Characteristics of the quasi-16-day wave in the mesosphere and lower thermosphere region as revealed by meteor radar,Aura satellite,and MERRA2 reanalysis data from 2008 to 2017

This study presents an analysis of the quasi-16-day wave(Q16DW)at three stations in the middle latitudes by using a meteor radar chain in conjunction with Aura Microwave Limb Sounder temperature data and MERRA2(Modern-Era Retrospective Analysis for Research and Applications,Version 2)reanalysis data from 2008 to 2017.The radar chain consists of three meteor radar stations located at Mohe(MH,53.5°N,122.3°E),Beijing(BJ,40.3°N,116.2°E),and Wuhan(WH,30.5°N,114.6°E).The Q16DW wave exhibits similar seasonal variation in the neutral wind and temperature,and the Q16DW amplitude is generally strong during winter and weak around summer.The Q16DW at BJ was found to have secondary enhancement around September in the zonal wind,which is rarely reported at similar latitudes.The latitudinal variations of the Q16DW in the neutral wind and temperature are quite different.The Q16DW at BJ is the most prominent in both neutral wind components among the three stations and the Q16DW amplitudes at MH and WH are comparable,whereas the wave amplitude in temperature decreases with decreasing latitude.The quasi-geostrophic refractive index squared at the three stations in the period from 2008 to 2017 was revealed.The results indicate that the Q16DW in the mesosphere and lower thermosphere(MLT)at MH has a limited contribution from the lower atmosphere.Around March and October,the Q16DW in the troposphere at BJ can propagate upward into the MLT region,whereas at WH,the contribution to the Q16DW in the MLT region is largely from the mesosphere.

Mesopause temperatures and relative densities at midlatitudes observed by the Mengcheng meteor radar

The atmospheric temperatures and densities in the mesosphere and lower thermosphere(MLT)region are essential for studying the dynamics and climate of the middle and upper atmosphere.In this study,we present more than 9 years of mesopause temperatures and relative densities estimated by using ambipolar diffusion coefficient measurements observed by the Mengcheng meteor radar(33.4°N,116.5°E).The intercomparison between the meteor radar and Thermosphere Ionosphere Mesosphere Energetics and Dynamics/Sounding of the Atmosphere by Broadband Emission Radiometry(TIMED/SABER)and Earth Observing System(EOS)Aura/Microwave Limb Sounder(MLS)observations indicates that the meteor radar temperatures and densities agree well with the simultaneous satellite measurements.Annual variations dominate the mesopause temperatures,with the maximum during winter and the minimum during summer.The mesopause relative densities also show annual variations,with strong maxima near the spring equinox and weak maxima before the winter solstice,and with a minimum during summer.In addition,the mesopause density exhibits a structure similar to that of the zonal wind:as the zonal wind flows eastward(westward),the mesopause density decreases(increases).At the same time,the meridional wind shows a structure similar to that of the mesopause temperature:as the meridional wind shows northward(southward)enhancements,the mesopause temperature increases(decreases).Simultaneous horizontal wind,temperature,and density observations provide multiple mesospheric parameters for investigating mesospheric dynamics and thermodynamic processes and have the potential to improve widely used empirical atmospheric models.

Quasi-90-day oscillation observed in the MLT region at low latitudes from the Kunming meteor radar and SABER

Observations of a quasi-90-day oscillation in the mesosphere and lower thermosphere(MLT) region from April 2011 to December 2014 are presented in this study. There is clear evidence of a quasi-90-day oscillation in temperatures obtained from the Kunming meteor radar(25.6°N, 103.8°E) and Sounding of the Atmosphere using Broadband Emission Radiometry(SABER), as well as in wind observed by the Kunming meteor radar. The quasi-90-day oscillation appears to be a prominent feature in the temperatures and meridional wind tides and presents quite regular cycles that occur approximately twice per year. The amplitudes and phases of the quasi-90-day oscillation in the SABER temperature show a feature similar to that of upward-propagated diurnal tides, which have a vertical wavelength of ～20 km above 70 km. In the lower atmosphere, a similar 90-day variability is presented in the surface latent heat flux and correlates with the temperature in the MLT region. Similar to the quasi-90-day oscillation in temperature, a 90-day variability of ozone(O3) is also present in the MLT region and is considered to be driven by a similar variability in the upwardly-propagated diurnal tides generated in the lower atmosphere. Moreover, the 90-day variability in the absorption of ultraviolet(UV) radiation by daytime O3 in the MLT region is an in situ source of the quasi-90-day oscillation in the MLT temperature.

Current Status and Future Challenges of Weather Radar Polarimetry: Bridging the Gap between Radar Meteorology/Hydrology/Engineering and Numerical Weather Prediction

After decades of research and development, the WSR-88 D(NEXRAD) network in the United States was upgraded with dual-polarization capability, providing polarimetric radar data(PRD) that have the potential to improve weather observations,quantification, forecasting, and warnings. The weather radar networks in China and other countries are also being upgraded with dual-polarization capability. Now, with radar polarimetry technology having matured, and PRD available both nationally and globally, it is important to understand the current status and future challenges and opportunities. The potential impact of PRD has been limited by their oftentimes subjective and empirical use. More importantly, the community has not begun to regularly derive from PRD the state parameters, such as water mixing ratios and number concentrations, used in numerical weather prediction(NWP) models.In this review, we summarize the current status of weather radar polarimetry, discuss the issues and limitations of PRD usage, and explore potential approaches to more efficiently use PRD for quantitative precipitation estimation and forecasting based on statistical retrieval with physical constraints where prior information is used and observation error is included. This approach aligns the observation-based retrievals favored by the radar meteorology community with the model-based analysis of the NWP community. We also examine the challenges and opportunities of polarimetric phased array radar research and development for future weather observation.

First results of optical meteor and meteor trail irregularity from simultaneous Sanya radar and video observations

Meteoroids entering the Earth's atmosphere can create meteor trail irregularity seriously disturbing the background ionosphere. Although numerous observations of meteor trail irregularities were performed with VHF/UHF coherent scatter radars in the past, no simultaneous radar and optical instruments were employed to investigate the characteristics of meteor trail irregularity and its corresponding meteoroid. By installing multiple video cameras near the Sanya VHF radar site, an observational campaign was conducted during the period from November 2016 to February 2017. A total of 242 optical meteors with simultaneous non-specular echoes backscattered from the plasma irregularities generated in the corresponding meteor trails were identified. A good agreement between the angular positions of non-specular echoes derived from the Sanya radar interferometer and those of optical meteors was found,validating that the radar system phase offsets have been properly calibrated. The results also verify the interferometry capability of Sanya radar for meteor trail irregularity observation. The non-specular echoes with simultaneous optical meteors were detected at magnetic aspect angles greater than ~78°. Based on the meteor visual magnitude estimated from the optical data, it was found that the radar nonspecular echoes corresponding to brighter meteors survived for longer duration. This could provide observational evidence for the significance of meteoroid mass on the duration of meteor trail irregularity. On the other hand, the simultaneous radar and video common-volume observations showed that there were some cases with optical meteors but without radar non-specular echoes. One possibility could be that some of the optical meteors appeared at extremely low altitudes where meteor trail irregularities rarely occur.

Statistics-based Optimization of the Polarimetric Radar Hydrometeor Classification Algorithm and Its Application for a Squall Line in South China

A modified hydrometeor classification algorithm （HCA） is developed in this study for Chinese polarimetric radars. This algorithm is based on the U.S. operational HCA. Meanwhile, the methodology of statistics-based optimization is proposed including calibration checking, datasets selection, membership functions modification, computation thresholds modification, and effect verification. Zhuhai radar, the first operational polarimetric radar in South China, applies these procedures. The systematic bias of calibration is corrected, the reliability of radar measurements deteriorates when the signal-to-noise ratio is low, and correlation coefficient within the melting layer is usually lower than that of the U.S. WSR-88D radar. Through modification based on statistical analysis of polarimetric variables, the localized HCA especially for Zhuhai is obtained, and it performs well over a one-month test through comparison with sounding and surface observations. The algorithm is then utilized for analysis of a squall line process on 11 May 2014 and is found to provide reasonable details with respect to horizontal and vertical structures, and the HCA results---especially in the mixed rain-hail region--can reflect the life cycle of the squall line. In addition, the kinematic and microphysical processes of cloud evolution and the differences between radar- detected hail and surface observations are also analyzed. The results of this study provide evidence for the improvement of this HCA developed specifically for China.

A comparison of MLT wind between meteor radar chain data and SDWACCM results

A meteor radar chain located along the 120°E meridian in the Northern Hemisphere from low to middle latitudes provides longterm horizontal wind observations of the mesosphere and lower thermosphere(MLT)region.In this study,we report a seasonal variation and its latitudinal feature in the horizontal mean wind in the MLT region observed by six meteor radar instruments located at Mohe(53.5°N,122.3°E),Beijing(40.3°N,116.2°E),Mengcheng(33.4°N,116.5°E),Wuhan(30.6°N,114.4°E),Kunming(25.6°N,108.3°E),and Fuke(19.5°N,109.1°E)stations.In addition,we compare the wind in the MLT region measured by the meteor radar stations with those simulated by the Whole Atmosphere Community Climate Model(WACCM).In general,the WACCM appears to capture well the seasonal and latitudinal variations in the zonal wind component.In particular,the temporal evolution of the eastward zonal wind maximum shifts from July to May as the latitude decreases.However,the simulated WACCM meridional wind exhibits differences from the meteor radar observations.

VHF meteor radar at King Sejong Station,Antarctica

Since 2002, we have been observing the mesosphere and lower thermosphere （MLT） region over King Sejong Station （KSS; 62.22°S, 58.78°W）, Antarctica, using various instruments such as the Spectral Airglow Temperature Imager （SATI）, All Sky Camera （ASC） and VHF meteor radar. The meteor radar, installed in March 2007, continuously measures neutral winds in the alti- tude region 70-110 km and neutral temperature near the mesopause 24 h.d-1, regardless of weather conditions. In this study, we present results of an analysis of the neutral wind data for gravity wave activity over the tip of the Antarctic Peninsula, where such activity is known to be very high. Also presented is temperature estimation from measurement of the decay times of meteor trails, which is compared with other temperature measurements from SATI and the Sounding of the Atmosphere using Broadband Emis- sion Radiometry （SABER） instrument onboard the Thermosphere Ionosphere Mesosphere Energy and Dynamics （TIMED） satel- lite.

Improvement of X-Band Polarization Radar Melting Layer Recognition by the Bayesian Method and ITS Impact on Hydrometeor Classification

Using melting layer(ML)and non-melting layer(NML)data observed with the X-band dual linear polarization Doppler weather radar(X-POL)in Shunyi,Beijing,the reflectivity(ZH),differential reflectivity(ZDR),and correlation coefficient(CC)in the ML and NML are obtained in several stable precipitation processes.The prior probability density distributions(PDDs)of the ZH,ZDR and CC are calculated first,and then the probabilities of ZH,ZDR and CC at each radar gate are determined(PBB in the ML and PNB in the NML)by the Bayesian method.When PBB>PNB the gate belongs to the ML,and when PBB<PNB the gate belongs to the NML.The ML identification results with the Bayesian method are contrasUsing melting layer(ML)and non-melting layer(NML)data observed with the X-band dual linear polarization Doppler weather radar(X-POL)in Shunyi,Beijing,the reflectivity(ZH),differential reflectivity(ZDR),and correlation coefficient(CC)in the ML and NML are obtained in several stable precipitation processes.The prior probability density distributions(PDDs)of the ZH,ZDR and CC are calculated first,and then the probabilities of ZH,ZDR and CC at each radar gate are determined(PBB in the ML and PNB in the NML)by the Bayesian method.When PBB>PNB the gate belongs to the ML,and when PBB<PNB the gate belongs to the NML.The ML identification results with the Bayesian method are contrasted under the conditions of the independent PDDs and joint PDDs of the ZH,ZDR and CC.The results suggest that MLs can be identified effectively,although there are slight differences between the two methods.Because the values of the polarization parameters are similar in light rain and dry snow,it is difficult for the polarization radar to distinguish them.After using the Bayesian method to identify the ML,light rain and dry snow can be effectively separated with the X-POL observed data.ted under the conditions of the independent PDDs and joint PDDs of the ZH,ZDR and CC.The results suggest that MLs can be identified effectively,although there are slight differences between the two methods.Because the values of the polarization parameters are similar in light rain and dry snow,it is difficult for the polarization radar to distinguish them.After using the Bayesian method to identify the ML,light rain and dry snow can be effectively separated with the X-POL observed data.

Identification and Removal of Non-meteorological Echoes in Dual-polarization Radar Data Based on a Fuzzy Logic Algorithm

A major issue in radar quantitative precipitation estimation is the contamination of radar echoes by non-meteorological targets such as ground clutter,chaff,clear air echoes etc.In this study,a fuzzy logic algorithm for the identification of non-meteorological echoes is developed using optimized membership functions and weights for the dual-polarization radar located at Mount Sobaek.For selected precipitation and non-meteorological events,the characteristics of the precipitation and non-meteorological echo are derived by the probability density functions of five fuzzy parameters as functions of reflectivity values.The membership functions and weights are then determined by these density functions.Finally,the nonmeteorological echoes are identified by combining the membership functions and weights.The performance is qualitatively evaluated by long-term rain accumulation.The detection accuracy of the fuzzy logic algorithm is calculated using the probability of detection（POD）,false alarm rate（FAR）,and clutter–signal ratio（CSR）.In addition,the issues in using filtered dual-polarization data are alleviated.

Deep convolutional neural network for meteorology target detection in airborne weather radar images

Considering the problem that the scattering echo images of airborne Doppler weather radar are often reduced by ground clutters,the accuracy and confidence of meteorology target detection are reduced.In this paper,a deep convolutional neural network(DCNN)is proposed for meteorology target detection and ground clutter suppression with a large collection of airborne weather radar images as network input.For each weather radar image,the corresponding digital elevation model(DEM)image is extracted on basis of the radar antenna scan-ning parameters and plane position,and is further fed to the net-work as a supplement for ground clutter suppression.The fea-tures of actual meteorology targets are learned in each bottle-neck module of the proposed network and convolved into deeper iterations in the forward propagation process.Then the network parameters are updated by the back propagation itera-tion of the training error.Experimental results on the real mea-sured images show that our proposed DCNN outperforms the counterparts in terms of six evaluation factors.Meanwhile,the network outputs are in good agreement with the expected mete-orology detection results(labels).It is demonstrated that the pro-posed network would have a promising meteorology observa-tion application with minimal effort on network variables or parameter changes.

The Nippon/Norway Svalbard Meteor Radar: First results of small-scale structure observations

The Nippon/Norway Svalbard Meteor Radar(NSMR), has been in operation since March 2001. While primarily thought of as an instrument for examining mean wind, tidal and gravity wave neutral atmosphere dynamics in the upper mesosphere region, it is also possible to investigate spatial and temporal structure of temperature and windshear. Here, the radar itself is described followed by a presentation of these derived parameters.

Metal–Organic Gel Leading to Customized Magnetic‑Coupling Engineering in Carbon Aerogels for Excellent Radar Stealth and Thermal Insulation Performances

Metal–organic gel(MOG)derived composites are promising multi-functional materials due to their alterable composition,identifiable chemical homogeneity,tunable shape,and porous structure.Herein,stable metal–organic hydrogels are prepared by regulating the complexation effect,solution polarity and curing speed.Meanwhile,collagen peptide is used to facilitate the fabrication of a porous aerogel with excellent physical properties as well as the homogeneous dispersion of magnetic particles during calcination.Subsequently,two kinds of heterometallic magnetic coupling systems are obtained through the application of Kirkendall effect.FeCo/nitrogen-doped carbon(NC)aerogel demonstrates an ultra-strong microwave absorption of−85 dB at an ultra-low loading of 5%.After reducing the time taken by atom shifting,a FeCo/Fe3O4/NC aerogel containing virus-shaped particles is obtained,which achieves an ultra-broad absorption of 7.44 GHz at an ultra-thin thickness of 1.59 mm due to the coupling effect offered by dual-soft-magnetic particles.Furthermore,both aerogels show excellent thermal insulation property,and their outstanding radar stealth performances in J-20 aircraft are confirmed by computer simulation technology.The formation mechanism of MOG is also discussed along with the thermal insulation and electromagnetic wave absorption mechanism of the aerogels,which will enable the development and application of novel and lightweight stealth coatings.

Possibility of Solid Hydrometeor Growth Zone Identification Using Radar Spectrum Width

In this study,the correlation between simulated and measured radar velocity spectrum width(σ_(v))is investigated.The results show that the dendrites growth zones(DGZs)and needles growth zones(NGZs)mostly contain dendrites(DN)and needles(NE),respectively.Clearσ_(v) zones(1.1<σ_(v)(m s^(-1))<1.3 and 0.3<σ_(v)(m s^(-1))<0.7 for the DGZ and NGZ,respectively)could be identified in the case studies(27 and 28 February 2016)near altitudes corresponding to temperatures of–15°C and–5°C,according to the Japan Meteorological Agency and mesoscale model reanalysis data.Oblate particles with diverse particle shapes were observed in the DGZ withσ_(v)>1.2 m s^(-1),a differential reflectivity(ZDR)higher than 0 dB,and a cross-correlation coefficient(ρhv)less than 0.96.In contrast,prolate particles with relatively uniform shapes were observed in the NGZ withσ_(v)<0.6 m s^(-1),a ZDR less than 0 dB,andρhv higher than 0.97.The simulation results show that the DN exhibited a largerσ_(v) compared to the NE,and this observedσ_(v) was strongly dependent on the wind fluctuations(v’)due to turbulence or wind shear.In contrast,the NE exhibited a significantly smallσ_(v)~0.55 m s^(-1),which converges irrespective of v’.In addition,a strong correlation between the measuredσ_(v) values at five radar elevation angles(θ=6.2°,9.1°,13.1°,19°,and 80°)and those simulated in this study confirmed the significance of the analysis results.

Modulated-ISRJ rejection using online dictionary learning for synthetic aperture radar imagery

In electromagnetic countermeasures circumstances,synthetic aperture radar(SAR)imagery usually suffers from severe quality degradation from modulated interrupt sampling repeater jamming(MISRJ),which usually owes considerable coherence with the SAR transmission waveform together with periodical modulation patterns.This paper develops an MISRJ suppression algorithm for SAR imagery with online dictionary learning.In the algorithm,the jamming modulation temporal properties are exploited with extracting and sorting MISRJ slices using fast-time autocorrelation.Online dictionary learning is followed to separate real signals from jamming slices.Under the learned representation,time-varying MISRJs are suppressed effectively.Both simulated and real-measured SAR data are also used to confirm advantages in suppressing time-varying MISRJs over traditional methods.

Analysis of the joint detection capability of the SMILE satellite and EISCAT-3D radar

The Solar wind Magnetosphere Ionosphere Link Explorer(SMILE)satellite is a small magnetosphere–ionosphere link explorer developed cooperatively between China and Europe.It pioneers the use of X-ray imaging technology to perform large-scale imaging of the Earth’s magnetosheath and polar cusp regions.It uses a high-precision ultraviolet imager to image the overall configuration of the aurora and monitor changes in the source of solar wind in real time,using in situ detection instruments to improve human understanding of the relationship between solar activity and changes in the Earth’s magnetic field.The SMILE satellite is scheduled to launch in 2025.The European Incoherent Scatter Sciences Association(EISCAT)-3D radar is a new generation of European incoherent scatter radar constructed by EISCAT and is the most advanced ground-based ionospheric experimental device in the high-latitude polar region.It has multibeam and multidirectional quasi-real-time three-dimensional(3D)imaging capabilities,continuous monitoring and operation capabilities,and multiple-baseline interferometry capabilities.Joint detection by the SMILE satellite and the EISCAT-3D radar is of great significance for revealing the coupling process of the solar wind–magnetosphere–ionosphere.Therefore,we performed an analysis of the joint detection capability of the SMILE satellite and EISCAT-3D,analyzed the period during which the two can perform joint detection,and defined the key scientific problems that can be solved by joint detection.In addition,we developed Web-based software to search for and visualize the joint detection period of the SMILE satellite and EISCAT-3D radar,which lays the foundation for subsequent joint detection experiments and scientific research.

Co-Sharing Waveform Design for Millimeter-Wave Radar Communication Systems

Millimeter-wave(mmWave)radar communication has emerged as an important technique for future wireless systems.However,the interference between the radar signal and communication data is the main issue that should be considered for the joint radar communication system.In this paper,a co-sharing waveform(CSW)is proposed to achieve communication and radar sensing simultaneously.To eliminate the co-interference between the communication and sensing signal,signal splitting and processing methods for communication data demodulation and radar signal processing are given respectively.Simulation results show that the bit error rate(BER)of CSW is close to that of the pure communication waveform.Moreover,the proposed CSW can achieve better performance than the existing waveforms in terms of range and velocity estimation.

A target parameter estimation method via atom-reconstruction in radar mainlobe jamming

Mainlobe jamming(MLJ)brings a big challenge for radar target detection,tracking,and identification.The suppression of MLJ is a hard task and an open problem in the electronic counter-counter measures(ECCM)field.Target parameters and target direction estimation is difficult in radar MLJ.A target parameter estimation method via atom-reconstruction in radar MLJ is proposed in this paper.The proposed method can suppress the MLJ and simultaneously provide high estimation accuracy of target range and angle.Precisely,the eigen-projection matrix processing(EMP)algorithm is adopted to suppress the MLJ,and the target range is estimated effectively through the beamforming and pulse compression.Then the target angle can be effectively estimated by the atom-reconstruction method.Without any prior knowledge,the MLJ can be canceled,and the angle estimation accuracy is well preserved.Furthermore,the proposed method does not have strict requirement for radar array construction,and it can be applied for linear array and planar array.Moreover,the proposed method can effectively estimate the target azimuth and elevation simultaneously when the target azimuth(or elevation)equals to the jamming azimuth(or elevation),because the MLJ is suppressed in spatial plane dimension.

Anti-swarm UAV radar system based on detection data fusion

There is a growing body of research on the swarm unmanned aerial vehicle(UAV)in recent years,which has the characteristics of small,low speed,and low height as radar target.To confront the swarm UAV,the design of anti-UAV radar system based on multiple input multiple output(MIMO)is put forward,which can elevate the performance of resolution,angle accuracy,high data rate,and tracking flexibility for swarm UAV detection.Target resolution and detection are the core problem in detecting the swarm UAV.The distinct advantage of MIMO system in angular accuracy measurement is demonstrated by comparing MIMO radar with phased array radar.Since MIMO radar has better performance in resolution,swarm UAV detection still has difficulty in target detection.This paper proposes a multi-mode data fusion algorithm based on deep neural networks to improve the detection effect.Subsequently,signal processing and data processing based on the detection fusion algorithm above are designed,forming a high resolution detection loop.Several simulations are designed to illustrate the feasibility of the designed system and the proposed algorithm.

Overview of radar detection methods for low altitude targets in marine environments

In this paper,a comprehensive overview of radar detection methods for low-altitude targets in maritime environments is presented,focusing on the challenges posed by sea clutter and multipath scattering.The performance of the radar detection methods under sea clutter,multipath,and combined conditions is categorized and summarized,and future research directions are outlined to enhance radar detection performance for low-altitude targets in maritime environments.