between 2011 and 2015 (along previous Doppler results) (4) further evidence of the consistency and robustness of our Doppler velocimetry method.

scholarly journals Doppler wind lidar activities at Cabauw

2021 ◽  
Author(s):  
Steven Knoop ◽  
Fred Bosveld ◽  
Marijn de Haij ◽  
Arnoud Apituley
Keyword(s):  
Wind Speed ◽  
Wind Profile ◽  
Continuous Wave ◽  
Wind Farms ◽  
Data Availability ◽  
Horizontal Wind ◽  
Horizontal Wind Speed ◽  
Low Clouds ◽  
Wind Measurements ◽  
Wind Lidar

<p>Atmospheric motion and turbulence are essential parameters for weather and topics related to air quality. Therefore, wind profile measurements play an important role in atmospheric research and meteorology. One source of wind profile data are Doppler wind lidars, which are laser-based remote sensing instruments that measure wind speed and wind direction up to a few hundred meters or even a few kilometers. Commercial wind lidars use the laser wavelength of 1.5 µm and therefore backscatter is mainly from aerosols while clear air backscatter is minimal, limiting the range to the boundary layer typically.</p><p>We have carried out a two-year intercomparison of the ZephIR 300M (ZX Lidars) short-range wind lidar and tall mast wind measurements at Cabauw [1]. We have focused on the (height-dependent) data availability of the wind lidar under various meteorological conditions and the data quality through a comparison with in situ wind measurements at several levels in the 213m tall meteorological mast. We have found an overall availability of quality-controlled wind lidar data of 97% to 98 %, where the missing part is mainly due to precipitation events exceeding 1 mm/h or fog or low clouds below 100 m. The mean bias in the horizontal wind speed is within 0.1 m/s with a high correlation between the mast and wind lidar measurements, although under some specific conditions (very high wind speed, fog or low clouds) larger deviations are observed. This instrument is being deployed within North Sea wind farms.</p><p>Recently, a scanning long-range wind lidar Windcube 200S (Leosphere/Vaisala) has been installed at Cabauw, as part of the Ruisdael Observatory program [2]. The scanning Doppler wind lidars will provide detailed measurements of the wind field, aerosols and clouds around the Cabauw site, in coordination with other instruments, such as the cloud radar.</p><p>[1] Knoop, S., Bosveld, F. C., de Haij, M. J., and Apituley, A.: A 2-year intercomparison of continuous-wave focusing wind lidar and tall mast wind measurements at Cabauw, Atmos. Meas. Tech., 14, 2219–2235, 2021</p><p>[2] https://ruisdael-observatory.nl/</p>

scholarly journals Comparison of Large Eddy Simulations of a convective boundary layer with wind LIDAR measurements

2012 ◽  
Vol 8 (1) ◽  
pp. 83-86 ◽  
Author(s):  
J. G. Pedersen ◽  
M. Kelly ◽  
S.-E. Gryning ◽  
R. Floors ◽  
E. Batchvarova ◽  
...  
Keyword(s):  
Boundary Layer ◽  
Wind Speed ◽  
Geostrophic Wind ◽  
Large Eddy Simulations ◽  
Horizontal Wind ◽  
Convective Boundary ◽  
Horizontal Wind Speed ◽  
Large Eddy ◽  
Lidar Measurements ◽  
Wind Lidar

Abstract. Vertical profiles of the horizontal wind speed and of the standard deviation of vertical wind speed from Large Eddy Simulations of a convective atmospheric boundary layer are compared to wind LIDAR measurements up to 1400 m. Fair agreement regarding both types of profiles is observed only when the simulated flow is driven by a both time- and height-dependent geostrophic wind and a time-dependent surface heat flux. This underlines the importance of mesoscale effects when the flow above the atmospheric surface layer is simulated with a computational fluid dynamics model.

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

2019 ◽  
Vol 76 (11) ◽  
pp. 3455-3484 ◽  
Author(s):  
Carsten Abraham ◽  
Adam H. Monahan
Keyword(s):  
Wind Speed ◽  
Turbulence Intensity ◽  
Three Dimensional ◽  
Static Stability ◽  
Wind Component ◽  
State Variables ◽  
Intermittent Turbulence ◽  
Additional Information ◽  
State Variable ◽  
Mean Wind Speed

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.

scholarly journals Three-Dimensional Simulation of Wind-Driven Ventilation Through a Windcatcher With Different Inlet Designs

2019 ◽  
Vol 12 (4) ◽  
Author(s):  
Peter Abdo ◽  
Rahil Taghipour ◽  
B. Phuoc Huynh
Keyword(s):  
Wind Speed ◽  
Average Velocity ◽  
Natural Ventilation ◽  
Ventilation System ◽  
Three Dimensional ◽  
Cfd Modeling ◽  
Ansys Fluent ◽  
Wind Velocities ◽  
Dimensional Simulation ◽  
Convergent Inlet

Abstract Windcatcher is an effective natural ventilation system, and its performance depends on several factors including wind speed and wind direction. It provides a comfortable and healthy indoor environment since the introduced fresh air decreases the moisture content and reduces the pollutant concentration. Since the wind speed and its direction are generally unpredictable, it is important to use special inlet forms and exits to increase the efficiency of a windcatcher. In this study, computational fluid dynamics (CFD) modeling is implemented using ansys fluent to investigate the airflow entering a three-dimensional room through a windcatcher with different inlet designs. Three designs are studied which are a uniform inlet, a divergent inlet, and a bulging-convergent inlet. The airflow pattern with all inlets provided adequate ventilation through the room. With all the applied wind velocities (1, 2, 3, and 6 m/s) at the domain's inlet, the divergent inlet shape has captured the highest airflow through the room and provided higher average velocity at 1.2 m high enhancing the thermal comfort where most of the human occupancy occurs. With 6 m/s wind velocity, the divergent inlet has captured 2.55% more flow rate compared to the uniform inlet and 4.70% compared to the bulging-convergent inlet, and it has also provided an average velocity at 1.2 m high in the room of 7.16% higher than the uniform inlet and 8.44% higher than the bulging-convergent inlet.

scholarly journals The Temporal Autocorrelation Structure of Sea Surface Winds

2012 ◽  
Vol 25 (19) ◽  
pp. 6684-6700 ◽  
Author(s):  
Adam H. Monahan
Keyword(s):  
Wind Speed ◽  
Zonal Wind ◽  
Large Scale ◽  
Strong Dependence ◽  
Meridional Wind ◽  
Sea Surface ◽  
Small Scale ◽  
Wind Component ◽  
Temporal Autocorrelation ◽  
Vector Wind

Abstract The temporal autocorrelation structures of sea surface vector winds and wind speeds are considered. Analyses of scatterometer and reanalysis wind data demonstrate that the autocorrelation functions (acf) of surface zonal wind, meridional wind, and wind speed generally drop off more rapidly in the midlatitudes than in the low latitudes. Furthermore, the meridional wind component and wind speed generally decorrelate more rapidly than the zonal wind component. The anisotropy in vector wind decorrelation scales is demonstrated to be most pronounced in the storm tracks and near the equator, and to be a feature of winds throughout the depth of the troposphere. The extratropical anisotropy is interpreted in terms of an idealized kinematic eddy model as resulting from differences in the structure of wind anomalies in the directions along and across eddy paths. The tropical anisotropy is interpreted in terms of the kinematics of large-scale equatorial waves and small-scale convection. Modeling the vector wind fluctuations as Gaussian, an explicit expression for the wind speed acf is obtained. This model predicts that the wind speed acf should decay more rapidly than that of at least one component of the vector winds. Furthermore, the model predicts a strong dependence of the wind speed acf on the ratios of the means of vector wind components to their standard deviations. These model results are shown to be broadly consistent with the relationship between the acf of vector wind components and wind speed, despite the presence of non-Gaussian structure in the observed surface vector winds.

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