Radial Wind Research Articles

Determination of eddy dissipation rate by Doppler lidar in Reykjavik, Iceland

AbstractThe temporal and spatial scale of atmospheric turbulence can be highly dynamic, requiring sophisticated methods for adequate detection and monitoring with high resolution. Doppler light detection and ranging (lidar) systems have been widely used to observe and monitor wind velocity and atmospheric turbulence profiles as Doppler lidar systems can provide continuous information about wind fields. The use of lidars in the subarctic region is particularly challenging as aerosol abundance can be very low, leading to weak backscatter signals. In the present study, we analysed data collected with a Leosphere Windcube 200S lidar system stationed in Reykjavik, Iceland, to estimate the eddy dissipation rate (EDR) as an indicator of turbulence intensity. For this purpose, we retrieved radial wind velocity observations from velocity–azimuth display scans and computed the EDR based on the Kolmogorov theory. We compared different noise filter thresholds, scan strategies and calculation approaches during typical Icelandic weather conditions to assess the accuracy and the uncertainty of our EDR estimations. The developed algorithm can process raw lidar observations, retrieve EDR and determine the qualitative distribution of the EDR. The processed lidar observations suggest that lidar observations can be of high importance for potential end‐users, for example air traffic controllers and aviation safety experts. The work is an essential step towards enhanced aviation safety in Iceland where aerosol concentration is in general low and severe turbulence occurs regularly.

Convective-Scale Sampling Error and Its Impact on the Ensemble Radar Data Assimilation System: A Case Study of a Heavy Rainfall Event on 16 June 2008 in Taiwan

ABSTRACT Sampling error stems from the use of ensemble-based data assimilation (EDA) with a limited ensemble size and can result in spurious background error covariances, leading to false analysis corrections. The WRF-LETKF radar assimilation system (WLRAS) is performed separately with 256 and 40 members to investigate the characteristics of convective-scale sampling errors in the EDA and its impact on precipitation prediction based on a heavy rainfall event on 16 June 2008. The results suggest that the sampling errors for this event are sensitive to the relationships between the simulated observations and model variables, the intensity of reflectivity, and how the prevailing wind projects to the radial wind in the areas that the radar cannot resolve U or V wind. The sampling errors lead to an underprediction of heavy rainfall when the horizontal localization radius is inadequately large, but this can be mitigated when a more accurate moisture condition is provided. In addition, being able to use a larger vertical localization plays an important role in providing necessary adjustments for representing the vertical thermodynamical structure of convection, which further improves precipitation prediction. A strategy mitigating the impact of sampling errors associated with the limitation of radial wind measurement by inflating the observation error over sensitive areas can bring benefits to precipitation prediction.

Mesocyclonic and non-mesocyclonic convective storms in Germany: Storm characteristics and life-cycle

A multi-year analysis of mesocyclonic (approximately 4300) and non-mesocyclonic convective storms (more than 100,000) is presented. A comprehensive data set is generated which includes measurements from a lightning location system, a precipitation radar network, as well as information from automated cell detection algorithms based on radar reflectivity and radial winds. Storms' rotation, reflectivity, lightning and motion characteristics are analysed for storms with different lifetimes. Furthermore, the temporal evolution of the storms' attributes is analysed in order to study the convective life-cycle. For this purpose, the storms are grouped according to their lifetime. The temporal evolution of storm attributes varies from one storm to the other, however, typical storm developments are revealed. The average temporal evolution of the storm size is symmetric, the maximum is reached at the half of the lifetime. In contrast, the maximum lightning rate is reached later. Comparing the attributes of non-mesocyclonic and mesocyclonic storms, varies differences are identified. Mesocyclonic storms are shown to be typically longer-living (the median is approximately 30 min longer), larger, faster moving (on average approximately 15 km/h faster) and electrically more active compared to non-mesocyclonic storms. These characteristics are more pronounced for stronger mesocyclonic storms.

A Study of the Interaction between Typhoon Francisco (2013) and a Cold-Core Eddy. Part II: Boundary Layer Structures

Abstract In Part II of this study, the influence of an oceanic cold-core eddy on the atmospheric boundary layer structures of Typhoon Francisco (2013) is investigated, as well as a comparison with the cold wake effect. Results show that the eddy induces shallower mixed-layer depth and forms stable boundary layer above and near it. The changes of these features shift from northwest to southeast across the storm eye, following the translation of Francisco over the eddy. Nonetheless, the decrease in mixed-layer depth and formation of stable boundary layer caused by the cold wake are located at right rear of the storm. The sensible heat fluxes at the lowest atmospheric model level are mostly downward over the sea surface cooling region. Due to their different relative locations with Francisco, the diabatic heating in the northwest quadrant of the storm can be more effectively inhibited by the cold-core eddy than by the cold wake. The asymmetric characteristics of surface tangential wind are less sensitive to sea surface cooling than those of surface radial wind, implying a change in surface inflow angle. Different from previous studies, the surface inflow angle is found to be reduced especially above the cold-core eddy and cold wake region. An analysis of radial wind tendency budget indicates that the decrease in radial pressure gradient is dominant in changing the acceleration rate of surface radial wind, rather than the decrease in the Coriolis and centrifugal forces, and therefore more outward surface flow is induced by both the cold-core eddy and cold wake.

(Non)radial Solar Wind Propagation through the Heliosphere

Abstract The solar wind nonradial velocity components observed beyond the Alfvén point are usually attributed to waves, the interaction of different streams, or other transient phenomena. However, Earth-orbiting spacecraft as well as monitors at L1 indicate systematic deviations of the wind velocity from the radial direction. Since these deviations are of the order of several degrees, the calibration of the instruments is often questioned. This paper investigates for the first time the evolution of nonradial components of the solar wind flow along the path from ≈0.17 to 10 au. A comparison of observations at 1 au with those closer to or farther from the Sun based on measurements of many spacecraft at different locations in the heliosphere (Parker Solar Probe, Helios 1 and 2, Wind, Advanced Composition Explorer, Spektr-R, Acceleration, Reconnection, Turbulence and Electrodynamics of the Moon’s Interaction with the Sun (ARTEMIS) probes, Mars Atmosphere and Volatile Evolution (MAVEN), Voyagers 1 and 2) shows that (i) the average values of nonradial components are not zero and vary in a systematic manner with the distance from the Sun and (ii) their values significantly depend on the solar wind radial velocity.

Assimilation of Radial Winds Over India Using a Community GSI Analysis System

With the modernization of the India Meteorological Department, the observational network of the country, both in situ and remote sensing, is enhanced. The Doppler Weather Radar (DWR) network is improved, and the National Centre for Medium Range Weather Forecasting is acquiring radar data from 20 stations all over the country. The maximum utilization of DWR observations in the numerical models remains a challenging task. This study represents the first assessment of assimilation of radial wind observations from all 20 DWR stations, utilizing the resources of weather research and a forecasting model with a community grid-point statistical interpolation system. DWR observations are an important data source for mesoscale and microscale weather analysis and forecasting because of their high temporal and spatial resolution. However, the representation of DWR radial wind and reflectivity in a desired format seems to be crucial in the modeling approach. A series of experiments are conducted to evaluate the sensitivity of the analysis to the velocity azimuth display quality control (VADQC) and without VADQC (VARQC) to understand the effect of QC on analysis. The statistical analysis of assimilation of DWR radial wind suggests that a gate distance of 250 m or its multiple is imperative for the setup of the DWR. Additionally, the density of the super-observation is amplified in the VARQC approach. The analysis procedure is implemented for the recent severe cyclone Phethai (December 2018) over the Bay of Bengal, and a few preliminary results are discussed.

Optimization of radial inflow wind turbines for urban wind energy harvesting

Radial (inflow) turbines with volutes have received limited attention in the body of literature for open-field wind harvesting. Few existing data in the literature indicate low maximum Cp, around 0.1. This study pursues demonstration of competitive radial wind turbines (RWT) towards exploring their potentials and increase the alternatives for a future urban energy planner. RWT may have advantages in adapting the renewable energy concept into buildings due to their an order-of-magnitude lower rotational speeds compared to propeller turbines, enclosed rotors and discharge of air uniquely from the top of the turbine (therefore the building). Moreover, such features may enable low-noise and fatigue-free rotors made of less durable but recyclable materials, crucial for acoustical comfort, safety and sustainability in urban areas. Design exploration over the complex 3D flowfield of the turbine is pursued by machine learning algorithms coupled with Computational Fluid Dynamics simulations. With the achieved peak Cp of 0.29 at Rec = 1.7 × 105, 103% improvement is attained relative to the existing RWTs with identical simulation methodologies. A sensitivity analysis revealed the most important parameters. The optimized turbine is compared with traditional alternatives, and it was elucidated that RWT is a competitive alternative among conventional alternatives with the described additional fundamental advantages.

Measurement and Prediction of Wind Fields at an Offshore Site by Scanning Doppler LiDAR and WRF

LiDAR-based wind speed measurements have seen a significant increase in interest in wind energy. However, reconstruction of wind speed vector from a LiDAR-measured radial wind speed is still a challenge. Furthermore, for extensive application of LiDAR technology, it can be used as a means to validate simulation and analytical models. To that end, this study employed scanning Doppler LiDAR for assessment of wind fields at an offshore site and compared Weather Research and Forecasting (WRF)-based mesoscale simulations and several wake models with the measurements. Firstly, the effect of carrier-to-noise-ratio (CNR) and data availability on the quality of scanning LiDAR measurements was evaluated. Analysis of vertical profiles show that the average wind speed is higher for wind blowing from the sea than that blowing from the land. Furthermore, profiles obtained from the WRF simulation also show a similar tendency in the LiDAR measurements in general, though it overestimates the wind speeds at higher altitudes. A method for reconstruction of wind fields from plan-position indicator (PPI) and range height indicator (RHI) scans of LiDAR-measured line of sight velocities was then proposed and first used to investigate the effect of coastal terrain. An internal boundary layer with strong shear could be observed to develop from the coastline. Finally, the flow field around wind turbine was measured using PPI scan and used to validate wake models.

Coastal Wind Measurements Using a Single Scanning LiDAR

A wind measurement campaign using a single scanning light detection and ranging (LiDAR) device was conducted at the Hazaki Oceanographical Research Station (HORS) on the Hazaki coast of Japan to evaluate the performance of the device for coastal wind measurements. The scanning LiDAR was deployed on the landward end of the HORS pier. We compared the wind speed and direction data recorded by the scanning LiDAR to the observations obtained from a vertical profiling LiDAR installed at the opposite end of the pier, 400 m from the scanning LiDAR. The best practice for offshore wind measurements using a single scanning LiDAR was evaluated by comparing results from a total of nine experiments using several different scanning settings. A two-parameter velocity volume processing (VVP) method was employed to retrieve the horizontal wind speed and direction from the radial wind speed. Our experiment showed that, at the current offshore site with a negligibly small vertical wind speed component, the accuracy of the scanning LiDAR wind speeds and directions was sensitive to the azimuth angle setting, but not to the elevation angle setting. In addition to the validations for the 10-minute mean wind speeds and directions, the application of LiDARs for the measurement of the turbulence intensity (TI) was also discussed by comparing the results with observations obtained from a sonic anemometer, mounted at the seaward end of the HORS pier, 400 m from the scanning LiDAR. The standard deviation obtained from the scanning LiDAR measurement showed a greater fluctuation than that obtained from the sonic anemometer measurement. However, the difference between the scanning LiDAR and sonic measurements appeared to be within an acceptable range for the wind turbine design. We discuss the variations in data availability and accuracy based on an analysis of the carrier-to-noise ratio (CNR) distribution and the goodness of fit for curve fitting via the VVP method.

Impact of Doppler Radar Wind Observations on Australian High-Resolution Numerical Weather Prediction

Abstract The impact of Doppler radar wind observations on forecasts from a developmental, high-resolution numerical weather prediction (NWP) system is assessed. The new 1.5-km limited-area model will be Australia’s first such operational NWP system to include data assimilation. During development, the assimilation of radar wind observations was trialed over a 2-month period to approve the initial inclusion of these observations. Three trials were run: the first with no radar data, the second with radial wind observations from precipitation echoes, and the third with radial winds from both precipitation and insect echoes. The forecasts were verified against surface observations from automatic weather stations, against rainfall accumulations using fractions skill scores, and against satellite cloud observations. These methods encompassed verification across a range of vertical levels. Additionally, a case study was examined more closely. Overall results showed little statistical difference in skill between the trials, and the net impact was neutral. While the new observations clearly affected the forecast, the objective and subjective analyses showed a neutral impact on the forecast overall. As a first step, this result is satisfactory for the operational implementation. In future, upgrades to the radar network will start to reduce the observation error, and further improvements to the data assimilation are planned, which may be expected to improve the impact.

Formation of Wind Gusts in an Extratropical Cyclone in Light of Doppler Lidar Observations and Large-Eddy Simulations

AbstractDamaging gusts in windstorms are represented by crude subgrid-scale parameterizations in today’s weather and climate models. This limitation motivated the Wind and Storms Experiment (WASTEX) in winter 2016–17 in the Upper Rhine Valley over southwestern Germany. Gusts recorded at an instrumented tower during the passage of extratropical cyclone “Thomas” on 23 February 2017 are investigated based on measurements of radial wind with ≈70-m along-beam spacing from a fast-scanning Doppler lidar and realistic large-eddy simulations with grid spacings down to 78 m using the Icosahedral Nonhydrostatic model. Four wind peaks occur due to the storm onset, the cold front, a precipitation line, and isolated showers. The first peak is related to a sudden drop in dewpoint and results from the downward mixing of a low-level jet and a dry layer within the warm sector characterized by extremely high temperatures for the season. While operational convection-permitting forecasts poorly predict the storm onset overall, a successful ensemble member highlights the role of upstream orography. Lidar observations reveal the presence of long-lasting wind structures that result from a combination of convection- and shear-driven instability. Large-eddy simulations contain structures elongated in the wind direction that are qualitatively similar but too coarse compared to the observed ones. Their size is found to exceed the effective model resolution by one order of magnitude due to their elongation. These results emphasize the need for subkilometer-scale measuring and modeling systems to improve the representation of gusts in windstorms.

Performance of Continuous-wave Coherent Doppler Lidar for WindMeasurement

A system for continuous-wave coherent Doppler lidar (CW lidar), made up of all-fiber structures and a coaxial transmission telescope, was set up for wind measurement in Hefei (31.84 N, 117.27 E), Anhui province of China. The lidar uses a fiber laser as a light source at a wavelength of 1.55 μm, and focuses the laser beam on a location 80 m away from the telescope. Using the CW lidar, radial wind measurement was carried out. Subsequently, the spectra of the atmospheric backscattered signal were analyzed. We tested the noise and obtained the lower limit of wind velocity as 0.721 m/s, through the Rayleigh criterion. According to the number of Doppler peaks in the radial wind spectrum, a classification retrieval algorithm (CRA) combining a Gaussian fitting algorithm and a spectral centroid algorithm is designed to estimate wind velocity. Compared to calibrated pulsed coherent wind lidar, the correlation coefficient for the wind velocity is 0.979, with a standard deviation of 0.103 m/s. The results show that CW lidar offers satisfactory performance and the potential for application in wind measurement.

Observational Study on the Characteristics of the Boundary Layer during Changes in the Intensity of Tropical Cyclones Landing in Guangdong, China

Eleven tropical cyclones that landed in Guangdong Province since 2012 and experienced strengthening or weakening over the offshore area were studied. Since the structure of the tropical cyclone boundary layer significantly influences the variation of the intensity of the cyclone, continuous observations of the wind profile radar at a coastal radar station in Guangdong Province were combined with aircraft observation data of the No. 1604 “Nida” cyclone to analyse the variations in the distributions of the radial wind, tangential wind, and angular momentum in the typhoon boundary layer and the similarities and differences between the boundary layers of the 11 tropical cyclones during the strengthening or weakening of their intensities. The analysis results show that the presence of the supergradient wind and the enhancement effect of the radial inflow play important roles in enhancing the intensity of a tropical cyclone. The observations indicate that when the tangential wind velocity in the maximum wind velocity radius reaches the velocity of the supergradient wind and when the radial inflow either gradually increases towards the centre of the tropical cyclone or gradually covers the entire boundary layer, the angular momentum tends to be shifted towards the centre. At this time, the maximum radial inflow, maximum tangential wind, and maximum angular momentum are in the same height range in the vertical direction. When a strong radial outflow occurs in the boundary layer of a tropical cyclone or the area with maximum wind velocity is located in the air outflow, the angular momentum cannot easily be transported towards the centre of the typhoon. Therefore, the spatial configuration of the three physical quantities will determine future changes in the intensity of tropical cyclones. The scope of the results presented here is limited to the 11 selected cases and suggests extending the analysis to more data.

Improvements to the Assimilation of Doppler Radial Winds for Convection-Permitting Forecasts of a Heavy Rain Event

AbstractThis work describes developments to improve the Doppler radial wind data assimilation scheme used in the National Centers for Environmental Prediction (NCEP) Gridpoint Statistical Interpolation (GSI) data assimilation system with a focus on convection-permitting, 0–18-h forecasts of a heavy precipitation single case study. This work focuses on two aspects: 1) the extension of the radial wind observation operator to include vertical velocity and 2) a refinement of the radial wind super-observation processing. The refinement includes reducing the magnitude of observation smoothing and allowing observations from higher scan angles into the analysis with the intent to improve the assimilation of the radar data for operational, convection-permitting models. The results of this study demonstrate that there is sensitivity to the refinement in super-observation settings. The inclusion of vertical velocity in the observation operator is shown to have a neutral to slightly positive impact on the forecast. Results from this study are suggested to be used as a foundation to prioritize future research into the effective assimilation of radial winds in an operational setting.

Observation Error Statistics for Doppler Radar Radial Wind Superobservations Assimilated into the DWD COSMO-KENDA System

AbstractCurrently in operational numerical weather prediction (NWP) the density of high-resolution observations, such as Doppler radar radial winds (DRWs), is severely reduced in part to avoid violating the assumption of uncorrelated observation errors. To improve the quantity of observations used and the impact that they have on the forecast requires an accurate specification of the observation uncertainties. Observation uncertainties can be estimated using a simple diagnostic that utilizes the statistical averages of observation-minus-background and observation-minus-analysis residuals. We are the first to use a modified form of the diagnostic to estimate spatial correlations for observations used in an operational ensemble data assimilation system. The uncertainties for DRW superobservations assimilated into the Deutscher Wetterdienst convection-permitting NWP model are estimated and compared to previous uncertainty estimates for DRWs. The new results show that most diagnosed standard deviations are smaller than those used in the assimilation, hence, it may be feasible to assimilate DRWs using reduced error standard deviations. However, some of the estimated standard deviations are considerably larger than those used in the assimilation; these large errors highlight areas where the observation processing system may be improved. The error correlation length scales are larger than the observation separation distance and influenced by both the superobbing procedure and observation operator. This is supported by comparing these results to our previous study using Met Office data. Our results suggest that DRW error correlations may be reduced by improving the superobbing procedure and observation operator; however, any remaining correlations should be accounted for in the assimilation.

Impact of Assimilating Upper-Level Dropsonde Observations Collected during the TCI Field Campaign on the Prediction of Intensity and Structure of Hurricane Patricia (2015)

Abstract The dropsondes released during the Tropical Cyclone Intensity (TCI) field campaign provide high-resolution kinematic and thermodynamic measurements of tropical cyclones within the upper-level outflow and inner core. This study investigates the impact of these upper-level TCI dropsondes on analyses and prediction of Hurricane Patricia (2015) during its rapid intensification (RI) phase using an ensemble–variational data assimilation system. In the baseline experiment (BASE), both kinematic and thermodynamic observations of TCI dropsondes at all levels except the upper levels are assimilated. The upper-level wind and thermodynamic observations are assimilated in additional experiments to investigate their respective impacts. Compared to BASE, assimilating TCI upper-level wind observations improves the accuracy of outflow analyses verified against independent atmospheric motion vector (AMV) observations. It also strengthens the tangential and radial wind near the upper-level eyewall. The inertial stability within the upper-level eyewall is enhanced, and the maximum outflow is more aligned toward the inner core. Additionally, the analyses including the upper-level thermodynamic observations produce a warmer and drier core at high levels. Assimilating both upper-level kinematic and thermodynamic observations also improves the RI forecast. Compared to BASE, assimilating the upper-level wind induces more upright and inward-located eyewall convection, resulting in more latent heat release closer to the warm core. This process leads to stronger inner-core warming. Additionally, the initial warmer upper-level inner core produced by assimilating TCI thermodynamic observations also intensifies the convection and latent heat release within the eyewall, thus further contributing to the improved intensity forecasts.

A Vortex-Based Doppler Velocity Dealiasing Algorithm for Tropical Cyclones

AbstractIn this study, a vortex-based Doppler velocity dealiasing (VDVD) algorithm for tropical cyclones (TCs) is proposed. The algorithm uses a Rankine combined vortex model as a reference field for dealiasing based on an inner–outer iterative procedure. The structure of the reference vortex is adjusted in an inner iterative procedure of VDVD that applies the ground-based velocity track display (GBVTD) technique. The outer loop of the VDVD based on the GBVTD-simplex algorithm is used for center correction. The VDVD is able to recover not only the aliased Doppler velocities from a simulated symmetric vortex but also those superimposed with wavenumber-1 asymmetry, radial wind, or mean flow. For real cases, the VDVD provides dealiased Doppler velocity with 99.4% accuracy for all pixels, based on 472 elevation sweeps from a typhoon without landfall. It is suggested that the VDVD algorithm can improve the quality of downstream applications such as Doppler wind retrievals and radar data assimilations of TCs and other storms, such as tornadoes and mesocyclones, with vortex signatures.

The Convective Electric Field Influence on the Cold Plasma and Diamagnetic Cavity of Comet 67P

Abstract We studied the distribution of cold electrons (<1 eV) around comet 67P/Churyumov–Gerasimenko with respect to the solar wind convective electric field direction. The cold plasma was measured by the Langmuir Probe instrument and the direction of the convective electric field conv = − × was determined from magnetic field ( ) measurements inside the coma combined with an assumption of a purely radial solar wind velocity . We found that the cold plasma is twice as likely to be observed when the convective electric field at Rosetta’s position is directed toward the nucleus (in the − conv hemisphere) compared to when it is away from the nucleus (in the + conv hemisphere). Similarly, the diamagnetic cavity, in which previous studies have shown that cold plasma is always present, was also found to be observed twice as often when in the − conv hemisphere, linking its existence circumstantially to the presence of cold electrons. The results are consistent with hybrid and Hall magnetohydrodynamic simulations as well as measurements of the ion distribution around the diamagnetic cavity.

Adaptive iteratively reweighted sine wave fitting method for rapid wind vector estimation of pulsed coherent Doppler lidar.

Wind vector estimation method that provides more available data in low signal-to-noise ratio (SNR) regime improves the performance of pulsed coherent Doppler lidar. The adaptive iteratively reweighted sine wave fitting (airSWF) method proposed here reweights the contribution of each radial wind velocity adaptively and iteratively when estimating the wind vector. Based on the processing results of both the simulated and real-captured signal, the airSWF method provides more available wind vector estimates with little computational time increment, compared with the direct sine wave fitting (DSWF) and weighted DSWF methods. Specifically, the proportion of available wind vector estimates determined using the airSWF method increases by >20% when the detection height exceeds 1 km. Another significant advantage of the airSWF method over the filtered sine wave fitting (FSWF) method is that no prior knowledge is required. Moreover, the computational complexity of the airSWF method is lower than that of the FSWF and maximum of the function of accumulated spectra methods.

A pragmatic strategy for implementing spatially correlated observation errors in an operational system: An application to Doppler radial winds

Recent research has shown that high‐resolution observations, such as Doppler radar radial winds, exhibit spatial correlations. High‐resolution observations are routinely assimilated into convection‐permitting numerical weather prediction models assuming their errors are uncorrelated. To avoid violating this assumption, observation density is severely reduced. To improve the quantity of observations used and the impact that they have on the forecast requires the introduction of full, correlated, error statistics. Some operational centres have introduced satellite inter‐channel observation‐error correlations and obtained improved analysis accuracy and forecast skill scores. Here we present a strategy for implementing spatially correlated observation errors in an operational system. We then provide the first demonstration of the practical feasibility of incorporating spatially correlated Doppler radial wind error statistics in the Met Office numerical weather prediction system.Inclusion of correlated Doppler radial winds error statistics has little impact on the computation cost of the data assimilation system, even with a fourfold increase in the number of Doppler radial winds observations assimilated. Using the correlated observation‐error statistics with denser observations produces increments with shorter length‐scales than the control. Initial forecast trials show a neutral to positive impact on forecast skill overall, notably for quantitative precipitation forecasts. There is potential to improve forecast skill by optimizing the use of Doppler radial winds and applying the technique to other observation types.