Clear-air Echoes Research Articles

A New Perspective on the Scattering Mechanism of S-Band Weather Radar Clear-Air Echoes Based on Communication Models

Clear-air echo studies are usually based on isotropic turbulence theory. But the theory has been considered incomplete by modern turbulence theory. The intermittence of turbulence can reveal obvious shortcomings in the existing studies of clear-air echoes. The mechanism of clear-air echo scattering needs to be supplemented. This paper introduces the troposcatter theory, normally used in over-the-horizon communication, to fill the gap left by Bragg scattering. By treating radar as a self-transmitted and self-received device, the equivalent transmission loss of weather radar is established and compared with the recommendations of the Radiocommunication Sector of the International Telecommunication Union (ITU-R). The results show that the S-band radar transmission loss aligns with ITU-R recommendations. There is also a linear regression relationship between the radar transmission loss and height, which conforms to the troposcatter theory. This means that the theory of troposcatter scattering is a supplement to the theory of Bragg scattering. Tropospheric scattering can be thought of as general Bragg scattering. Meanwhile, based on ITU-R recommendations, this study also provides a new way for the recognition of biological echoes.

Clear-Air Bragg Scattering Observed above the Convective Boundary Layer in the Morning

Reflected waves have been frequently observed via weather radar, even during sunny, cloudless days. Additionally, it is recognized that turbulence and biological scatterers can also dominate the scattering process. In previous studies, echo returns of turbulence from clear-air Bragg scattering (CABS) have been used to detect the height of the convective boundary layer (CBL). However, in a dual-frequency antenna multiplexing radar system, through which the dual-wavelength ratio (DWR) identifies the CABS clearly, CABS can be unexpectedly observed not only at the edge of the CBL but also above the CBL, highlighting the need for an expanded set of causes of clear-air echoes. It was further identified that the negative second derivative of horizontal wind speed, which is measured by a coherent Doppler Lidar, is consistent with the variation of the CABS layers’ height above the CBL. These results emphasize the presence of physical processes leading to turbulence in the troposphere, with implications for Bragg scattering studies and the theory of turbulence in general. This study will help the ecology of research better understand the laws of biological activity.

Turbulence: A Significant Role in Clear-Air Echoes of CINRAD/SA at Night

It is commonly believed that clear-air echoes detected by weather radars are caused by atmobios migration. However, clear-air echoes are sometimes inconsistently related to the activity of living creatures. In some cases, the characteristics of radar products seem to conform to biological scattering, but the movement of echoes cannot be observed. For these reasons, we sought to expand the cause of clear-air echoes from a Chinese Doppler S-band Weather Radar (CINRAD/SA) in Beijing. Some contradictions were discovered in a case which diverged from previous conclusions. It was found that the progression and movement of clear-air echoes do not conform to the rules of biological activities. The frequency distribution of dual-wavelength ratio peaks is 21.5 dB, which is in accordance with Villars–Weisskopf’s turbulence theory. From 1 May to 20 May, the 58% dual-wavelength ratio between the S-band and the X-band was distributed between 18 dB and 24 dB. These results show that more than half of the clear-air echoes of CINRAD/SA at night were caused by turbulence in Beijing. A new model of troposcatter propagation, the reflecting-layers model, was then introduced to explain the radar observations. According to the reflecting-layers model, the echoes’ diurnal variation and reflectivity characteristics are attributed to the effects of turbulent mixing. Excessive turbulent mixing affects the generation of the reflective layer, thereby weakening the echo signal. It is necessary to re-examine the position of turbulence in clear-air echoes.

Identification and removal of aircraft clutter to improve wind velocity measurement made with Chung-Li VHF Radar

Abstract In this study, a data processing based on the empirical mode decomposition (EMD) of Hilbert-Huang Transform (HHT) is developed at Chung-Li VHF radar to identify and remove the aircraft clutter for improving the atmospheric wind measurement. The EMD decomposes the echo signals into the so-called intrinsic mode functions (IMFs) in the time domain, and then the aircraft clutter that is represented by a number of specific IMFs can be identified in the radar returns and separated from the clear air echoes that are observed concurrently by the VHF radar. The identified clutter is validated by using the aircraft information collected by the Automatic Dependent Surveillance-Broadcast (ADS-B) receiver. It shows that the proposed algorithm can detect the aircraft echoes that are mixed with the clear air echoes. After implementing the algorithm on the experimental data, the atmospheric horizontal wind velocities are estimated after the aircraft clutter is removed. In order to evaluate the degree of the improvement of the horizontal wind measurement, a comparison in the horizontal wind velocities between Chung-Li VHF radar and a co-located UHF wind profiler radar is made. The results show that the use of EMD and the proposed data processing can effectively reduce the uncertainty and substantially improve the precision and reliability of the horizontal wind measurement.

Classifying Clear Air Echoes via Static and Motion Streams Network

Classification of nonprecipitation echoes of radar is an inevitable step in radar-based precipitation estimation. Among nonprecipitation echoes, clear air echoes are specifically difficult to distinguish for their similarity to precipitation echoes. This letter aims to conduct a pixelwise classification of clear air echoes for image sequences of the radar reflectivity. We propose the Static and Motion streams Network (SMNet) to simultaneously utilize the static and motion features. SMNet realizes capturing the spatiotemporal characteristics while maintaining the details of the current frame via a fusion structure and a novel training method. For feature fusion, the static and motion streams are concatenated. Then, for model training, we adopt a dynamic weight assignment strategy to further extract rich information. Finally, we validate our method on an S-band single-polarization radar in Beijing, China, from May to September 2018. The results demonstrate that the overall performance of SMNet is superior to other competitors.

Aerial Clutter Suppression in a Wind Profiler Radar With Antenna Subarrays

Undesired echo from a flying object (aerial clutter) significantly contaminates the received signal of a wind profiler radar (WPR) because it has high intensity and spreads over a wide Doppler velocity range. In this study, results of aerial clutter mitigation obtained by applying adaptive clutter suppression (ACS) to a 1.3-GHz WPR are shown. The 1.3-GHz WPR used in this study has a main antenna comprising 13 antenna subarrays (MSAs). five-element Yagi-Uda antennas were also used as antenna subarrays for detecting clutters from low elevation angles (CSAs). The CSAs were used only in reception and installed so that they covered most of the horizontal directions and the horizontal and vertical polarizations. The directionally constrained minimization of power (DCMP) method was used as the adaptive signal processing to mitigate clutter. By the DCMP method, the weighted sum of the signals collected by 13 MSAs and 11 CSAs was computed so that the power of output signals was minimized under the constraint of constant gain in the antenna beam direction. Results of a case study for an aerial clutter from a low elevation angle at 17:04:37 on October 1 2020 showed that an overlap of the aerial clutter over a desired echo (i.e., clear-air echo) was solved by decreasing the aerial clutter whose peak intensity was ~24 dB greater than that of the clear-air echo. In a case study at 09:30:27 on September 18 2020, effects of the DCMP method on the processed results were discussed.

Clear-Air Turbulence (CAT) Identification with X-Band Dual Polarimetric Radar Based on Bayesian Approach

The echo of weather radar is seriously disturbed by clear-air turbulence echo (CAT) which needs identifying and eliminating to improve the data quality of weather radar. Using the data observed with the five X-band dual polarimetric radars in Changping, Fangshan, Miyun, Shunyi, and Tongzhou, Beijing in 2018, the probability density distribution (PDD) of the horizontal texture of four radar moments reflectively factor (ZH), differential reflectivity (ZDR), correlation coefficient (ρHV), differential propagation phase shift (ΦDP), and then the CAT is identified and removed using Bayesian method. The results show that the radar data can be effectively improved after the CAT has been eliminated, which include: (1) the removal rate of CAT is more than 98.2% in the analyzed cases. (2) In the area with high-frequency distribution of CAT, the CAT can be effectively suppressed; in the area with low-frequency distribution, some weather echo in the edge with SNR < 15 dB may be mistakenly identified as CAT, but the proportion of meteorological echoes to the total echoes is more than 85%, which indicate that the error rate is very low and does not affect the radar operation.

Evaluation of convective boundary layer height estimates using radars operating at different frequency bands

Abstract. Knowledge of the atmospheric boundary layer state and evolution is important for understanding air pollution and low-level cloud development, among other things. There are a number of instruments and methods that are currently used to estimate boundary layer height (BLH). However, no single instrument is capable of providing BLH measurements in all weather conditions. We proposed a method to derive a daytime convective BLH using clear air echoes in radar observations and investigated the consistency of these retrievals between different radar frequencies. We utilized data from three vertically pointing radars that are available at the SMEAR II station in Finland, i.e. the C band (5 GHz), Ka band (35 GHz) and W band (94 GHz). The Ka- or W-band cloud radars are an integral part of cloud profiling stations of pan-European Aerosol, Clouds and Trace Gases Research Infrastructure (ACTRIS). Our method will be utilized at ACTRIS stations to serve as an additional estimate of the BLH during summer months. During this period, insects and Bragg scatter are often responsible for clear air echoes recorded by weather and cloud radars. To retrieve a BLH, we suggested a mechanism to separate passive and independently flying insects that works for all analysed frequency bands. At the lower frequency (the C band) insect scattering has been separated from Bragg scattering using a combination of the radar reflectivity factor and linear depolarization ratio. Retrieved values of the BLH from all radars are in a good agreement when compared to the BLH obtained with the co-located HALO Doppler lidar and ERA5 reanalysis data set. Our method showed some underestimation of the BLH after nighttime heavy precipitation yet demonstrated a potential to serve as a reliable method to obtain a BLH during clear-sky days. Additionally, the entrainment zone was observed by the C-band radar above the CBL in the form of a Bragg scatter layer. Aircraft observations of vertical profiles of potential temperature and water vapour concentration, collected in the vicinity of the radar, demonstrated some agreement with the Bragg scatter layer.

The scattering mechanism of squall lines with C-Band dual polarization radar. Part II: the mechanism of an abnormal ZDR echo in clear air based on the parameterization of turbulence deformation

In part I, the clear air echo in front of the squall line is caused by turbulence diffraction, which makes the ZDR echo characteristics different from particle scattering. To study the turbulence deformation phenomenon that is affected by environmental wind, the turbulence-related method is used to analyze the characteristics of three-dimensional turbulence energy spectrum density, and the parametric model of turbulence integral length scale and environmental wind speed is established. The results show that the horizontal scale of turbulence is generally larger than the vertical scale. The turbulence is nearly isotropic in the horizontal direction, presenting a flat ellipsoid with the vertical orientation of the rotation axis when there is no horizontal wind or the horizontal velocity is small. When horizontal wind exists, the turbulence scale increases along the dominant wind direction. The turbulence scale is positively correlated with the wind speed. The power function is used to fit the relationships of turbulence integral length scale and horizontal wind speed, which obtains the best fitting effect, and the goodness of fit (GF) is above 0.99 in each direction. The deforming turbulence can cause 8–9 dB ZDR anomalies in the echo of dual polarization radar, which the ratio of scales in the dominant wind and the vertical direction of deforming turbulence (Lu/Lw) is around 4.3. The variation in ZDR depends on the turbulence shape, orientation and the relative position between turbulence and radar. The shape of turbulence derived from radar detection results is consistent with that of the parametric model, which can provide a parametric scheme for turbulence research. The results reveal the mechanism of abnormal ZDR echo caused by deforming turbulence.

The Cause of Night Clear Air Echo of S-band Weather Radar in Beijing

S-band weather radar can often detect a large number of clear air echoes at night. However, there are different views on the mechanism of clear air echoes. According to characteristics of biological migration, combined with L-band radiosonde data and Beijing S-band weather radar data from 1 March to 18 October in 2018, changes of clear air echo reflectivity factor in different seasons and wind directions are analyzed to discuss causes of clear air echo. Firstly, characteristics of time variation of clear air echo are analyzed. The intensity of clear air echo in Beijing increases after sunset, weakens before sunrise, and changes little at night. The intensity of echo gradually increases from March to the middle of May, then weakens from July to the first ten days in August, and maintains at a high level since September. In vertical profiles, the fluctuation of high-level echoes, up to the altitude of 2 kilometers, is larger than that of low-level echoes, with an obviously seasonal variation. Secondly, by comparing the relationship between the wind direction and radar data in different periods of time, it is found that the echo is not consistent with the biological activity regularity. The entropy of radar data gray level co-occurrence matrix is also calculated, and there is no rule to follow the biology. Therefore, it is considered that the turbulence is the dominant cause of night clear air echo in Beijing. And then, radiosonde data show that the temperature lapse rate and wind shear are consistent with the seasonal variation of combined reflectivity factor at the altitude from 1 to 2 km. Finally, possible influence factors of clear air echo are inferred based on some phenomena observed.

High Wind Alerts: A System Created With Observations From the X-band Teaching and Research Radar

Following the August 13, 2011, Indiana State Fair stage collapse tragedy, caused by a wind gust from an approaching thunderstorm, Purdue University enforced a wind speed restriction of 30 mph (13 m s-1) for tents at outdoor events. During these events, volunteers stand outside with handheld anemometers, measuring and reporting when the wind speeds exceed this limit. In this study, we report testing of a new system to automate high-wind alerts based on observations from a Doppler radar, the X-band Teaching and Research Radar (XTRRA), near Purdue’s campus. XTRRA scans over campus at low elevations approximately every 5 minutes. Using XTRRA data collected over its first eight months of operation, we developed an algorithm that generates high-wind alerts whenever observed winds at altitudes below 240 m (the height of Ross-Ade Stadium) exceed the 13 m s-1 threshold. We describe how a combination of median filtering, clutter filtering, and statistical outlier removal mitigated false alarms caused by noise and ground clutter. The high-wind alerts are validated against wind gust observations from a nearby Automated Surface Observing System at Purdue University Airport, known as KLAF. Results indicate that the alerts work well in high-wind events associated with precipitation but less well in high-wind events not associated with precipitation (e.g., frontal passages). This is likely because XTRRA, which has a wavelength of 3 cm, is less sensitive to clear-air echoes than an operational WSR-88D. Following further testing, we envision that these automated high-wind alerts will be distributed to interested parties such as campus event coordinators and safety officials.

Automatic Identification of Clear-Air Echoes Based on Millimeter-wave Cloud Radar Measurements

Millimeter-wave cloud radar (MMCR) provides the capability of detecting the features of micro particles inside clouds and describing the internal microphysical structure of the clouds. Therefore, MMCR has been widely applied in cloud observations. However, due to the influence of non-meteorological factors such as insects, the cloud observations are often contaminated by non-meteorological echoes in the clear air, known as clear-air echoes. It is of great significance to automatically identify the clear-air echoes in order to extract effective meteorological information from the complex weather background. The characteristics of clear-air echoes are studied here by combining data from four devices: an MMCR, a laser-ceilometer, an L-band radiosonde, and an all-sky camera. In addition, a new algorithm, which includes feature extraction, feature selection, and classification, is proposed to achieve the automatic identification of clear-air echoes. The results show that the recognition algorithm is fairly satisfied in both simple and complex weather conditions. The recognition accuracy can reach up to 95.86% for the simple cases when cloud echoes and clear-air echoes are separate, and 88.38% for the complicated cases when low cloud echoes and clear-air echoes are mixed.

Dual-Polarization Radar Observations of Deep Convection over Lake Victoria Basin in East Africa

Lake Victoria in East Africa supports the livelihood of thousands of fishermen and it is estimated that 3000–5000 human deaths occur per year over the lake. It is hypothesized that most of these fatalities are due to localized, severe winds produced by intense thunderstorms over the lake during the rainy season and larger scale, intense winds over the lake during the dry season. The intense winds produce a rough state of the lake (big wave heights) that cause fishing boats to capsize. In this region, weather radars have never been a primary tool for monitoring and nowcasting high impact weather. The Tanzania Meteorological Agency operates an S-band polarimetric radar in Mwanza, Tanzania, along the south shore of Lake Victoria. This radar collects high temporal and spatial resolution data that is now being used to detect and monitor the formation of deep convection over the lake and improve scientific understanding of storm dynamics and intensification. Nocturnal thunderstorms and convection initiation over the lake are well observed by the Mwanza radar and are strongly forced by lake and land breezes and gust fronts. Unexpected is the detection of clear air echo to ranges ≥100 km over the lake that makes it possible to observe low-level winds, gust fronts, and other convergence lines near the surface of the lake. The frequent observation of extensive clear air and low-level convergence lines opens up the opportunity to nowcast strong winds, convection initiation, and subsequent thunderstorm development and incorporate this information into a regional early warning system proposed for Lake Victoria Basin (LVB). Two weather events are presented illustrating distinctly different nocturnal convection initiation over the lake that evolve into intense morning thunderstorms. The evolution of these severe weather events was possible because of the Mwanza radar observations; satellite imagery alone was insufficient to provide prediction of storm initiation, growth, movement, and decay.

Spectral parameters estimation in precipitation for 50 MHz band atmospheric radars

AbstractFifty megahertz band atmospheric radars (ARs) can detect clear air echoes and hydrometeor echoes simultaneously. However, in order to calculate spectral parameters (i.e., echo power, Doppler velocity, and spectrum width) of the clear air echo accurately, the clear air echo must be separated from the hydrometeor echo well. In this study, we propose methods (top method and two‐echo method) for calculating the spectral parameters in precipitation region. The top method is used when raindrops or solid hydrometeors with small echo intensities exist. The top method sets an echo cut level by using the peak intensity of the clear air echo. The echo cut level is used for separating clear air echoes from hydrometeor echoes. The two‐echo method is used when solid hydrometeors with large echo intensities exist. The two‐echo method sets the echo cut level by using the local minimum of echo intensity between the clear air echo and the hydrometeor echo. Measurement results obtained by the vertical beam of the middle and upper atmosphere radar during a precipitation event on 26 October 2009 were used for evaluating the performance of the top and two‐echo methods. The echo cut levels of the top and two‐echo methods were determined from numerical simulation. The measurement results demonstrate that the top and two‐echo methods are useful for reducing errors of spectral parameters.

Bayesian Echo Classification for Australian Single-Polarization Weather Radar with Application to Assimilation of Radial Velocity Observations

AbstractThe Australian Bureau of Meteorology’s operational weather radar network comprises a heterogeneous radar collection covering diverse geography and climate. A naïve Bayes classifier has been developed to identify a range of common echo types observed with these radars. The success of the classifier has been evaluated against its training dataset and by routine monitoring. The training data indicate that more than 90% of precipitation may be identified correctly. The echo types most difficult to distinguish from rainfall are smoke, chaff, and anomalous propagation ground and sea clutter. Their impact depends on their climatological frequency. Small quantities of frequently misclassified persistent echo (like permanent ground clutter or insects) can also cause quality control issues. The Bayes classifier is demonstrated to perform better than a simple threshold method, particularly for reducing misclassification of clutter as precipitation. However, the result depends on finding a balance between excluding precipitation and including erroneous echo. Unlike many single-polarization classifiers that are only intended to extract precipitation echo, the Bayes classifier also discriminates types of nonprecipitation echo. Therefore, the classifier provides the means to utilize clear air echo for applications like data assimilation, and the class information will permit separate data handling of different echo types.

A test pattern identification algorithm and its application to CINRAD/SA(B) data

A variety of faulty radar echoes may cause serious problems with radar data applications, especially radar data assimilation and quantitative precipitation estimates. In this study, “test pattern” caused by test signal or radar hardware failures in CINRAD (China New Generation Weather Radar) SA and SB radar operational observations are investigated. In order to distinguish the test pattern from other types of radar echoes, such as precipitation, clear air and other non-meteorological echoes, five feature parameters including the effective reflectivity data percentage (R Z), velocity RF (range folding) data percentage (R RF), missing velocity data percentage (R M), averaged along-azimuth reflectivity fluctuation $$\left( {R_{N_{r,Z} } } \right)$$ and averaged along-beam reflectivity fluctuation $$\left( {R_{N_{a,Z} } } \right)$$ are proposed. Based on the fuzzy logic method, a test pattern identification algorithm is developed, and the statistical results from all the different kinds of radar echoes indicate the performance of the algorithm. Analysis of two typical cases with heavy precipitation echoes located inside the test pattern are performed. The statistical results show that the test pattern identification algorithm performs well, since the test pattern is recognized in most cases. Besides, the algorithm can effectively remove the test pattern signal and retain strong precipitation echoes in heavy rainfall events.

The New French Operational Polarimetric Radar Rainfall Rate Product

AbstractIn 2012 the Météo France metropolitan operational radar network consists of 24 radars operating at C and S bands. In addition, a network of four X-band gap-filler radars is being deployed in the French Alps. The network combines polarimetric and nonpolarimetric radars. Consequently, the operational radar rainfall algorithm has been adapted to process both polarimetric and nonpolarimetric data. The polarimetric processing chain is available in two versions. In the first version, now operational, polarimetry is only used to correct for attenuation and filter out clear-air echoes. In the second version there is a more extensive use of polarimetry. In particular, the specific differential phase Kdp is used to estimate rainfall rate in intense rain. The performance of the three versions of radar rainfall algorithms (conventional, polarimetric V1, and polarimetric V2) at different frequency bands (S, C, and X) is evaluated by processing radar data of significant events offline and comparing hourly radar rainfall accumulations with hourly rain gauge data. The results clearly show a superior performance of the polarimetric products with respect to the nonpolarimetric ones at all frequency bands, but particularly at higher frequency. The second version of the polarimetric product, which makes a broader use of polarimetry, provides the best overall results.

Signal Postprocessing and Reflectivity Calibration of the Atmospheric Radiation Measurement Program 915-MHz Wind Profilers

Abstract The Department of Energy Atmospheric Radiation Measurement (ARM) Program has recently initiated a new research avenue toward a better characterization of the transition from cloud to precipitation. Dual-wavelength techniques applied to millimeter-wavelength radars and a Rayleigh reference have a great potential for rain-rate retrievals directly from dual-wavelength ratio measurements. In this context, the recent reconfiguration of the ARM 915-MHz wind profilers in a vertically pointing mode makes these instruments the ideal candidate for providing the Rayleigh reflectivity/Doppler velocity reference. Prior to any scientific study, the wind profiler data must be carefully quality checked. This work describes the signal postprocessing steps that are essential for the delivery of high-quality reflectivity and mean Doppler velocity products—that is, the estimation of the noise floor from clear-air echoes, the absolute calibration with a collocated disdrometer, the dealiasing of Doppler velocities, and the merging of the different modes of the wind profiler. The improvement added by the proposed postprocessing is confirmed by comparison with a high-quality S-band profiler deployed at the ARM Southern Great Plains site during the Midlatitude Continental Convective Clouds Experiment. With the addition of a vertically pointing mode and with the postprocessing described in this work in place, besides being a key asset for wind research wind profilers observations may therefore become a centerpiece for rain studies in the years to come.

Discrimination of Bird and Insect Radar Echoes in Clear Air Using High-Resolution Radars

Abstract The source of clear-air reflectivity from operational and research meteorological radars has been a subject of much debate and study over the entire history of radar meteorology. Recent studies have suggested that bird migrations routinely contaminate wind profiles obtained at night, while historical studies have suggested insects as the main source of such nocturnal clear-air echoes. This study analyzes two cases of nocturnal clear-air return using data from operational Weather Surveillance Radar-1988 Doppler (WSR-88D) and X- and W-band research radars. The research radars have sufficient resolution to resolve the echo as point targets in some cases. By examining the radar cross section of the resolved point targets, and by determining the target density, it is found for both cases of nocturnal clear-air echoes that the targets are almost certainly insects. The analysis of the dependence of the echo strength on radar wavelength also supports this conclusion.

Retrieval of Arbitrarily Shaped Raindrop Size Distributions from Wind Profiler Measurements

Abstract An efficient iterative retrieval method for arbitrarily shaped raindrop size distributions (ITRAN) is developed for Doppler spectra measured with a wind profiler. A measured Doppler spectrum is a convolution of the precipitation spectrum and the turbulent spectrum. Deconvolution of the Doppler spectra is achieved through repeated convolutions. The developed method assumes no prior shape of drop size distributions and automatically obtains raindrop size distributions; additionally, it can be applied to large data volumes. Furthermore, it is insensitive to initial values. The method was applied to both simulated and observed spectra. Derived drop size distributions agree with simulated values. Narrower turbulent spectral widths yield better results. Integral values of median volume diameter (D0), liquid water content (LWC), and radar reflectivity factor are estimated with errors of less than 10%. Accurate vertical profiles of raindrop size distributions result when this method is applied to wind profiler data. The technique performed very well with most observed spectra. Some recovered spectra departed from the corresponding measured spectra, for cases in which a clear-air peak could not be accurately reproduced because of uncertainties in the location of the minimum position between the clear-air echo and the precipitation echo. Statistical relationships between LWC and integral rainfall parameters yield interesting features. The median volume diameter is statistically independent of the LWC and is associated with the large variability of the total number of drops, NT, between events. Vertical profiles from one event show a clear inverse relationship between NT and D0