Search

Millimetre‐wave radar offers high ranging accuracy and can capture subtle vibration information of the human heart. This study proposes a heartbeat prediction method based on the transformer model using millimetre‐wave radar. Firstly, the millimetre‐wave radar was used to collect the heartbeat data and conduct normalisation processing. Secondly, a position coding was introduced to assign sine or cosine variables to input data and extract their relative position relationship. Subsequently, the transformer encoder was adopted to allocate attention to input data through the multi‐head attention mechanism, using a mask layer before the decoding layer to prevent the leakage of future information. Finally, we employ the fully connected layer was employed in the linear decoder for regression and output the predicted results. Our experimental results demonstrate that the proposed transformer model achieves nearly 30% higher prediction accuracy than traditional long short‐term memory models while improving both the prediction accuracy and convergence rate. The proposed method has great potential in predicting the heartbeat state of elderly and sick patients. [ABSTRACT FROM AUTHOR]

Waterfowl migrations are large‐scale events that involve millions of birds moving over broad geographic extents, which make them difficult to quantify and study. Historically, wildlife managers have relied mostly on field surveys, such as visual counts from the ground or air that sample at small spatial or temporal extents, or both. Combining field surveys with remote sensing data comprehensively collected over large spatial extents at high temporal frequency may improve the study of migrating waterfowl distributions. We tested the strength of the relationship between broad‐scale weather surveillance radar data and fine‐scale field surveys of waterfowl abundance at wetlands within the Rainwater Basin of Nebraska, USA, from 2017–2019. Radar reflectivity of waterfowl at the peak exodus of evening flights was positively correlated with diurnal waterfowl count data, although there was unexplained variation in the relationship. The association was also very similar across various time scales ranging from daily to monthly averages of waterfowl abundance. We suggest that human‐based ground surveys can calibrate and leverage more comprehensive remote sensing data to get a broad understanding of waterfowl distributions during migration. Several confounding factors, such as spatial displacement between radar and survey observation, individual variation in orientation and body size, and identification of avian species sampled by radar, remain on the path to improving radar‐based waterfowl estimates. [ABSTRACT FROM AUTHOR]

Vegetation structural complexity (VSC)—the three‐dimensional distribution of plants within an ecosystem—is an important ecological trait. To date, research has focused primarily on the effects of VSC on ecological patterns and processes, but comparatively little is known about what drives variation in VSC.Recent advances in active remote sensing technology, particularly light detection and ranging and radio detection and ranging, have allowed the measurement of VSC at unprecedented spatial scales and resolutions. Out of this and earlier work has emerged evidence that VSC is typically associated with greater ecosystem functioning (especially microclimate regulation, productivity, faunal diversity and habitat provisioning), making restoration of vegetation complexity a potentially powerful restoration tool.Recent studies of VSC across natural and experimental gradients of plant diversity have also revealed that more diverse plant communities tend to be more structurally complex. However, the shape and generality of this relationship—and the mechanism(s) by which phytodiversity might contribute to structural complexity—remain poorly understood.Here, we review how active remote sensing has facilitated recent VSC research and shaped our understanding of the relationship between vegetation complexity and ecosystem function. We then present a theoretical framework for the relationship between phytodiversity and VSC based on classic biodiversity‐ecosystem functioning principles. Finally, we evaluate the evidence for the notion that diverse plant assemblages tend to be more structurally complex and explore the shape of the relationship between phytodiversity and VSC using data from 13 recent remote sensing studies.Synthesis. The relationship between phytodiversity and VSC appears to be almost universally positive. Preliminary evidence further suggests that the most common relationships between phytodiversity and VSC are linear or saturating, indicating that the extent of functional redundancy between species varies across plant communities and ecosystems. In contrast, we find little evidence for exponential or negative relationships between plant diversity and VSC, suggesting that even modest increases in plant diversity could markedly increase structural complexity. Additional investigations of phytodiversity‐VSC relationships are necessary to establish whether the observed positive relationships are causal (and, if so, in which direction) and to clarify the potential impact of plant community restoration on structural complexity and broader ecosystem function. [ABSTRACT FROM AUTHOR]

Orthogonal time frequency space (OTFS) is a new method technique that supports reliable information transmission in a strong Doppler environment. Aiming at the radar target parameter estimation problem of integration of radar and communication (IRC) based on OTFS, this paper proposes a two‐step radar target parameter estimation algorithm combining maximum likelihood (ML) estimation and gradient descent (GD) principle. Firstly, the echo signal of the OTFS integrated signal is constructed and based on this, the ML estimation model is constructed, and the alternating projection (AP) algorithm is employed to make a rough estimation of the target parameters. Then the rough estimation results of the AP‐ML algorithm are employed as the initial value of the GD algorithm for the fine parameter estimation. Simulation results show that the proposed algorithm has better target parameter estimation performance and resolution while reducing the computational complexity. [ABSTRACT FROM AUTHOR]

Remote sensing (RS) and geospatial sciences already amount to a long history of fostering research in topics related to ecology. Data and methods have mainly been subject to research and experiments, but trends are now emerging that suggest the use of RS in practical applications like nationwide monitoring programs and assisting global conservation goals. However, use of active remote sensing for ecological and conservation is in its infancy, and the implications of active sensor data, including light detection and ranging and radio detection and ranging that mostly deliver three‐dimensional (3D) information, are still relatively primitive and have largely been limited to indirect use of their extracted proxies for ecological modelling.This cross‐journal special feature between Methods in Ecology and Evolution, Journal of Animal Ecology, Journal of Applied Ecology and Journal of Ecology includes 18 papers that include full research papers, reviews and technical applications. They are mostly novel in either or both their interpretation of proxies derived from active RS data and the direct usage of 3D RS techniques (terrestrial, airborne, UAV borne and spaceborne) to address ecological topics.We categorized the published contributions into the following thematic groups, with some degree of overlap: (i) ecosystem structural analysis by active data (nine studies); (ii) response of animal populations to climate dynamics as shown by active data; (iii) interactive effects of forest structure and wildlife monitoring (five studies); (iv) forest inventories assisted by active data (one study) and (v) tree type classification by active data (one study).Synthesis. The studies in this Special Feature and trends shown by other recent works at the interface of ecology and active RS confirm the ongoing shift from indirect and solely proxy‐based approaches to direct and more data‐science driven methods in approaching ecology and conservation problems by means of active sensors. Relatively affordable and accessible drone and citizen science‐based on‐demand active RS data acquisition are becoming common practice, and the future of sensor development is hypothesized to go beyond the current domination of very high spatial resolution data and towards multiple spaceborne platforms. These tools and methods will support spatial upscaling, uncertainty analysis, large‐scale mapping and monitoring of wildlife dynamics, among other topics that can take advantage of multitemporal/time series data. Nevertheless, access to demanding and costly very high‐resolution data sources may still be maintained and optimized by establishing international and public–private partnered data pools. [ABSTRACT FROM AUTHOR]

Bat movement and behaviour are still mostly understudied over large scales. High‐altitude, nocturnal activity makes visual identification of bats from the ground virtually impossible, dramatically hindering our ability to study their movement ecology. Despite the wide use of radar in aeroecology, its application to study specific taxa is limited due to incomplete target classification abilities. BATScan is a bat classifier for vertical‐looking radar data, which enables identifying bats and characterizing their unique aeroecology.We constructed the classifier using data from 10 radar deployments, covering a wide range of habitats on a central bird migration flyway over a 7‐year period, comprising ~18 million observations. We analysed animal migration above the Hula Valley, home to over 30 species of bats spanning a range of 5–150 g in size and exhibiting a variety of ecological characteristics. We distinguished bat‐labelled radar echoes for training according to phenology, morphology and movement ecology of bats, birds and insects. Several non‐bat datasets were constructed and joined to train classifiers under increasing levels of difficulty. Class imbalance in the resulting training data was handled using a generative adversarial network for up‐sampling the much smaller bat dataset.The resulting classification tool reached a high level of accuracy and precision, and was further scrutinized with an extensive set of ecological validations.Bats perform seasonal migrations over long distances, but little is known about the spatial and temporal characteristics of this movement, and the ability to study it at a large scale has so far been limited. We present the Israeli BATScan dataset, containing over 60,000 bat observations spanning the entire country and representing multiple habitats. Using this data, we produce an unprecedented large scale, highly detailed documentation of the yearly movements of bats on a major migration flyway, and distinguish this pattern from bird migration over space and time.So far, radar aeroecology dealt primarily with birds, increasingly with insects, and only rarely with bats. We present BATScan, a classification tool that can incorporate bats into the framework of radar aeroecology to finally enable a comprehensive description of animal aeroecology. [ABSTRACT FROM AUTHOR]

The Jiamusi (JME) radar is the first high‐frequency coherent scatter radar independently developed in China. In this study, we investigate the statistical characteristics of the Jiamusi radar scattering occurrence rate from the F‐region ionosphere between 40°N and 65°N geomagnetic latitude (MLAT) from March 2018 to November 2019. Then, the diurnal and seasonal variations in scattering echoes and their dependence on geomagnetic conditions are statistically investigated. It is shown that the local time of the peak scattering occurrence rate varies depending on the seasons, that is, approximately 20–22.5 magnetic local time (MLT) in summer, 17.5–20.5 MLT in equinox, and 16–17.5 MLT in winter, which is closely associated with the time of sunset. The occurrence rate also increases with the enhancement of the Kp index. To further understand the mechanism of these features, we simulate the distribution of the gradient drift instability (GDI) indicator ∇n·V→/n $\nabla n\cdot \overrightarrow{V}/n$ by using the Thermosphere‐Ionosphere‐Electrodynamics General Circulation Model (TIEGCM). The analysis results indicate that the GDI may be one of the factors that contribute to these characteristic features. Key Points: Using the JME radar data to study the diurnal, seasonal, and Kp dependencies of mid‐latitude F‐region scattering occurrence rateAt night, there is a long and narrow area with an increasing scattering occurrence rate in the mid‐latitudeGradient drift instability may influence the distribution characteristics of the scattering occurrence rate of the Jiamusi radar observation [ABSTRACT FROM AUTHOR]

Based on observations of the Jicamarca Unattended Long‐term investigations of the Ionosphere and Atmosphere (JULIA) radar, we perform statistical analysis on the occurrence of 3‐m‐scale E‐region irregularities and F‐region irregularities (FRI) in Jicamarca region of South America. The results show that there is a negative correlation between the occurrence rates of equatorial irregularities in E‐ and F‐region. When the equatorial spread F appears, the occurrence rate of irregularities in E‐layer decreases. By analyzing the ion zonal drift velocity detected by JULIA radar, it is proposed that the vertically polarized electric field in the bottom F‐layer could extend downward to E‐layer when FRI appears, leading to the weakening or even reversal of E‐layer electric field. As a result, the electron vertical drift velocity in the E‐layer decreases so as to suppress the growth rate of two‐stream instability, which cause a weakening or even disappearance of equatorial irregularities in E‐region. Plain Language Summary: For the equatorial region, the previous researches on E‐ and F‐region coupling are mainly focused on the relationship between valley region irregularities and F‐region irregularities (FRI). Up to now, the connection between the E‐region irregularities (ERI) existing in Equatorial Electrojet and FRI at night in the equatorial region has not been revealed and needs to be further studied and supplemented. Based on observations of the Jicamarca Unattended Long‐term investigations of the Ionosphere and Atmosphere radar from 2018 to 2022, we conduct a statistical study on the occurrence rate of 3 m‐scale irregularities in the E‐ and F‐layer at Jicamarca at night. The results show that there is a negative correlation between the occurrence rates of ERI and FRI. Based on the observation of ion drift, the vertical polarized electric field in the FRI is suggested to suppress the ERI. Key Points: Occurrence distributions of E‐region irregularities (ERI) and F‐region irregularities (FRI) in the equatorial ionosphere are obtainedThe occurrence rates of equatorial irregularities in E‐region and F‐region is negatively correlatedThe vertical polarized electric field in the FRI is suggested to suppress the ERI in the equatorial ionosphere [ABSTRACT FROM AUTHOR]

Many studies have performed microphysical retrievals using radars of different frequencies, platforms, and methodologies. However, little is known about the consistency of retrievals derived from different radar platforms (i.e., airborne or spaceborne vs. ground‐based) and their methodologies. This study is the first to directly compare snow mass‐weighted mean diameter (Dm) retrievals from both nadir‐pointing airborne multi‐frequency radars and ground‐based polarimetric range‐height indicator radar scans along the same airborne flight track with a resolution of O(10m) $\mathcal{O}(10\,\mathrm{m})$. Dm retrievals between each method produced mean absolute errors of 0.49, 0.74, and 0.93 mm where the largest differences were between the ground and aircraft retrievals. A triple‐frequency analysis suggests the possibility that snow aggregates were generally composed of needles. These results can be used as a benchmark for comparing retrieval methodologies and highlight the continued uncertainty regarding the optimal approach for ice microphysical retrievals. Plain Language Summary: Both airborne and ground‐based weather radar measurements can be used to estimate snowflake characteristics such as their mean size. However, it is difficult to compare the radar‐estimated mean sizes between these platforms because of the vast methodological differences in how these sizes are estimated and the spatial and temporal differences resulting from each radar's geographical location. This study is the first to directly compare snowflake size retrievals using ground‐based mobile radar scans that collected data along the same path as an overhead‐passing aircraft, thus directly minimizing any error resulting from matching values between radars aboard the aircraft and the ground radar. We also used the aircraft radars' multiple frequencies to investigate what types of particles were dominant throughout the storm. Through this multi‐frequency analysis, we found that it is possible that snow particles were aggregates of thin needles that were stuck together. These results can be used by other researchers and forecasters to understand how snowflake size estimates can vary between different platforms and methodologies. Key Points: Mobile X‐band polarimetric radar Range Height Indictor scans were directly collocated with overpassing multi‐frequency airborne radars during a snowstormThree separate mass‐weighted mean diameter retrievals had mean absolute errors of 0.49, 0.74, and 0.93 mm between each otherThese results provide a one‐of‐a‐kind, high‐resolution benchmark for comparing retrieval methods across various platforms [ABSTRACT FROM AUTHOR]

Capabilities to directly assimilate radar data are implemented within the local ensemble transform Kalman filter (LETKF) and the gain‐form LETKF (LGETKF) algorithms of the Joint Effort for Data assimilation Integration (JEDI) system. The capabilities are evaluated for the analysis and forecast of a severe convection case of 20 May 2019 in the Southern Great Plains using the limited area model version of the FV3 dynamical core (FV3‐LAM) from a recent release for Short‐Range Weather Application (SRW App). The LETKF and LGETKF implementations are shown to produce analyses and short‐range forecasts comparable to those using the ensemble square‐root Kalman Filter (EnSRF) within the Gridpoint Statistical Interpolation (GSI) framework used by current NCEP operational models. In addition, LGETKF retaining only 60% variances for model‐space vertical localization performs similarly to LGETKF retaining 99% of variance and LETKF using observation error‐based vertical localization. JEDI LETKF shows better parallel scalability than LGETKF and GSI EnSRF. Plain Language Summary: The JEDI data assimilation (DA) framework under development will be used by all operational forecasting systems of the U.S. National Weather Service, including the Rapid Refresh Forecast System based on FV3, a dynamic core chosen for next‐generation NWS forecasting systems. In this study, we implemented radar DA capabilities into the JEDI with two local ensemble transform Kalman filter (LETKF) algorithms coupled with limited‐area FV3. Analyses and forecasts with radar DA better match radar reflectivity and radial velocity observations than forecasts without radar DA during the assimilation period. Three‐hour forecasts of precipitation, reflectivity, and updraft rotation show skills comparable to a DA experiment using the ensemble square‐root Kalman filter within the more mature GSI DA system. In addition, the new gain‐form LETKF, which has not been applied to radar DA before, performs quite well, although it is computationally more expensive than the regular LETKF. This work paves the way for using JEDI to assimilate radar data in operational forecasting systems. Key Points: Radar data assimilation capabilities are implemented and tested in Joint Effort for Data assimilation Integration (JEDI), a future data assimilation infrastructure for Unified Forecast System applicationsLocal ensemble transform Kalman filter (LETKF) algorithm with gain‐form vertical localization is tested for radar data assimilation and is found to perform similarly as LETKFThe enhanced gain‐form LETKF and LETKF in JEDI perform similarly as ensemble square‐root Kalman Filter within Gridpoint Statistical Interpolation for radar data assimilation [ABSTRACT FROM AUTHOR]

The ever‐expanding horizon of radar applications demands solutions with high‐end radar functionalities and technologies and is often limited by the available radar equipment, cost and time. A practical method to tackle the situation is to rely on the modelling and simulation of radar systems based on the user requirements. The comprehensive system‐level modelling of a pulsed Doppler radar in MATLAB/Simulink consisting of all the fundamental blocks in the transmit chain, the environment, the receive chain, and the data processing chain is presented in this article. The first half of the article discusses the high‐fidelity simulation of each building block in the radar model. In the second half of the article, the range‐Doppler plot generated from the high‐fidelity radar model is compared and validated using the range‐Doppler plot from a real radar trial. The radar phase noise plays a crucial role in the detection of slowly moving, low radar cross‐section targets in the presence of strong clutter. The article also briefly discusses the effects of radar oscillator phase noise in the range‐Doppler plot. The validated, fully flexible radar model has the advantage of supporting the addition of further building blocks and optimising the parameters based on user requirements. [ABSTRACT FROM AUTHOR]

Ionospheric phase contamination (IPC) is a major contributor to the imprecise retrieval of ocean dynamics parameters by the high‐frequency hybrid sky‐surface wave radar (HFHSSW). Since the direct wave and sea echo of HFHSSW have comparable IPC, the information of ocean dynamics parameters can be preserved by using the IPC extracted from the direct waves to correct the sea echoes. In this article, a wavelet transform (WT) algorithm for HFHSSW sea echo correction is proposed. The direct waves are decomposed using a series of wavelet functions constructed with complex Morlet wavelets in order to extract the IPC and correct the sea echoes. The authors enumerated two examples and counted the correction results for 50 echoes to validate the performance of the WT algorithm. The results demonstrate that the WT algorithm enhances the signal‐to‐noise ratio (SNR) of the sea echoes and suppresses the broadening of the sea echoes. The 6‐dB bandwidth of the positive and negative first‐order Bragg peaks (B+, B−) decreases by 32.96% and 35.04% respectively, while the SNR increases by 1.16 and 1.21 dB respectively. In comparison to the generalised S‐transform (GST algorithm), the computation speed of the WT algorithm is approximately 3.2 times that of the GST algorithm, making it more suitable for practical operation. [ABSTRACT FROM AUTHOR]

Belligerent sides of current military conflicts are first and foremost counting on intelligence, air supremacy, and electromagnetic spectrum dominance. Actual concepts of conducting military operations can be characterised by the massive employment of air defence systems, radars, and electronic warfare systems. An approach is aimed to strengthen air‐defence potential by improving the resilience of pulse radar against electronic warfare threats, such as an electronic attack. To cope with the above‐mentioned situation, a radar intrapulse modulation was designed, where a combination of Costas codes and Walsh‐Hadamard codes is applied. Using a particular waveform together with the proposed model for radar signal processing results in increased resilience against an electronic attack, especially against repeater jamming methods. Furthermore, it is also possible to process radar echoes at low levels of Signal‐to‐Noise Ratio (SNR), which enhances radar electronic counter–countermeasure capability. The main scientific contribution of the paper is in the unique design of the Pulse Compression Filter for Combined Intrapulse Modulation (PCF‐CIM) and in its modelling. Based on the statistical evaluation of results, using the proposed radar waveform together with PCF‐CIM, it is possible to detect radar signals with combined intrapulse modulation in the case of SNR ≥ −14 dB with TPR ≥0.9999 and FPR ≤10−6, where SNR stands for Signal‐to‐Noise Ratio, TPR stands for True Positive Rate, and FPR stands for False Positive Rate. [ABSTRACT FROM AUTHOR]

Human identification and activity recognition (HIAR) is crucial for many applications, such as surveillance, smart homes, and assisted living. As a sensing modality, radar has many unique characteristics including privacy protection, and contactless sensing. Single classification systems have shown to be accurate, but for long‐term solutions both human identification (ID) and human activity recognition (HAR) will need to be integrated in one system where it can be utilised simultaneously. In this article, a novel radar‐based human tracking system is presented where three classifiers are utilised to identify the subject and his/her behaviour. For any kind of motion, the system tracks the subject and detect the type of his/her motion. Based on the detected type of motion, the three classifiers are utilised for identification and activity recognition. The classifiers are built utilising deep transfer learning where three radar datasets are established to train and validate each of the deep networks. To recognise six activities and 10 human subjects, the three classifiers, namely, HAR, Gait ID, and Heart sound ID, achieve superior performance compared to the best reported results in literature with classification accuracies of 97.6%, 100%, and 41.8% respectively. Three successful examples are presented to demonstrate the introduced concept. [ABSTRACT FROM AUTHOR]

The goal of this paper is to propose a method to achieve a higher classification rate in Polarimetric Synthetic Aperture Radar (PolSAR) image classification. In our work, PolSAR features are extracted from Convolutional Neural Networks (CNNs) and also Graph Convolutional Networks (GCNs). Due to the construction of the adjacency matrix on all the data, traditional GCNs usually suffer from a substantial computational cost, particularly in large‐scale remote sensing (RS) problems. To this end, first of all, we propose a new mini‐batch GCN (called Mini‐GCN), which allows to train large‐scale GCNs in a mini‐batch fashion. More significantly, our designed mini‐GCN is capable of inferring out‐of‐sample data without re‐training networks and improving classification performance. Furthermore, as CNNs and GCNs can extract different types of PolSAR features, an intuitive solution to break the performance bottleneck of a single model is to fuse them. Since mini‐GCNs can perform batch‐wise network training (enabling the combination of CNNs and GCNs), we can use the feature fusion strategy. Therefore, in this paper, a local graph‐based fusion method is proposed to couple dimension reduction and feature fusion of the information extracted from the designed CNN and Mini‐GCN. Experimental results on real PolSAR data are very encouraging. Compared to the methods using only single feature and stacking all the features together, the proposed feature fusion method improves the overall classification accuracy on the real PolSAR data sets for more than 5%. Moreover, the experiments conducted on PolSAR datasets, demonstrate the advantages of the used mini‐GCNs over the traditional GCNs and the superiority of the proposed feature fusion method with regards to the single CNN or GCN models. [ABSTRACT FROM AUTHOR]

The range and azimuth information of a target can be obtained after coherent pulse accumulation of the traditional multiframe stepped‐frequency (SF) synthesis wideband echo and spectrum analysis, and high‐resolution two‐dimensional imaging of the target can be achieved. However, the accumulation of a certain number of pulses requires a long beam dwell time, which cannot meet real‐time imaging requirements for high‐speed radar moving platforms. To solve the above problems, a scanning imaging mode is proposed by combining forward‐looking imaging and scanning imaging, and a target echo signal model with the structure of scanning stepped‐frequency is constructed. The SF pulses are grouped and transmitted according to the scanning order, and the echo pulses are sorted and reorganised. After the timing compensation and range Doppler coupling compensation are completed, the target is located and projected. The proposed imaging mode can achieve high‐resolution scanning forward‐looking imaging and can basically attain an azimuth resolution of approximately 0.1° within the forward‐looking scanning range. This imaging mode has higher real‐time performance and a larger target imaging range than the traditional methods. Moreover, the simulation results showed good performance via the scanning imaging method. [ABSTRACT FROM AUTHOR]

With radar sounders, coherent backscattering simulations from global planetary digital elevation models (DEMs) typically display a deficit in diffuse clutter, which is mainly due to the implicit assumption that roughness at scales below the resolution of the DEM is absent. Indeed, while polynomial approximations of the phase evolution across the facet allow for fast and mathematically rigorous simulators, the coarse resolution of these planetary DEMs leads to a potentially significant portion of the backscattering response being neglected. In this paper, we derive the analytical phase response of a rough rectangular facet characterized by Gaussian roughness and a Gaussian isotropic correlation function under the linear phase approximation. Formulae for the coherent and incoherent power scattered by such an object are obtained for arbitrary bistatic scattering angles. Validation is done both in isolation and after inclusion in different Stratton‐Chu simulators. In order to illustrate the different uses of such a formulation, we reproduce two lunar radargrams acquired by the Lunar Radar Sounder instrument with a Stratton‐Chu simulator incorporating the proposed rough facet phase integral, and we show that the original radargrams are significantly better‐reproduced than with state‐of‐the‐art methods, at a similar computational cost. We also show how the rough facet integral formulation can be used in isolation to better characterize subglacial water bodies on Earth. Key Points: Planetary digital elevation models are often of coarse resolution and depict a surface that is smooth at scales below that resolutionPolynomial phase approximations can be used to simulate radar scattering rigorously but they overestimate the coherence of reflected signalsWe analytically derive the linear phase approximation formula on a rough rectangular facet, leading to much better clutter simulations [ABSTRACT FROM AUTHOR]

A new incoherent scattering radar established at Sanya (18.3°N, 109.6°E; SYISR) has made it possible to directly measure the fine structure of the ionospheric E‐F valley. An intriguing phenomenon termed "ionospheric drizzle" was revealed by the month‐long continuous observation of complete ionospheric profiles with a temporal and vertical resolution of 0.8 s and 4.5 km. It manifests as weak plasma "streaks" in the strength of ∼103–104 cm−3 that detach from the F‐layer base and extends downward to the sporadic E (Es) layer during pre‐dawn hours, with an apparent descent speed of ∼10–20 m/s. The frequently observed "ionospheric drizzle" provides additional plasma to enhance the Es layer. Subsequent testing particle simulations were performed, revealing the critical role of the neutral winds in the plasma descent. This downward coupling process enhancing the Es layer is thus supposed to be important in communication and navigation. Key Points: Using the Sanya ISR, "ionospheric drizzle", a phenomenon linking the F‐layer and sporadic E layer at pre‐dawn hours, was revealedStreak‐like plasma detaches from the F‐layer base with a descent speed of ∼10–20 m/s and significantly enhances the Es layer at ∼120 kmTest particle simulations are performed to explain the critical role of neutral winds in the "ionospheric drizzle" formation [ABSTRACT FROM AUTHOR]

An "atlas" of the Lunar penetrating radar (LPR) patterns is organized and a comprehensive interpretation of the lunar subsurface layers in the areas of the Chang'E (CE) mission is proposed. There are three layers inferred by the LPR high‐frequency profiles of the CE‐3 and CE‐4. The first two layers (i.e., the fine regolith and the ejecta layer) at CE‐3 and CE‐4 sites have the same strata type but differ in internal structure and thickness. The third layer at the CE‐3 site is inferred as the paleoregolith, while at the CE‐4 site, it is inferred as the alternating layer with fine materials, ejecta, and fragments. Due to the limited penetration depth of the CE‐5 LPR, the data disclose only the fine regolith, with support from the empirical ejecta distribution model. The thicknesses, physical properties, and equivalent growth rates of lunar regolith at three landing sites are estimated and discussed in detail. The lunar regolith thicknesses inferred by the CE‐3 and CE‐5 LPR data are both approximately 1.0 m. In contrast, the thickness of the lunar regolith at the CE‐4 site is 10.0 m, which is greater than that at the other two landing sites. However, the equivalent growth rate of the regolith at the CE‐3 and CE‐5 landing sites is four times greater than that at the CE‐4 landing site. This illustrates that with the increase in lunar regolith thickness, the influence of small impact gardening events on the lunar regolith reconstruction gradually weakened, and the self‐buffering effect avoids the fast growth of lunar regolith. Plain Language Summary: Lunar penetrating radar (LPR) data from the Chang'E (CE) missions have revealed the complexity of the lunar stratigraphic sequences. The available LPR sections from the CE‐3, CE‐4, and CE‐5 expeditions have been significantly analyzed to infer the lunar subsurface layers; however, many details of the reflector patterns from the LPR images are neglected, which contain significant information on the sedimentary deposits. Our work proposes a synthesized interpretation of subsurface structuring in the areas of CE mission radar data collection and an organization of an "Atlas" of the radar patterns used to interpret the geological layers. We identified three main layers in the subsurface at CE‐3 and CE‐4 landing sites and only one stratigraphic layer at CE‐5. We detail the characteristics of radar patterns that have been interpreted as regolith (immature and mature), crater ejecta, paleoregolith, and multilayer ejecta‐regolith deposits. In addition, we found that the equivalent growth rate of lunar regolith is related to its own thickness and the structure of the underlying layer, with the regolith equivalent growth rate at CE‐3 and CE‐5 landing sites being four times higher than that at CE‐4 landing site. Key Points: An atlas of the lunar penetrating radar patterns is organized to comprehensively interpret the lunar subsurface layers of Chang'E (CE) landing areasRegolith layers found in the different CE landing areas are characterized by two distinct patterns interpreted as early and late stageThe equivalent growth rate of CE‐5 lunar regolith indicates that its underlying layer is loose ejecta deposit [ABSTRACT FROM AUTHOR]

Wind energy is a major and rapidly expanding renewable energy source. Horizontal‐axis wind turbines, the main tool in this industry, induce mortality in flying animals and consequently bring about conservation concerns and regulatory restrictions. We utilized a unique combination of RADAR, LIDAR and ultrasonic acoustic recorders to test the utility of a novel technology meant to prevent wind turbine‐related mortality in bats. Our drone‐mounted deterrent device produces a pulsating combination of strong auditory and visual signals while moving through the air. LIDAR was used to assess the device's impact below its flight altitude and RADAR to assess its influence above its flight altitude. Continuous acoustic recordings from ground level to ~400 m above‐ground‐level were used to monitor bat activity in the research site. We recorded the nightly altitudinal distributions of multiple bat species throughout the experiment. Analysis revealed a significant change in activity while the deterrent was flying compared to baseline conditions. We also recorded a significant ~40% decrease below and a significant ~50% increase above the deterrent's flight altitude during its operation compared to the post‐flight control. The tested technology is independent of wind farm activities and does not require modifying wind turbine form or operation procedures. The device differs from previously proposed solutions by being dynamic – moving in the airspace and emitting constantly changing signals – thus decreasing the probability of animal habituation. Our findings suggest that the deterrent could dramatically decrease wind turbine‐related mortality by deterring bats from approaching rotor‐swept airspace. Focused implementation in conditions where bat activity and energy production are in conflict may provide a practical, cost‐effective mortality mitigation solution compared to current alternatives. Thus, our results should be considered by the wind‐turbine industry and environmental monitoring and animal conservation organizations, as well as by regulatory agencies, when pursuing alleviation of wind turbine‐related mortality. [ABSTRACT FROM AUTHOR]

A new satellite observation concept to estimate upward air mass flux in convective storms has been proposed using a convoy of small radars that measure reflectivity only. The approach is to analyze a pair of radar reflectivity profiles obtained within 30–120 s of one another, and infer the upward transport above the freezing level and at a nominal 3‐km horizontal resolution from the reflectivities and their temporal change. This paper summarizes the theoretical basis for this approach, with quantitative justification using sensitivity analyses of convection‐permitting model simulations and from ground‐based zenith profiler data. We then describe and quantify the performance of the approach to detect updrafts from the radar observations. Finally, we illustrate the expected performance of retrievals of the vertical transport and evaluate their ability to meet the objectives of the "Investigation into Convective Updrafts" mission, selected by NASA to place in orbit in 2027–2028 a convoy of three identical Ka‐band radars measuring radar reflectivity within their common swath. Plain Language Summary: This paper describes a new concept to measure the vertical transport in updrafts in convective storms, from space, using pairs of small radars that measure radar reflectivity only. The paper first presents the theoretical relation between the evolution of reflectivity from the time of the first radar observation to the time of the last (up to 2 min later), on one hand, and the underlying vertical velocities in the updraft. The paper then demonstrates the forward‐sensitivity of reflectivity, under the practical radar constraints, to the vertical velocities. And finally the paper demonstrates the ability to invert this forward sensitivity and produce retrievals of vertical velocity with low uncertainty. Key Points: A new satellite observation concept to estimate air mass transport in convective updrafts is explainedIt is shown that chronological sequences of radar reflectivities are sensitive to the characteristics of vertical transportIt is shown how the characteristics of the vertical transport can be derived from the radar observations [ABSTRACT FROM AUTHOR]

In recent years, frequency‐multiplexed metasurfaces have received extensive attention due to the increasing demands for device integration and communication capacity. However, most of previously reported works can only manipulate either surface waves (SW) or spatially propagating waves (SPW). In this paper, a frequency‐multiplexed holographic‐reflective‐integration (HRI) coding metasurface is proposed, which can independently manipulate SW and SPW at different frequencies with a shared aperture. To be specific, the metasurface can act as a holographic metasurface to manipulate SW at low frequency and a reflective metasurface to manipulate SPW at high frequency. The performance of the frequency‐multiplexed HRI coding metasurface is validated by matched simulation and measurement results of versatile wavefront and polarization manipulations. Due to the advantages of low profile, high aperture usage, and multifunction integration, the proposed frequency‐multiplexed HRI coding metasurface is promising to be applied in wireless communications, radar detections, and holographic technology. [ABSTRACT FROM AUTHOR]

Obstacles on railway tracks are a factor hindering safe and stable operation. For this reason, obstacle detection systems have been introduced at level crossings, slopes and under platforms. However, they have been introduced only in limited sections for limited applications. Therefore, the authors considered to introduce an obstacle monitoring system that combines 90 GHz band millimeter‐wave and Radio over Fiber (RoF) technology, as an obstacle monitoring system over tracks to monitor the entire line. Since the millimeter‐wave band has a wide bandwidth, high precision detection is possible when they are used in radar. In addition, since radar control units can be grouped in one place by introducing the RoF technology, we can build a system at a low cost. In order to study the feasibility of introducing a new obstacles monitoring system combining 90 GHz band millimeter‐wave and RoF technology in railway environment, a field test using prototype equipment was conducted on a railway track. As a result, it was confirmed that the prototype radar system could detect humans and non‐metallic objects entering a track at a distance of about 200 m from the location of the prototype system. These results shows that the proposed system has the potential to be introduced as a new railway obstacle monitoring system using 90 GHz band millimeter‐waves and RoF technology. © 2023 The Authors. IEEJ Transactions on Electrical and Electronic Engineering published by Institute of Electrical Engineer of Japan and Wiley Periodicals LLC. [ABSTRACT FROM AUTHOR]

Polarization and phase are two essential properties of electromagnetic (EM) waves. A transmissive metasurface is proposed that can simultaneously manipulate the polarization and phase of the EM waves. The design has a powerful capability of rotating the polarization to any desired azimuth direction for a linearly polarized (LP) wave and achieving the cross‐polarization conversion for a circularly polarized (CP) wave. Meanwhile, the transmission phase of the cross‐polarization can be dynamically controlled for the CP wave. The proposed metasurface is composed of two types of substrate‐integrated waveguides (SIW) in a cross arrangement, which has an insertion loss of less than 0.3 dB from 9.7 to 10.3 GHz. Some samples are fabricated and measurements are performed, which are in satisfactory agreement with the theoretical and simulated results, indicating the feasibility of the proposed method. It is believed that the proposed design has many potential applications in the fields of imaging, communication, and radar systems. [ABSTRACT FROM AUTHOR]

Earth's ionosphere has long been targeted as a medium for remote sensing of explosive terrestrial events such as earthquakes, volcanic eruptions, and nuclear/conventional weapon detonations. Until now, the only confirmed ionospheric detections have been of very large events that were easily detectable through other traditional global sensor systems (e.g., seismic). We present the first clear, confirmed detections of relatively low yield 1‐ton TNT‐equivalent chemical explosions using pulsed Doppler radar observations of isodensity layers in the ionospheric E region. The shape and spectra of the detected waveforms closely match predictions from the acoustic ray tracing and weakly nonlinear waveform propagation models. The explosions were roughly three orders of magnitude lower yield than any previous confirmed ionospheric detection and represent the first conclusive evidence that explosions of this size can have clear impacts on the ionosphere. This technique could improve the remote detection of both anthropogenic and natural explosive events. Plain Language Summary: Explosions, even of modest yield, generate copious amounts of acoustic waves across a wide range of frequencies. While the high frequencies are quickly absorbed by the atmosphere, the lowest frequencies, in the sub‐audible infrasound part of the spectrum, are capable of traveling to great distances. Typically this infrasound is detected on the ground using highly sensitive listening equipment such as microbarometers. We present a different method, however, where we utilize the fact that the upper atmosphere is ionized (the ionosphere) and is therefore a good target for a radar. As the sound wave passes through the ionosphere it sloshes the bulk ions such that it shows up an oscillating radar target. We use this new technique to clearly detect explosions with yields of 1‐ton TNT equivalent. These detections are 500 times smaller than previous confirmed detections using the ionosphere as a sensor for explosions. Key Points: Infrasound from 1‐ton TNT‐equivalent chemical explosions are clearly detectable using pulsed Doppler radar of the ionosphereObservations match the modeled temporal and spectral predictions of infrasound propagationStrong azimuthal differences in waveform shape and strength could be caused by uneven terrain or complex wind fields [ABSTRACT FROM AUTHOR]

This article presents a deep neural network‐based constant false alarm rate (NNB‐CFAR) detector for simulated high‐frequency surface wave radar (HFSWR) data. A deep neural network is trained to identify fluctuation parameters of each cell of a range‐Doppler power spectrum based on the patterns present in the neighbouring cells. The estimated parameters are then used for calculating a detection threshold with a user‐specified probability of false alarm. To train the network, a realistic model of HFSWR echoes is used for generating a large labelled range‐Doppler image dataset, including many possible clutter scenarios and interfering target echoes. Several CFAR windows are extracted from the training range‐Doppler dataset and used as training data. The neural network is trained to replicate the output of a maximum likelihood estimator based on the reference cells of the CFAR window. The NNB‐CFAR algorithm was then compared to traditional CFAR algorithms by identifying targets in the second set of simulated range‐Doppler images. The probability of detection was also experimentally measured in the context of HFSWR for all algorithms. Results show that the technique can significantly improve detection rates amid strong clutter. [ABSTRACT FROM AUTHOR]

In high frequency (HF) hybrid sky‐surface wave radar, the first‐order sea clutter broadening is severe under the action of ionospheric phase disturbance and bistatic angles. In this study, a spread sea clutter suppression method based on prior knowledge and joint domain localised (JDL) algorithm is proposed. Firstly, the first‐order sea clutter broadening mechanisms and model under the action of ionospheric phase disturbance and bistatic angles are introduced. Secondly, the space‐time coupling characteristics of the first‐order sea clutter is analysed. Then in order to better suppress clutter or avoid target information loss, the spread sea clutter suppression method based on space time adaptive processing is proposed. In the proposed method, the space‐time distribution characteristics and simulation model of the first‐order sea clutter is used as the prior knowledge into JDL algorithm to improve the sea clutter suppression performance. Finally, the performance of sea clutter suppression based on JDL algorithm is simulated and analysed. And the proposed spread sea clutter suppression method based on prior knowledge and JDL algorithm is proved by measured data. [ABSTRACT FROM AUTHOR]

It is difficult for a receiver to intercept the signals from a radar system that can emit low probability of intercept (LPI) polyphase coded signals. The traditional Wigner Hough transform (WHT) algorithm requires a large amount of computation and takes a long time to estimate the parameters of the LPI radar polyphase coded signals. To address this problem, an iterative angle search (IAS) algorithm, which when used in combination with the WHT algorithm significantly reduces the computational cost is proposed. When the signal‐to‐noise ratio is in the range of −4 to 20 dB, the carrier frequency, number of subcodes, and number of cycles of the carrier frequency per subcode of five polyphase coded signals, namely, Frank, P1, P2, P3, and P4, are accurately estimated in simulation experiments. Based on the selected IAS algorithm parameters, the estimation accuracy of the proposed method is the same as that of the traditional WHT algorithm. However, the operation time is only 5.14% of that of the traditional method. The IAS algorithm has certain application prospects. Experiments indicate that the proposed algorithm provides excellent performance and can rapidly and accurately estimate the parameters of LPI polyphase codes. [ABSTRACT FROM AUTHOR]

In the D‐region, the ionization rate cannot be detected directly with any known measurement technique, therefore it must be estimated. Starting from space‐based measurements of precipitating particle flux, we estimate the ionization rate in the atmosphere using the Electron Precipitation Monte Carlo transport method. This ionization rate is used to calculate the expected electron density in the D‐region with the Glukhov‐Pasko‐Inan five species (GPI5) atmospheric chemistry model. We then compare the simulated electron density with that measured by the Poker Flat Incoherent Scatter Radar (PFISR). From ground‐based radar measurements of electron density enhancements due to sub‐relativistic and relativistic electron precipitation, we present a method to extract the ionization rate altitude profiles using inverse theory. We use this estimation of ionization rate to find the energy distribution of the precipitating particles. With this inverse method, we are able to link ground measurements of electron density to the precipitating flux in a time dependent manner and with uncertainty in the inverted parameters. The method was tested on synthetic data and applied to specific PFISR data sets. The method is able to retrieve the ionization rate altitude profiles that, when forward modeled, return the expected electron densities within ∼7% error as compared to the PFISR data. For the case presented here, the arbitrary energy distribution inversion results are comparable in magnitude and shape to those presented in Turunen et al. (2016, https://doi.org/10.1002/2016jd025015) for the inversion of a single event of pulsating aurora observed by EISCAT. Plain Language Summary: Electrons expelled from the Earth's radiation belts by electromagnetic waves enter the upper atmosphere and travel through it. Interactions of these electrons with atmospheric constituents lead to the ionization of the atmospheric species. This ionization produces enhancements of electron density in certain altitude ranges that depend on the incoming particles' energy. Satellites orbiting Earth at an altitude of a few hundred km can measure the flux of the entering particles. We use a modeling technique to simulate their behavior in the atmosphere, including the electron density modification, starting from the satellite measurements. Radars at ground stations on Earth can detect the electron density enhancements in the atmosphere. We use inverse theory to estimate the ionization rate and flux of precipitating particles starting from the radar electron density measurements. Key Points: We compare D‐region radar measurements of electron density to a forward‐modeled electron precipitation flux and spectrumA method is presented to infer ionization rates from D‐region electron density measurements made by radar, accounting for time dependence and to infer precipitating flux from D‐region ionization rates with exponential or arbitrary energy distributionsWe establish a time‐dependent inversion from radar‐observed electron density to an estimate of the precipitating energetic electron source [ABSTRACT FROM AUTHOR]

We associate new data from icebear, a coherent scatter radar located in Saskatchewan, Canada, with scale‐dependent physics in the ionosphere. We subject the large‐scale icebear 3D echo patterns (treated as 2D point clouds) to a data analysis technique hitherto never applied to the ionosphere, a technique that is widely applied in cosmological red‐shift surveys to characterize the spatial clustering of galaxies. The technique results in a novel method to calculate the spatial power spectral density of the greater ionospheric irregularity field. We compare results from this method to in‐situ plasma density and magnetic field observations from the Swarm mission. We show that there is a remarkable similarity between echo clustering spectra in the E‐region and the field‐aligned current structuring spectrum observed in the F‐region: a clear and characteristic preferred scale (5 km) both in the E‐ and F‐region spectra. We discuss the possibility that this represents evidence of an energy injection into the ionospheric irregularity field via energetic particle precipitation, but offer alternative interpretations with wider connotations for the ionosphere‐magnetosphere system. These findings open new and promising avenues of research for the study of the location of ionospheric scatter echoes with 3D information. It constitutes a novel way to consider the pattern of ionospheric irregularities over wide fields of view when there is an abundance of radar echoes, which allows for the analysis of radar data as point clouds. Plain Language Summary: With the advent of precision radar data from the aurora containing detailed information about radar echo locations, we are in a position to apply statistical methods from cosmology to extract information about plasma turbulence in the ionosphere. This interdisciplinary paper presents some birds‐eye view discussions about the use of correlation functions in physics, showing how it can be used to understand physics on virtually all spatial scales in the observable universe. We present results pertinent to the ionosphere, shedding light on plasma turbulence and its relation to energetic particles in the aurora. Here, we use observations both from space, by the orbiting satellites in the European Space Agency's Swarm mission, and using an experimental auroral radar in Saskatchewan, Canada. Key Points: Clustering Statistics are used to extract large scale turbulence information from 3‐m structures in the E‐regionE‐region clustering spectra are remarkably similar to in‐situ spectra from field‐aligned currents in the F‐regionA preferential 5‐km scale is simultaneously observed in the E‐region and in the F‐region field‐aligned currents [ABSTRACT FROM AUTHOR]

Martian ice holds an important key to interpreting Mars' past climate, but much is still unknown regarding the distribution and properties of Mars' ice deposits. Previous surveys identified craters that contain "outlying" deposits of ice separate from, but nearby, the north and south polar layered deposits (NPLD and SPLD). There are many differences between the characteristics of the NPLD and SPLD, which may or may not be shared by these outlying deposits, and may provide clues to the climate conditions under which ice in the polar regions formed. Ground penetrating radar is one of the crucial datasets for understanding Martian ice, as it can probe the subsurface and place constraints on the properties of buried materials. We have analyzed 517 SHARAD radar tracks across 24 ice deposits housed within craters, including quantifying surface reflectivity and identifying the presence of subsurface reflectors. After examining the subsurface radar observations, we determined that the northern outlier deposits share many common characteristics with the NPLD, and thus may have been emplaced concurrently or at least under similar environmental conditions. The southern outlying crater deposits exhibit a variety of subsurface characteristics, and likely represent two or more populations of ice‐rich deposits that may have differing emplacement histories. Plain Language Summary: Mars has two large ice caps at its poles, which combined contain a similar volume of ice as Greenland on Earth. Near these large ice caps are craters that are also filled with ice, referred to as outlying crater ice deposits. These outlying crater ice deposits may or may not have formed at the same time as the polar caps. Like scientists on Earth use ice cores to analyze how our climate has changed over time, radar observations of ice on Mars can penetrate deep into the ice and act as digital ice cores, recording changes to the ice deposited over time. We use these radar observations to analyze the history of the outlying crater deposits and find that the northern deposits may have had a similar history to the north polar cap, while the southern deposits may have a more varied history. Key Points: We analyzed the radar surface and subsurface properties of outlying ice deposits in craters near the Martian polesSouthern outlying deposits likely represent two or more different depositional historiesNorthern outlying deposits likely record the same depositional history as the north polar layered deposit [ABSTRACT FROM AUTHOR]

As a tropical cyclone (TC) intensifies, the tangential wind field expands vertically and increases in magnitude. Observations and modeling support vortex height as an important TC structural characteristic. The Tropical Cyclone Radar Archive of Doppler Analyses with Recentering data set provides kinematic analyses for calculation of the height of the vortex (HOV) in observed storms. Analyses are azimuthally‐averaged with tangential wind values taken along the radius of maximum winds. A threshold‐based technique is used to determine the HOV. A fixed threshold HOV strongly correlates with current intensity. A dynamic HOV metric quantifies vertical decay of tangential wind with reduced dependency on intensity. Statistically significant differences are present between dynamic HOV values in groups of steady‐state, intensifying, and rapidly‐intensifying cases categorized by subsequent changes in pressure. A tall vortex is always observed in cases meeting a pressure‐based rapid intensification definition. Taller vortices are also evident with slower intensification. Results suggest HOV may be a helpful predictor for TC intensification. Plain Language Summary: As a tropical cyclone gets stronger, the wind field of the storm grows taller in the atmosphere. The height‐intensity relationship is known to be present from the beginning of a tropical cyclone until its peak strength. A large data set of airborne radar observations in tropical cyclones is used to show the strength of the relationship between vortex height and current intensity. A tall vortex is always present in observed cases for periods of rapid intensification during which the minimum surface pressure at the storm center drops at a high rate. Drops in minimum surface pressure are associated with increases in wind and size in tropical cyclones. A taller vortex also favors intensification at slower rates. Improved understanding of the role that tropical cyclone height plays during intensification may be helpful for forecasting changes in intensity of these storms. Key Points: Vertical extent of the tropical cyclone wind field correlates strongly with current intensity in observed stormsDeep vertical vortex structure is always present in observed cases meeting a pressure‐based rapid intensification definitionVortex height decreases with increasing vertical wind shear, but taller storms intensify more in moderate shear [ABSTRACT FROM AUTHOR]

The assimilation of Doppler radar radial wind observations is important for improving tropical cyclone (TC) prediction. However, the specific impacts and contributions of these observations over different areas are still unclear. In this study, the impact of assimilating radar radial winds within the inner‐ and outer‐cores of TCs is evaluated. For TC Mujigae (2015), analyses suggest that although the outer‐core observations better improve the upper‐level outflow of the TC, the inner‐core observations contribute more to enhancing tangential wind and updraft near the eyewall as well as correcting the TC size, warm core structure, and asymmetrical eyewall convection. The improvements conferred by the assimilating the total observations in the analysis and forecasting of TC tracks and intensities are mainly contributed by the inner‐core observations. This is probably because: (a) the model has a higher deficiency in simulating the TC inner‐core structure, which leads to a larger background deviation relative to the observations and the assimilation increment contributed by the inner‐core observations; (b) as determined by the stronger nonlinearity of the physical processes, the ensemble spread (i.e., model uncertainty) around the inner core is larger, resulting in a more distinct impact of data assimilation. The significant improvements in the inner‐core observations are further consolidated by analyses of two other TCs of different sizes and intensities, in which the number of inner‐core observations accounts for only 1/3 of the total on average. The TC inner‐core area should be a major consideration of future TC observation projects. Plain Language Summary: This study analyzes the individual impact and contribution of the radar radial wind observation within the inner‐ and outer‐cores of tropical cyclones (TCs) to its analysis and forecasting. Regarding the case study of TC Mujigae (2015), the inner‐core observations contribute more to enhancing tangential wind and updraft near the eyewall as well as correcting the TC size, warm core structure, and asymmetrical eyewall convection. The improvements of radar data assimilation to TC track and intensity are found to mainly come from the assimilation of inner‐core observations. This may come from two aspects: (a) the model has a higher deficiency in simulating the precise structure of TC inner‐core, which leads to a larger assimilation increment by inner‐core observation. (b) the physical processes of the TC inner‐core region have a stronger nonlinearity, which makes a larger uncertainty in the model background, resulting in a more distinct impact of data assimilation. These results are further validated by two other TCs of different sizes and intensities. The TC inner‐core area should be a major consideration of future TC observation projects. Key Points: The impacts and contributions of assimilating radar radial winds within tropical cyclone (TC) inner‐ and outer‐core regions are analyzed for three TC casesThe improvements on TC track and intensity are primarily due to the assimilation of inner‐core observationsThe dominant impact of inner‐core data is due to the large model deficiency and strong nonlinearity of TC inner‐core dynamic processes [ABSTRACT FROM AUTHOR]

Attenuation of radar waves in the subsurface can be quantified with a constant‐Q approximation through time‐frequency analysis. We implement the centroid frequency‐shift method and study Radar Imager for Mars' Subsurface Exploration (RIMFAX) data acquired along the Mars 2020 Perseverance rover traverse. Attenuation is among key media properties, but quantified estimates need to account for instrument characteristics and limitations in the analysis technique. We ensure accurate constant‐Q characterization and present the first estimates of radar attenuation in the upper 5 m of the shallow Martian subsurface. Over Jezero Crater Floor, constant‐Q is on average 70.4 ± 7.7, which equals an attenuation of −2.6 ± 0.3 dB/m at RIMFAX' 675 MHz center frequency. Regions comprising the Máaz or Séítah formations have similar attenuation properties that are consistent with magmatic lithologies. Plain Language Summary: First estimates of radar attenuation in the shallow Martian subsurface are presented. Estimates are from Jezero Crater Floor, along the drive path of the Mars 2020 Perseverance rover. Attenuation is among key media properties that describe radar wave propagation and can relate to lithological properties. Estimates of signal losses are consistent with magmatic lithologies and differences between distinct regions on Jezero Crater Floor are not detected. Key Points: First estimates of radar attenuation in the shallow Martian subsurface are on average −2.6 dB/m at the Radar Imager for Mars' Subsurface Exploration (RIMFAX) 675 MHz center frequencyResults are consistent with magmatic lithologies on the Jezero Crater FloorThe centroid frequency‐shift method is adequately implemented for RIMFAX analysis [ABSTRACT FROM AUTHOR]

The performance of 4‐km Weather Research and Forecasting model in predicting reflectivity structure in China over three summer months is investigated using three‐dimensional (3D) reflectivity observations. Three verification domains, namely Southern China (SC), Central and Eastern China , and North China, that correspond to the three major rainfall centers of mainland China are selected. Results show that the forecasts reproduce the distribution and diurnal variation of precipitation well, but significant differences exist in the vertical distributions of the predicted and observed reflectivities. In observations, the highest frequency (of reflectivity ≥35 dBZ) occurs between 3 and 6 km, whereas it is at the surface in the forecast. The forecasts tend to over‐predict reflectivity intensity at the lower levels, especially in SC. Further evaluation using object‐based verification methods show that the forecasts greatly underestimate the afternoon peak frequency of precipitation clouds with reflectivity >30 dBZ. The forecasts fail to reproduce the diurnal variation of 35 dBZ mean and maximum height of the objects, producing less variation than observations. Analyses show that the failure in properly reproducing small‐scale reflectivity objects (with diameter <100 km) is primarily responsible for the underestimation of the mean and maximum object heights. Evaluation using additional 3D information show that the forecasts tend to produce a greater proportion of faster‐moving small‐scale objects. This study reveals that the simulation of the 3D structure of precipitation clouds in terms of reflectivity remains a great challenge, especially for smaller convective cells. Plain Language Summary: The simulation of precipitation clouds is associated carries the largest uncertainty in numerical weather prediction and climate models. With continued advancement in observations and numerical models, forecasts of horizontal distribution, intensity, diurnal variation and propagation of precipitation have been greatly improved. However, faithful representation of three‐dimensional (3D) cloud structure remains a great challenge, with the lack of systematic evaluations being one of the key causes. In this study, 3D gridded radar reflectivity observations are used to evaluate the precipitation clouds structure (with reflectivity ≥30 dBZ) predicted at a convection‐permitting‐resolution (CPR) over three summer months of 2016 in China. The evaluation reveals differences between the simulated and observed reflectivity structures, including the reflectivity intensity profile, the 35 dBZ mean and maximum height, the fraction of fast‐moving objects. CPR models still have difficulties in simulating 3D reflectivity structures especially for relatively small‐scale objects (with diameter <100 km). Key Points: Reflectivity structure predicted by the 4‐km Weather Research and Forecasting model are evaluated using 3D radar observationsThe model overpredicts the intensity of reflectivity at lower levels and fails to reproduce the diurnal variation of object heightThe failure to correctly reproduce the structure of smaller reflectivity objects is primarily responsible for the deviations [ABSTRACT FROM AUTHOR]

Radar‐derived refractivity provides moisture information near the surface, which plays a crucial role in convective initiation and of heavy rain. In this study, the high‐resolution Weather Research and Forecasting local ensemble transform Kalman filter data assimilation system was employed for two cases in the Southwest Monsoon Experiment to conduct two experimental sets. The first set was applied in both cases to investigate the effects of assimilating radar‐retrieved refractivity along with reflectivity and radial wind. The second set was conducted in the second case to examine the benefit of increasing the frequency of refractivity assimilation and investigate the optimal strategy to assimilate refractivity. Results of the two cases revealed that assimilating reflectivity and radial velocity modified near‐surface humidity on the basis of the flow‐dependent error correlation estimated by the ensemble, but the spatial distribution may not be fully accurate, causing underestimation of rainfall. With further refractivity assimilation, stronger convergence and more accurate low‐level moisture, temperature, and wind field corrections were obtained, leading to superior forecasts for both light and heavy rainfall during six hours. The results of the second set indicated that increasing the assimilation interval of refractivity enabled capturing the dramatic moisture variation and enhancing wind convergence, resulting in short‐term forecast improvement. The strategy that solely assimilated refractivity before the appearance of the convection system optimized the correction of environmental moisture, then accurately represented the humidity and strengthened the wind convergence when precipitation occurred. Consequently, the achieved improvement of the short‐term forecast was most noteworthy, particularly for heavy rain. [ABSTRACT FROM AUTHOR]

With the advancement of manoeuvrability and the increasement of coherent processing interval (CPI), the observed target might be of multiple motion stages. Therefore, most existing long‐time coherent integration (LTCI) algorithms based on the assumption of single‐motion stage is not proper any more. To address this problem, this letter proposes an effective motion parameters estimation algorithm, which is the key step of LTCI, for the manoeuvring weak target with multiple motion stages based on range symmetry transform and short‐time fractional Fourier transform (RST‐STFrFT). The effectiveness of the proposed algorithm is verified by signal‐level simulations. [ABSTRACT FROM AUTHOR]

Small‐array high‐frequency surface wave radar (HFSWR) is widely used to monitor maritime targets as it can be used to save on‐land resources. In small‐array HFSWR systems, the main lobe of the receiving angle spectrum is significantly broadened. In complex clutter backgrounds, an extremely wide beam severely influences clutter suppression performance; consequently, targets with a low signal‐to‐clutter ratio (SCR) may be eliminated, or the angle may be barely estimated. This study proposes a space‐time adaptive processing (STAP) algorithm based on hyper beamforming (HBF) to improve the clutter suppression performance of small‐array HFSWR. In addition, HBF can obtain more independent identical distributed training samples than the conventional beamforming; thus, the STAP algorithm can extract the clutter information with high accuracy in the covariance matrix estimation. Moreover, this study combines an efficient STAP algorithm with a joint domain localised (JDL) algorithm to improve clutter suppression. Based on the experimental results, the proposed HBF‐JDL algorithm performs satisfactorily and significantly improves the SCR. Moreover, HBF‐JDL is still applicable at lower SCRs of the target compared with JDL. [ABSTRACT FROM AUTHOR]

This study considers designing constant‐modulus waveforms for multiple‐input‐multiple‐output radar in spectrally crowded environment. The mutual information is used as the waveform design metric. A constant‐modulus constraint is imposed on the waveforms to improve the hardware efficiency. To enhance the spectral compatibility of the transmit waveforms, a precise control on the interference energy produced on each reserved bandwidth is considered. To tackle the multi‐spectrally constrained waveform design problem, a minorisation‐maximisation based method is developed, and a quadratic function to minorise the objective function is derived. Then an alternating direction method of multipliers is used to tackle the quadratically constrained quadratic programming problem at each iteration. The effectiveness of the presented algorithm is demonstrated via simulation results. [ABSTRACT FROM AUTHOR]

In this study, an anti‐deception jamming target tracking algorithm based on the data‐level fusion is proposed in a distributed radar network. First, the consensus covariance intersection (CCI) algorithm is proposed to improve tracking performance by introducing the consensus theory to the field of covariance intersection fusion. Second, unscented Kalman filter is utilised to implement the preprocessing of distributed filtering. Then, two distributed target discrimination schemes are developed for non‐collaborative and collaborative false targets respectively. For non‐collaborative false targets, according to the characteristics that estimated spatial locations of the false target from different radars are relatively scattered, a false target elimination method based on nearest neighbour algorithm is proposed. For collaborative false targets, after equipped with passive radars that are less vulnerable to interference, the consensus algorithm is introduced to convey the real target information to the unconnected active radars, thus achieving an effect of global anti‐deception jamming. Finally, the CCI algorithm is deployed for distributed fusion of physical target tracking, so as to improve the overall estimation performance. [ABSTRACT FROM AUTHOR]

Multicarrier technology is widely used for improving the performance of beampattern synthesis in frequency diverse array multiple‐input and multiple‐output (FDA‐MIMO) Radar. However, how to use multicarrier technology to achieve highly focussed beampattern synthesis is still an open problem. To this end, the authors first establish the system model of FDA‐MIMO radar with multicarrier transmission and analyse the parameters influencing beampattern synthesis by Cramér–Rao lower bound derivation. It can be recognised that frequency increments and multicarrier distribution are key parameters hindering highly focussed beampattern synthesis. On top of the investigation, a simple yet effective Multidimensional Non‐linear Frequency Component, named multidimensional frequency components (MNFC), is proposed for forming a highly focussed beam. Specifically, MNFC is a two‐dimension frequency component for FDA‐MIMO radar. The first dimension is the frequency increment weighted by the Dynamic Taylor Window Function that effectively decouples the joint‐range‐angle beampattern. The second dimension is a non‐linear multicarrier weighted by Log with a Linear Coefficient for further optimising dot‐shaped beampatterns for target indication with high precision. Finally, numerical simulations and comparative experiments are performed to validate the superiority of the MNFC in beampattern synthesis. [ABSTRACT FROM AUTHOR]

The high‐frequency (HF) hybrid sky‐surface wave system is a new early warning radar. However, due to the influence of bistatic angle and ionospheric phase path disturbance, the echo spectrum will be widened, which seriously affects the ability of detecting slow targets of ships. In view of the overlapping of positive and negative Bragg broadening peaks caused by the large amplitude ionospheric phase path disturbance in the echo spectrum of HF sky‐surface wave radar, a joint correction method of ionospheric phase pollution based on adaptive optimal path is proposed in this paper. Firstly, the time‐frequency spectrum polluted by ionospheric phase is obtained by high resolution time‐frequency MUSIC transform, then the ionospheric phase disturbance curve in the time spectrum of polluted echo is extracted by the proposed adaptive optimal path method, and then the polluted echo is initially compensated to obtain the sharpened ocean echo spectrum. Finally, the residual phase of pollution curve is estimated by the Phase Gradient Autofocus method, and then the pollution echo is accurately corrected. The results of theoretical and measured data show that this method is effective in correcting the overlapping of positive and negative Bragg broadening peaks caused by serious ionospheric phase pollution. [ABSTRACT FROM AUTHOR]

The non‐stationary clutter phenomenon and the severe range ambiguity make space‐based early warning radar as an intricate model of received ground and sea clutter. The received clutter is severely broadened in Doppler dimension, and the degrees of freedom (DOFs) of the received clutter is severely increased. Because the DOFs of the system is always lower than the theoretical DOFs of the received clutter, the adaptive processing capability of the system is insufficient and the performance of clutter suppression is seriously degraded. A multi‐domain cascaded adaptive processing method is proposed in this study. The proposed method takes full advantage of the digital antenna array to suppress a portion of the clutter energy by introducing the transmit pulse coding domain, and the remaining influential clutter energy is suppressed by introducing the elevation‐dimensional receive channel domain. Finally, the clutter after the two‐dimensional (2D) pre‐processed is suppressed by the 2D adaptive processing in the azimuthal receive beam‐receive Doppler domain. This method pre‐processes the clutter data by extending the processing dimension to meet the freedom requirements of the adaptive signal processing, and the capability of clutter suppression is significantly improved. Simulation examples show the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

A method for time‐domain motion compensation of high frequency (HF) radar signals for the case of a floating transmitter and fixed receiver is proposed when the motion parameters (including the amplitude and angular frequency of the motion) are not known a priori. In this study, the floating platform is assumed to follow a single‐frequency motion model. Additionally, instead of trying to estimate platform motion parameters from the received motion‐contaminated Doppler spectrum, which is proportional to the observed radar cross‐section of the ocean surface from the floating platform, the motion parameters from the autocorrelation function of the received electric field are estimated, which is related to the received radar cross‐section by application of an inverse temporal Fourier transform. By comparing the locations of the zeros of the autocorrelation function for the fixed antenna case with that for an antenna on a floating platform and finding the zeros associated with the platform motion, the motion parameters are estimated. These parameters are matched with actual motion parameter values, from which the motion‐compensated Doppler spectrum is recovered from the Doppler spectrum of the antenna on a floating platform. [ABSTRACT FROM AUTHOR]

In order to improve the detection probability of weak targets, tracking radar using sum and difference beams often adopt the method of long‐time coherent integration. However, the multidimensional migration of time‐varying targets will lead to the decline of parameter estimation accuracy. To solve this problem, this article proposes a refined angle estimation method for time‐varying targets with the traditional sum and difference beam echo model, this method compensates and searches the angle parameters of the targets based on subarray rotation invariant and focus process. In addition, this article also studies the masking problem of highly dynamic proximity group targets detection, and proposes an adaptive weighted LMS‐CLEAN based on Least Mean Square criterion, which effectively reduces the influence of masking effect on the parameter estimation accuracy of weak targets. Firstly, the proposed algorithm performs angle search and phase compensation on the pulse compression echo of sum and difference channels based on subarray rotation invariant. Secondly, focus the search matrix, reconstruct the strong target echo, and stripe it from both channels by adaptive weighting. Lastly, repeat the above steps until parameters of all targets are achieved precisely. The proposed two algorithms maintain a very low computational effort while effectively reducing the parameter estimation error, and are highly promising for engineering applications. In order to verify the effectiveness of the proposed algorithm, this article also provides some numerical experiments to compares with two existing algorithms in error performance, anti‐noise performance, and computational complexity. [ABSTRACT FROM AUTHOR]

Using potentially best available rainfall data sets for the entire country of Japan (spatial scales of 1‐ and 20‐km), we analyze the 1–24 hr and city‐scale (1–400 km2) extreme rainfalls for both current (2006–2020) and future periods (2081–2109) at 1.5 K global warming scenario, complementing previous work that focuses on either coarse spatial and temporal scales or other warming scenarios (e.g., RCP and 2 K warming scenarios). A peak‐over‐threshold (POT)‐based approach is applied to compute areal reduction factor (ARF) for subsequently establishing intensity‐duration‐area‐frequency (IDAF) curves. Our results reveal that ARF values generally decrease with increasing area size and increase with longer duration and are affected by multiple underlying physical phenomena. Moreover, we find a greater increase in the rainfall intensities for shorter durations and higher return periods, ranging from 9.4% (1‐hr) to 6.2% (24‐hr), averaged for all return periods and 8.3% (25‐year) to 7.3% (2‐year), averaged for all rainfall durations. Spatially, extreme rainfall intensities are projected to increase by 8.9% in northern Japan (albeit with a less intense rainfall intensity in the current period), which is greater than the rest of the country (6.8%), underscoring the need to focus more on infrastructure designs in northern Japan. The projected IDAF curves further display an increase in the frequency of extreme events at city‐scale, for example, 25‐year extreme rainfall events in 2006–2020 would likely be 5‐10‐year events in 2081–2109. Our results with the state‐of‐the‐art data and implementable approach can be utilized for policymaking to reduce the warming‐induced risks in Japan and beyond. Key Points: For the first time, we analyze the city‐scale and sub‐daily extreme rainfall for the entire country of Japan by using high‐quality data setsAreal reduction factor values generally decrease with increasing area size and increase with longer duration and are affected by multiple physical phenomenaUnder 1.5 K warming, extreme rainfall will increase more for shorter durations and higher return periods, especially in northern Japan [ABSTRACT FROM AUTHOR]

From meteor radar observations typically measuring neutral winds and temperatures in the upper atmosphere, we showed that under‐dense meteor plasma trails respond to geomagnetic activity. Depending on the geomagnetic activity conditions, the parameters of the under‐dense trail echoes show substantial anomalies, and their responses are immediate. As geomagnetic activity increases, the decay time decreases up to about 10% at Kp = 8, while both the returned signal power and radial velocity error increase. In addition, the types of diffuse evolution vary with geomagnetic activity, resulting in strong geomagnetic activity that immediately affects the trail. The evolution of the trail is affected not only by the ambient mesospheric neutral atmospheric properties but also by electromagnetic effects, such as strong electric fields inside meteor trails. Furthermore, our findings suggest that the geomagnetic effect should be considered when estimating atmospheric parameters from MR during a geomagnetically active period. Plain Language Summary: Through long‐term meteor radar (MR) observation (2007–2021) at King Sejong Station in the Antarctic Peninsula, we found that the diffusion process in the meteor trail immediately accelerated under enhanced geomagnetic activity. The backscattered‐returned signal powers, which are proportional to the square of the electron line density of the meteor trail, also instantly increased. These anomalous characteristics in meteor trails appear while the background atmospheric parameters remain constant. Therefore, we propose that the observed immediate responses in the MR may be associated with the strong electric field in the ambient ionosphere D/E region induced by the increased geomagnetic activity. The strong external electric field can stimulate an electric field and current inside the meteor trail, owing to the difference in electrical conductivities between the meteor trail and ambient atmosphere. Thus, the electric field, current, and charge separation inside the meteor trail can lead to faster diffusion and enhanced electron line density in the trail. The meteor plasma trails are observed in regions that are affected by electric fields caused by geomagnetic activity; therefore, when deriving neutral atmospheric parameters from MRs, the impact of geomagnetic activity must be considered. Key Points: Under‐dense meteor echo parameters at a geomagnetic latitude of 50.2°S revealed an instantaneous response to geomagnetic activityGeomagnetic activity can directly modulate the evolution of meteor trails, such as the decay time and returned signal powerEffects of geomagnetic activity should be considered when estimating neutral atmospheric parameters from meteor radars [ABSTRACT FROM AUTHOR]

Climate and numerical weather prediction models require assumptions to represent the vertical distribution of subgrid‐scale clouds, which have radiative transfer implications. In this study, nearly 25 years of ground‐based radar and lidar observations of vertical cloud profiles at the Atmospheric Radiation Measurement Program (ARM) Southern Great Plains (SGP) site are utilized to derive cloud vertical overlap characteristics from the Cloud Type (CLDTYPE) data product. The cloud vertical overlap characteristics are further separated by cloud regime by considering seven cloud types (i.e., low cloud, congestus, deep convection, altocumulus, altostratus, cirrostratus, and cirrus) as well as periods of shallow cumulus. The decorrelation length scale (i.e., exponential transition from maximum to random overlap with layer separation) is found to vary by cloud regime, ranging between 0.04 km for cirrostratus paired with cirrus to 4.58 km for low cloud paired with cirrus at SGP. Cloud vertical overlap characteristics are also considered for other ARM sites including the Tropical Western Pacific (TWP), North Slope of Alaska (NSA), and Eastern North Atlantic (ENA) sites among other shorter term ARM deployments globally. The decorrelation length scale ranged globally from 1.03 km in the Arctic Ocean to 3.06 km in Manacapuru, Brazil. Globally, the decorrelation length scale by cloud regime exhibited similarities (e.g., for cirrus paired with cirrus) and differences (e.g., congestus paired with cirrus). The results could help inform development of cloud vertical overlap assumptions within operational numerical weather prediction models and potentially improve prediction of radiative fluxes for weather, climate, and renewable energy forecasting. Plain Language Summary: The complexity of cloud vertical structure requires approximations in weather and climate models, which has implication for the forecast of how much sunlight reaches the surface. Cloud observations from radars and lidars help to inform how cloud layers overlap vertically. The cloud observations ultimately inform what model assumptions best capture the observed cloud vertical structure. In this study, cloud profiles from ground‐based radars and lidars are considered to calculate cloud vertical overlap characteristics at 18 long‐term and short‐term sites across the globe. The cloud vertical overlap characteristics are also considered by cloud types to understand if cloud type provides additional information on the model assumptions to use. The cloud vertical overlap characteristics are found to vary by site, season, and cloud type. The results could help inform development of cloud vertical overlap assumptions within weather and climate models and potentially improve prediction of sunlight reaching the surface, which has implications for weather, climate, and renewable energy forecasting. Key Points: Decorrelation length scales varied by cloud regime at the Atmospheric Radiation Measurement Program Southern Great Plains site between 0.04 and 4.58 kmDecorrelation length scales varied by site with values ranging from near 1 km in the Arctic to near 3 km in BrazilDecorrelation length scales for the same cloud regime across the sites were similar, although some cloud regimes exhibited differences [ABSTRACT FROM AUTHOR]

We conducted two 10‐day observational campaigns in 2019 targeting turbulence in the troposphere and lower stratosphere by adopting a frequency domain radar interferometric imaging technique using Program of the Antarctic Syowa radar (PANSY radar) and radiosonde observations obtained at Syowa Station in the Antarctic. Seventy three Kelvin‐Helmholtz (K‐H) billows were detected, and two characteristic cases likely excited by the same cyclone were examined in detail. In the first case with the longest observational duration of ∼6.5 hr, the K‐H billows had a thickness of ∼800 m and a horizontal wavelength of ∼2,500 m. According to a numerical simulation, continuously existing gravity waves associated with the cyclone maintained strong vertical wind shear sufficient to cause the K‐H instability. In the second case with the deepest thickness of ∼1,600 m, the K‐H billows had a horizontal wavelength of ∼4,320 m. Numerical simulation suggested that an enhanced upper‐tropospheric jet associated with a well‐developed synoptic‐scale cyclone caused the K‐H instability. Such background conditions, frequently observed in the Antarctic coastal region, are typical mechanisms for K‐H excitation. Linear stability analysis also indicated that the characteristics of the observed K‐H billows were consistent with the most unstable modes. Furthermore, statistical analysis was performed using data of all 73 observed cases. The characteristics of K‐H billows observed at Syowa Station are similar to those observed over Japan. However, the K‐H billows tend to have longer wave periods over Syowa Station than over Japan, likely due to the weaker tropospheric jet in the Antarctic. Plain Language Summary: Two 10‐day observational campaigns were conducted in 2019 for tropospheric and lower stratospheric turbulence with the Program of the Antarctic Syowa radar (PANSY radar) and radiosondes at Syowa Station in the Antarctic. Seventy three Kelvin‐Helmholtz (K‐H) billows were detected and two distinct cases were studied in detail by numerical simulations: the first case has the longest observational duration of the 73 cases and was most likely caused by instability due to continuous gravity waves associated with a cyclone that imparts strong vertical wind shear. The second case is the deepest and is most likely caused by instability due to a strong upper‐tropospheric jet associated with a well‐developed synoptic‐scale cyclone. Such background conditions are frequently observed in the Antarctic coastal region, suggesting typical mechanisms for K‐H excitation in this region. Theoretical calculations also show that the observed K‐H billow characteristics were consistent with the most unstable mode. Furthermore, statistical analysis using the 73 observed cases indicates that the characteristics of K‐H billows observed at Syowa Station are similar to those over Japan except for the long wave periods, which may be due to the weaker tropospheric jet in the Antarctic. Key Points: Seventy‐three Kelvin‐Helmholtz (K‐H) billows were detected in Program of the Antarctic Syowa radar observations using a frequency radar interferometric imaging techniqueGravity waves and well‐developed cyclones unique to the Antarctic coastal region cause strong vertical shearK‐H billows in the coastal Antarctic region have comparable spatial scale and strength to those in the mid‐latitudes [ABSTRACT FROM AUTHOR]

Finally, the convective windstorm identification process was determined when two adjacent stations near the convective system had a maximum wind gust reaching gale force. Based on the radar data of these convective -windstorm cases, convective cell recognition was conducted.[1] These studies will provide a reference for the automatic identification and early prediction of convective windstorms. (b) Monthly convective gale gust distribution in Hubei Province from 2010 to 2016. gl Sources and movement paths of convective windstorms Using the SWAN reflectivity mosaic product of the convective windstorms identification process, we noted 212 convective systems, whose sources and directions were clearly identifiable. [Extracted from the article]