Search

Tornadoes, as highly destructive weather events, require accurate detection for effective decision‐making. Traditional radar‐based tornado detection algorithms (TDA) face challenges with limited tornado feature extraction capabilities, leading to high false alarm rates and low detection probabilities. This study introduces the Multi‐Task Identification Network (MTI‐Net), leveraging Doppler radar data to enhance tornado recognition. MTI‐Net integrates tornado detection and estimation tasks to acquire comprehensive spatial and locational information. As part of MTI‐Net, we introduce a novel backbone network of Multi‐Head Convolutional Block (MHCB), which incorporates Spatial and Channel Attention Units (SAU and CAU). SAU optimizes local tornado feature extraction, while CAU reduces false alarms by enhancing dependencies among input variables. Experiments demonstrate the superiority of MTI‐Net over TDA, with a decrease in false alarm rates from 0.94 to 0.46 and an increase in hit rates from 0.23 to 0.81, highlighting the effectiveness of MTI‐Net in handling small‐scale tornado events. Plain Language Summary: Tornadoes, highly destructive small‐scale weather phenomena, demand accurate detection for informed decision‐making. Although meteorological radars are commonly utilized for tornado identification, current methods often suffer from false alarms or missed detections due to radar noise. In this study, we introduce the multi‐task learning‐based identification network (MTI‐Net), which not only enables tornado detection but also estimates tornado counts within radar data. We integrate Convolutional Neural Networks (CNNs) with Transformer techniques to enhance the model's ability to capture tornado information. CNNs detect local details using filters, while Transformers manage global connections through attention mechanisms. A series of experiments demonstrate significant improvements in tornado detection with MTI‐Net compared to traditional methods. Key Points: A tornado dataset with detailed radar features was created over China from 2017 to 2023Multi‐task learning was designed to simultaneously infer tornado detection and tornado number estimationIntegration of spatial and channel attention units can better extract tornado features from radar data [ABSTRACT FROM AUTHOR]

Quantitative precipitation estimation (QPE) by radar observation data is a crucial aspect of meteorological forecasting operations. Accurate QPE plays a significant role in mitigating the impact of severe convective weather. Traditional QPE methods mainly employ an exponential Z–R relationship to map the radar reflectivity to precipitation intensity on a point-to-point basis. However, this isolated point-to-point transformation lacks an effective representation of convective systems. Deep learning-based methods can learn the evolution patterns of convective systems from rich historical data. However, current models often rely on 2 km-height CAPPI images, which struggle to capture the complex vertical motions within convective systems. To address this, we propose a novel QPE model: combining the classic extrapolation model ConvLSTM with Unet for an encoder-decoder module assembly. Meanwhile, we utilize three-dimensional radar echo images as inputs and introduce the convolutional block attention module (CBAM) to guide the model to focus on individual cells most likely to trigger intense precipitation, which is symmetrically built on both channel and spatial attention modules. We also employ asymmetry in training using weighted mean squared error to make the model concentrate more on heavy precipitation events which are prone to severe disasters. We conduct experiments using radar data from North China and Eastern China. For precipitation above 1 mm, the proposed model achieves 0.6769 and 0.7910 for CSI and HSS, respectively. The results indicate that compared to other methods, our model significantly enhances precipitation prediction accuracy, with a more pronounced improvement in forecasting accuracy for heavy precipitation events. [ABSTRACT FROM AUTHOR]

In the development of meteorological detection technology and services, weather radar undoubtedly plays a pivotal role, especially in the monitoring and early warning of severe convective weather events, where it serves an irreplaceable function. This research delves into the landscape of weather radar research from 1945 to 2024, employing scientometric methods to investigate 13,981 publications from the Web of Science (WoS) core collection database. This study aims to unravel, for the first time, the foundational structures shaping the knowledge domain of weather radar over an 80-year period, exploring general features, collaboration, co-citation, and keyword co-occurrence. Key findings reveal a significant surge in both publications and citations post-1990, peaking in 2022 with 1083 publications and 13832 citations, signaling sustained growth and interest in the field after a period of stagnation. The United States, China, and European countries emerge as key drivers of weather radar research, with robust international collaboration playing a pivotal role in the field's rapid evolution. Analysis uncovers 30 distinct co-citation clusters, showcasing the progression of weather radar knowledge structures. Notably, deep learning emerges as a dynamic cluster, garnering attention and yielding substantial outcomes in contemporary research efforts. Over eight decades, the focus of weather radar investigations has transitioned from hardware and software enhancements to Artificial Intelligence (AI) technology integration and multifunctional applications across diverse scenarios. This study identifies four key areas for future research: leveraging AI technology, advancing all-weather observation techniques, enhancing system refinement, and fostering networked collaborative observation technologies. This research endeavors to support academics by offering an in-depth comprehension of the progression of weather radar research. The findings can be a valuable resource for scholars in efficiently locating pertinent publications and journals. Furthermore, policymakers can rely on the insights gleaned from this study as a well-organized reference point. [ABSTRACT FROM AUTHOR]

Deformation along a subway rail network is related to the safe operation of the subway and the stability of construction facilities on the surface, making long-term deformation monitoring imperative. Long-term monitoring of surface deformation along the subway network and statistical analysis of the overall deformation situation are lacking in China. Therefore, targeting 35 Chinese cities whose subway mileage exceeds 50 km, we extracted their surface deformation along subway networks between 2018 and 2022, using spaceborne synthetic aperture radar (SAR) interferometry (InSAR) technology and Sentinel-1 satellite data. We verified the results with the continuous global navigation satellite system (GNSS) stations' data and found that the root mean square error (RMSE) of the InSAR results was 3.75 mm/year. Statistical analysis showed that ground subsidence along the subways was more prominent in Beijing, Tianjin, and other areas in the North China Plain, namely Kunming (which is dominated by karst landforms), as well as Shanghai, Guangzhou, Qingdao, and other coastal cities. In addition, an analysis revealed that the severity of surface subsidence correlated positively with a city's gross domestic product (GDP) with a Pearson correlation of 0.787, since the higher the GDP, the more frequent the construction and maintenance of subway, and the more commuters there are, which in turn exacerbates the disturbance to the surface. Additionally, the type of land cover also affects the ground deformation. Our findings provide a reference for constructing, operating, and maintaining the urban subway systems in China. [ABSTRACT FROM AUTHOR]

To evaluate the impact of different momentum control variable (CV) schemes (CV5, the momentum control variable option with ψχ and CV7, the momentum control variable option with UV) on radar data assimilation (DA) in weather research and forecasting model data-assimilation (WRFDA) systems, a heavy snowfall in central and eastern regions of China, which started on 6 February 2022, was taken as a case in this study. The results of the wind-field increments from the single observation tests indicated that the wind-field increments had a larger range of influence when stream function and velocity potential (ψχ) were used as momentum control variables in CV5. Some spurious increments were also generated in the wind-field analysis, since CV5 tended to maintain the integrated value of the wind field. When U-wind and V-wind were used as control variables in CV7, the wind-field increments had a smaller impact range, and there was less dependence among different locations on the wind increments. For the heavy snow case, the CV7 schemes displayed some improvements in simulating the composite reflectivity compared to the other two experiments, since the composite reflectivity in the CV5 and control experiments were overestimated to some level. It was also found that the RMSEs were lower in the CV7 compared to those in the CV5 in the short-term forecasts during the data-assimilation cycles. Results also indicated that the CV7 had a more significant effect on the 6 h accumulated precipitation forecasts. Meanwhile, the experiment Exp_CV7 achieved the best ETS and FSS scores among the three groups of experiments, while Exp_CV5 appeared to be generally superior to the CTRL. In summary, the precipitation of Exp_CV7 yielded the rainfall intensity and location most close to the observation compared to those from both the CTRL and Exp_CV5 experiments. [ABSTRACT FROM AUTHOR]

The accurate prediction of landslide susceptibility relies on effectively handling landslide absence samples in machine learning (ML) models. However, existing research tends to generate these samples in feature space, posing challenges in field validation, or using physics-informed models, thereby limiting their applicability. The rapid progress of interferometric synthetic aperture radar (InSAR) technology may bridge this gap by offering satellite images with extensive area coverage and precise surface deformation measurements at millimeter scales. Here, we propose an InSAR-based sampling strategy to generate absence samples for landslide susceptibility mapping in the Badong–Zigui area near the Three Gorges Reservoir, China. We achieve this by employing a Small Baseline Subset (SBAS) InSAR to generate the annual average ground deformation. Subsequently, we select absence samples from slopes with very slow deformation. Logistic regression, support vector machine, and random forest models demonstrate improvement when using InSAR-based absence samples, indicating enhanced accuracy in reflecting non-landslide conditions. Furthermore, we compare different integration methods to integrate InSAR into ML models, including absence sampling, joint training, overlay weights, and their combination, finding that utilizing all three methods simultaneously optimally improves landslide susceptibility models. [ABSTRACT FROM AUTHOR]

Characterizing the coseismic slip behaviors of earthquakes could offer a better understanding of regional crustal deformation and future seismic potential assessments. On 18 December 2023, an Mw 6.0 earthquake occurred on the Lajishan–Jishishan fault system (LJFS) in the northeastern Tibetan Plateau, causing serious damage and casualties. The seismogenic fault hosting this earthquake is not well constrained, as no surface rupture was identified in the field. To address this issue, in this study, we use Interferometric Synthetic Aperture Radar (InSAR) data to investigate the coseismic surface deformation of this earthquake and invert both ascending and descending line-of-sight observations to probe the seismogenic fault and its slip characteristics. The InSAR observations show up to ~6 cm surface uplift caused by the Jishishan earthquake, which is consistent with the thrust-dominated focal mechanism. A Bayesian-based dislocation modeling indicates that two fault models, with eastern and western dip orientations, could reasonably fit the InSAR observations. By calculating the coseismic Coulomb failure stress changes (∆CFS) induced by both fault models, we find that the east-dipping fault scenario could reasonably explain the aftershock distributions under the framework of stress triggering, while the west-dipping fault scenario produced a negative ∆CFS in the region of dense aftershocks. Integrating regional geological structures, we suggest that the seismogenic fault of the Jishishan earthquake, which strikes NNE with a dip of 56° to the east, may be either the Jishishan western margin fault or a secondary buried branch. The optimal finite-fault slip modeling shows that the coseismic slip was dominated by reverse slip and confined to a depth range between ~5 and 15 km. The released seismic moment is 1.61 × 1018 N·m, which is equivalent to an Mw 6.07 earthquake. While the Jishishan earthquake ruptured a fault segment of approximately 20 km, it only released a small part of the seismic moment that was accumulated along the 220 km long Lajishan–Jishishan fault system. The remaining segments of the Lajishan–Jishishan fault system still have the capability to generate moderate-to-large earthquakes in the future. [ABSTRACT FROM AUTHOR]

A trend in the development of spaceborne Synthetic Aperture Radar (SAR) technology is the shift from a single-satellite repeated observation mode to a multi-satellite collaborative observation mode. However, current multi-satellite collaborative geolocation algorithms face challenges, such as geometric model mismatch and poor baseline estimation accuracy, arising from highly dynamic changes among multi-satellites. This paper introduces a high-precision and efficient geolocation algorithm for a spaceborne bistatic interferometric SAR (BiInSAR) system based on an improved range–Doppler (IRD) model. The proposed algorithm encompasses three key contributions. Firstly, a comprehensive description of the spatial baseline geometric model unique to the bistatic configuration is provided, with a specific focus on deriving the perpendicular baseline expression. Secondly, IRD geolocation functions are established to meet the specific requirements of the bistatic configuration. Then, a novel BiInSAR geolocation algorithm based on the IRD's functions is proposed, which can significantly improve the target geolocation accuracy by modifying the range–Doppler equation to suit the bistatic configuration. Meanwhile, a low-coupling parallel calculation method is proposed, which can improve the calculation speed by two to three times. Finally, the accuracy and efficiency of the algorithm are demonstrated using experimental data acquired by the TH-2 satellite, which is China's first spaceborne BiInSAR system. The experimental results prove that the IRD algorithm exhibits geolocation accuracy with an average error of less than 1 m and a standard deviation of less than 2.5 m while maintaining computational efficiency at a calculation speed of 1,429,678 pixels per second. [ABSTRACT FROM AUTHOR]

Dual-polarization radar data are useful for numerical models to improve precipitation forecasts. For an extremely heavy precipitation event that occurred in Central China on 11 August 2021, the hydrometeor concentration and water vapor content used in the initial field of the Weather Research and Forecasting (version 4.1) model are retrieved by the statistical relationship of relative humidity with dual-polarization radar reflectivity in Suizhou City of Central China. Three experiments are conducted, and the simulation results are compared after assimilating the radar data. The results indicate that the multiple factors contributing to this extreme heavy precipitation event included the divergence of upper-level airflows, the middle- and low-level low vortex/shear, the easterly jet stream in front of the low vortex, and the continuous intrusion of cold air on the ground. In addition, with the retrieval of the hydrometeor concentration and water vapor content, the composite reflectivity forecast results are more similar to the observations. Also, the location and intensity of the short-term extremely heavy precipitation event are less different from the observations. In addition, by cyclically adjusting the hydrometeor concentration and water vapor content in the initial field, we can obtain better forecasts of the reflectivity and short-term extremely heavy precipitation, and this improvement can be maintained for approximately 3 h. [ABSTRACT FROM AUTHOR]

The proposed "Guanlan" ocean science satellite, led by China's Laoshan Laboratory, includes an interferometric radar altimeter (IRA) as a key payload. As an integral part of its development, an airborne IRA experiment was conducted on 6 November 2021, with a flight path of approximately 90 km in the South China Sea. This study investigates the IRA's ability to observe ocean sea surface height (SSH) across scales ranging from meters to mesoscale. The sea surface height anomaly (SSHA) of the IRA is aligned with the SSHA of the AVISO at scales greater than 30 km, but also demonstrates the ability to capture small-scale SSHA changes in two dimensions. We analyzed wavenumber spectra of SSHA obtained from the airborne IRA, ICESat-2, and SARAL/AltiKa satellite for this region. The results show a good agreement in power spectral density (PSD) levels between ICESat-2, SARAL/AltiKa and IRA at scales larger than 30 km. Within the submesoscale range of 1–10 km, the IRA SSHA spectrum exhibits a distinctly negative slope and the lowest energy level. The minimum PSD level of the IRA fell in the range of 10−4–10−3 m2/cycle/km, at scales around 1 km, which is more than an order of magnitude lower than that of ICESat-2, forming a spectral gap that is in agreement with the theoretical expectation. Furthermore, IRA-derived wave direction and significant wave height matched well with the MFWAM wave data. The results of this study underscore the considerable potential of airborne IRA in capturing SSHA across a range of scales, from oceanic waves to submesoscale. [ABSTRACT FROM AUTHOR]

Identification of slope subsurface strata for natural soil slopes is essential to assess the stability of potential landslides. The highly variable strata in a slope are hard to characterize by traditional boreholes at limited locations. Ground-penetrating radar (GPR) is a non-destructive method that is capable of capturing continuous subsurface information. However, the accuracy of subsurface identification using GPRs is still an open issue. This work systematically investigates the capability of the GPR technique to identify different strata via both laboratory experiments and on-site examination. Six large-scale models were constructed with various stratigraphic interfaces (i.e., sand–rock, clay–rock, clay–sand, interbedded clay, water table, and V–shaped sand–rock). The continuous interfaces of the strata in these models were obtained using a GPR, and the depths at different points of the interfaces were interpreted. The interpreted depths along the interface were compared with the measured values to quantify the interpretation accuracy. Results show that the depths of interfaces should be interpreted with the relative permittivity, back-calculated using on-site borehole information instead of empirical values. The relative errors of the depth of horizontal interfaces of different strata range within ±5%. The relative and absolute errors of the V–shaped sand–rock interface depths are in the ranges of [−9.9%, 10.5%] and [−107, 119] mm, respectively. Finally, the GPR technique was used in the field to identify the strata of a slope from Tanglang Mountain in China. The continuous profile of the subsurface strata was successfully identified with a relative error within ±5%. [ABSTRACT FROM AUTHOR]

The potential increases in carbon stocks in arid regions due to recent shrub encroachment have attracted extensive interest among both ecologists and carbon policy analysts. Quantifying the shrub root biomass amount in these ecosystems is essential to understanding the ecological changes occurring. In this paper, we proposed a simple nondestructive method for estimating the coarse lateral root biomass of shrubs based on the root counts obtained from ground-penetrating radar (GPR) radargrams. Root data were gathered via field experiments using GPR with antenna center frequencies of 900 MHz and 400 MHz. Five Caragana microphylla Lam. shrubs of different sizes were selected for measuring objects, and a total of 40 GPR survey lines were established for GPR data acquisition. The soil profile wall excavation method was used to obtain the total root biomass from each radargram. A model for estimating the root biomass was built by establishing the relationship between the root biomass in each profile and the root counts interpreted from the radargrams. According to the mathematical relationship between the root diameter and root biomass, the proxy root radius was derived, which could explain the rationality of the proposed model from the biological mechanism. The established model provided high confidence in estimating the root dry biomass using the GPR data obtained at the two antenna frequencies (R 2 = 0.73 for 900 MHz and R 2 = 0.71 for 400 MHz). The leave-one-out cross-validation results showed that the model exhibits satisfactory performance. This study expands the application of geophysical methods in root research and offers a new simplified method for estimating the root biomass from GPR data under field conditions., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

China has successfully carried out five lunar exploration missions since 2007. These missions indicate that China has successfully implemented a three-step lunar exploration program of "orbiting, landing, and returning". Among them, the Lunar Penetrating Radar (LPR) carried by the Yutu-2 rover in the Chang'E-4 (CE-4) mission is the only one still operating on the far side of the Moon. Up to now, the Yutu-2 radar has measured a large amount of scientific data, and its observations are of great significance to human cognition of the geological evolution of the lunar surface and the exploration of possible lunar in situ resources. This paper reviews the scientific results obtained by previous researchers based on the radar exploration data of Yutu-2, focusing mainly on three aspects, e.g., the geological structure of the shallow surface at the CE-4 landing site, the dielectric properties of the shallow subsurface materials and the special geological features. Finally, the prospects of Yutu-2 radar research priorities and future exploration, and the application trend of Moon-based ground-penetrating radar are given. [ABSTRACT FROM AUTHOR]

A new dual-frequency stratospheric–tropospheric (ST) and meteor radar has been built and installed at the Langfang Observatory in northern China. It utilizes a new two-frequency system design that allows interleaved operation at 53.8 MHz for ST mode and at 35.0 MHz for meteor mode, thus optimizing performance for both ST wind retrieval and meteor trail detection. In dedicated meteor mode, the daily meteor count rate reaches over 40 000 and allows wind estimation at finer time resolutions than the 1 h typical of most meteor radars. The root mean square uncertainty of the ST wind measurements is better than 2 m s -1 when estimating the line of best fit with radiosonde winds. Preliminary observation results for 1 month of winter gravity wave (GW) momentum fluxes in the mesosphere, lower stratosphere and troposphere are also presented. A case of waves generated by the passage of a cold front is found. [ABSTRACT FROM AUTHOR]

In order to achieve a rapid and accurate identification of soil stratification information and accelerate the development of smart agriculture, this paper conducted soil stratification experiments on agricultural soils in the Mollisols area of Northeast China using Ground Penetrating Radar (GPR) and obtained different types of soil with frequencies of 500 MHz, 250 MHz, and 100 MHz antennas. The soil profile data were obtained for 500 MHz, 250 MHz, and 100 MHz antennas, and the dielectric properties of each type of soil were analyzed. In the image processing procedure, wavelet analysis was first used to decompose the pre-processed radar signal and reconstruct the high-frequency information to obtain the reconstructed signal containing the stratification information. Secondly, the reconstructed signal is taken as an envelope to enhance the stratification information. The Hilbert transform is applied to the envelope signal to find the time-domain variation of the instantaneous frequency and determine the time-domain location of the stratification. Finally, the dielectric constant of each soil horizon is used to obtain the propagation velocity of the electromagnetic wave at the corresponding position to obtain the stratification position of each soil horizon. The research results show that the 500 MHz radar antenna can accurately delineate Ap/Ah, horizon and the absolute accuracy of the stratification is within 5 cm. The effect on the soil stratification below the tillage horizon is not apparent, and the absolute accuracy of the 250 MHz and 100 MHz radar antennas on the stratification is within 9 cm. The overwhelming majority of the overall calculation errors are kept to within 15%. Based on the three central frequency antennas, the soil horizon detection rate reaches 93.3%, which can achieve accurate stratification of soil profiles within 1 m. The experimental and image processing methods used are practical and feasible; however, the GPR will show a missed detection for soil horizons with only slight differences in dielectric properties. Overall, this study can quickly and accurately determine the information of each soil stratification, ultimately providing technical support for acquiring soil configuration information and developing smart agriculture. [ABSTRACT FROM AUTHOR]

Background: A consensus exists that the first author and corresponding author make the most contribution to the publication of an article. The Y-index has been proposed to assess the scientific achievements of authors, institutions, and countries/regions (AIC/R for short) based on the number of first-author publications (FPs) and corresponding-author publications (RPs). Nonetheless, the Y-index is defined in terms of count and radian (represented by j and h) instead of using the relative radius and angle degree to simplify understanding. In the literature, a method for drawing radar diagrams online with the Y-index is also lacking. This study was conducted to enhance the Y-index with an additional relative radius denoted by k and the angle degree represented by h* (named Yk-index), include easy-to-use features (e.g., copying and pasting) for the delivery of the online Radar-Yk, and identify which one of AIC/R contributed the most to a scientific journal., Methods: From the Web of Science (WoS) database, we downloaded 9498 abstracts of articles published in the journal of Medicine (Baltimore) in 2020 and 2021. Three visual representations were used, including a Sankey diagram, a choropleth map, and a radar diagram, to identify the characteristics of contributions by AIC/R to Medicine (Baltimore) using the Yk-index (j, k, h*). A demonstration of Rada-Yk with easy-to-use features was given using the copy-and-paste technique., Results: We found that Qiu Chen (China), Sichuan University (China), China, and South Korea (based on regions, e.g., provinces/metropolitan areas in China) were the most productive AIC/R, with their Yk equal to 27,715, 12415.1, and 2045, respectively; a total of 85.6% of the published articles in Medicine (Baltimore) came from the 3 countries (China, South Korea, and Japan); and this method of drawing the Radar-Yk online was provided and successfully demonstrated., Conclusion: A breakthrough was achieved by developing the online Radar-Yk to show the most contributions to Medicine (Baltimore). Visualization of Radar-Yk could be replicated for future academic research and applications on other topics in future bibliographical studies., Competing Interests: The authors have no funding and conflicts of interest to disclose., (Copyright © 2022 the Author(s). Published by Wolters Kluwer Health, Inc.)

This paper comprehensively analyzed two consecutive tornado events associated with heavy precipitation during the Mei-yu season (a period of continuous rainy weather that occurs in the middle and lower reaches of the Yangtze River in China from mid-June to mid-July each year) and detailed the formation and development process of the tornadoes using Doppler weather radar, wind profiler radar, ERA5 reanalysis data, ground automatic station data and other multi-source data. The results showed that: (1) Small-scale vortices were triggered and developed during the eastward movement of the low vortex, forming two tornadoes successively on the eastern section of the Mei-yu front. (2) The presence of a gap on the front side of the reflectivity factor profile indicated that strong incoming airflow entered the updraft. Mesocyclones were detected with decreasing heights and increasing shear strengths. The bottom height of the tornado vortex signature (TVS) dropped to 0.7 km, and the shear value increased to 55.4 × 10−3 s−1. Tornado debris signatures (TDSs) could be seen with a low cross-correlation coefficient (CC) value area of 0.85–0.9 in the mesocyclone. The difference between the lowest-level difference velocity (LLDV) and the maximum difference velocity (MXDV) reached the largest value when a tornado occurred. (3) The continuously enhanced low-level jet propagated downward to form a super-low-level jet, and the strong wind direction and wind speed convergence in the boundary layer created a warm, moist and unstable atmosphere in Suzhou. With the entrainment of dry air, the northwest dry jet and the southeast moist jet stimulated the formation of a miniature supercell. (4) The low-level vertical wind shear of 0–1 km increased significantly upon tornado occurrence, which was more conducive to the formation and intensification of horizontal vorticity tubes. Encountering updrafts and downdrafts, the vorticity tubes might have been stretched and intensified. The first lightning jumps appeared 15 min and 66 min earlier than the Kunshan Bacheng tornado and the Taicang Liuhe tornado. The Liuhe tornado occurred during the stage when the lightning frequency reached its peak and then fell back. [ABSTRACT FROM AUTHOR]

X-band dual-polarization phased-array weather radars (X-PARs) have been used in South China extensively. Eliminating the attenuation and system bias of X-band radar data is the key to utilizing the advantage of X-PAR networks. In this paper, the disdrometer raindrop-size distribution (DSD) measurements are used to calculate the radar polarimetric variables and analyze the characteristics of precipitation attenuation. Furthermore, based on the network of S-band dual-polarization Doppler weather radar (S-POL) and X-PARs, an attenuation-correction method for X-PAR reflectivity is proposed with S-POL constraints in view of the radar-mosaic requirements of a multi-radar network. Linear programming is used to calculate the attenuation-correction parameters of different rainfall areas, which realizes the attenuation correction for X-PAR. The results show that the attenuation-correction parameters simulated based on the disdrometer DSD vary with different precipitation classification; the attenuation-corrected reflectivity of X-PARs is consistent with S-POL and can realize a more precise observation of the evolution of the convective system. Compared with previous attenuation-correction methods with constant correction parameters, the improved method can reduce the deviation between X-PAR reflectivity and that of S-POL in heavy rainfall areas and areas of strong attenuation. The method proposed in this paper is stable and effective. After effective quality control, it is found that the X-PAR network deployed in South China observes data accurately and is consistent with S-POL; thus, it is expected to achieve high temporal–spatial resolution within a radar mosaic. [ABSTRACT FROM AUTHOR]

In order to improve the understanding of the microphysical characteristics of raindrop size distribution (DSD) under different rainfall rates (R) classes, and broaden the knowledge of the impact of radar wavelengths and R classes on the QPE of dual-polarization radars in the Tianshan Mountains, a typical arid area in China, we investigated the microphysical characteristics of DSD across R classes and dual-polarimetric radar QPE relationships across radar wavelengths and R classes, based on the DSD data from a PARSIVEL2 disdrometer at Zhaosu in the Tianshan Mountains during the summers of 2020 and 2021. As the R class increased, the DSD became wider and flatter. The mean value of the mass-weighted mean diameters (Dm) increased, while the mean value of logarithm normalized intercept parameters (log10 Nw) decreased after increasing from C1 to C3, as the R class increased. The largest contributions to R and the radar reflectivity factor from large raindrops (diameter > 3 mm) accounted for approximately 50% and 97%, respectively, while 84% of the total raindrops were small raindrops (diameter < 1 mm). Dual-polarization radars—horizontal polarization reflectivity (Zh), differential reflectivity (Zdr), and specific differential phase (Kdp)—were retrieved based on the DSD data using the T-matrix scattering method. The DSD-based polarimetric radar QPE relations of a single-parameter (R(Zh), R(Kdp)), and double-parameters (R(Zh,Zdr), R(Kdp,Zdr)) on the S-, C-, and X-bands were derived and evaluated. Overall, the performance of the R(Kdp) (R(Kdp,Zdr)) scheme was better than that of R(Zh) (R(Zh,Zdr)) for the QPE in the three bands. Furthermore, we have for the first time confirmed and quantified the performance differences in the QPE relationship of dual-polarization radars under different schemes, radar wavelengths, and R classes in typical arid areas of China. Therefore, selecting an appropriate dual-polarization radar band and QPE scheme for different R classes is necessary to improve the QPE ability compared with an independent scheme under all R classes. [ABSTRACT FROM AUTHOR]

The geometric and polarimetric characteristics of the melting layer (ML) during the pre-summer rainy season over South China (PRSC) are investigated from 389 S-band polarimetric radar volume scans. The existing ML detection algorithm is slightly improved, in which the ML is automatically detected by using vertical gradients of radar reflectivity factor for horizontal polarizations (ZH), and co-polar cross-correlation coefficient (ρHV) from quasi-vertical profiles. And these profiles are obtained by azimuthal averaging of polarimetric radar variables at antenna elevation 19.5°. The comparison between the detected ML top and the 0°C isotherm heights from ERA5 demonstrates that the detection algorithm has high accuracy with an offset of 158 m. Due to larger snowflakes, the average ML thickness in PRSC is thicker (i.e. 150 m) than that in other climatic regions. The ML is characterized by large ZH, large differential reflectivity (ZDR) and small ρHV, with average values of 32 dBZ, 0.91 dB and 0.94. Furthermore, the peak values of ZH and ZDR in the ML are obviously larger than that from rain regions and snow regions, while the opposite is true for ρHV distribution. [ABSTRACT FROM AUTHOR]

In order to alleviate the conflict between populations and land resource, Tianjin adopted multi-phase reclamation projects to the formed large-scale artificial reclamation land. The reclamation areas, however, are prone to subsidence, which poses a significant threat to infrastructure as well as the safety and assets of the residents. The SBAS-InSAR was used to acquire surface deformation of Tianjin Binhai New Area from January 2017 to December 2022, analyze in depth the response relationship between land subsidence, reclamation project time, and land-use type. There is a strong correlation between surface deformation and reclamation time. Severe land subsidence occurred over newly reclaimed areas. In the offshore direction, the deformation values of the Nangang Industrial Zone, the Lingang Industrial Zone, and Hangu Harbor were −98 mm to −890 mm, 45 mm to −580 mm, and −140 mm to −290 mm, respectively. Significant differences in deformation were detected among different land-use types where reclamation projects were completed in the same time. Subsidence was positively correlated with surface load; in areas with higher surface loads, the surface settlement was also more severe. The average surface settlement for the heavy shipyard, with 67 grain storage tanks and 27 grain storage tanks, road, and bare land were −201 mm, −166 mm, −107 mm, −64 mm, and −43 mm, respectively. This study reveals significant differences of surface deformation in the reclamation completed at different times, and determines that the load is the main driving factor of settlement difference in the reclamation land completed at the same time. This has important guiding significance for preventing and controlling geological disasters in the reclamation area and later development planning. [ABSTRACT FROM AUTHOR]

In this study, we investigate the seasonal and diurnal variations in cloud occurrence frequency, as well as cloud vertical structure (CVS) characteristics under different seasons and precipitation intensities over the Guangzhou region in South China, based on the analysis of millimeter-wave cloud radar (MMCR) and ground automatic weather station rainfall observations from May 2019 to August 2021. The results showed that the occurrence frequency of clouds exhibits a bimodal distribution throughout the year, with peaks in March to June and October, reaching its highest occurrence in May at approximately 80% and its lowest from December to February at around 40%. Additionally, there are distinct diurnal variations in occurrence frequency, with the lowest rates occurring around 0005 LST, rapidly increasing after 0006 LST, and peaking during the afternoon to evening hours. Cloud top height (CTH) shows bimodal distributions during the pre-flood and post-flood seasons. The most frequently occurring range of CTH during the pre-flood season is below 3 km, accounting for approximately 43%, while during the post-flood season, it ranges from 11 to 14 km, constituting about 37%. For precipitation clouds, CTH can extend beyond 12 km, with the radar reflectivity decreasing gradually with increasing height. The highest frequencies of radar echoes are observed below 2 km and between 4 and 7 km, exhibiting clear diurnal variations, with echoes mainly below 2 km and between 4 to 6 km during the early morning, intensifying and shifting to higher altitudes during the day and reaching their maximum below 4 km during the afternoon to nighttime hours, while both the frequency and intensity increase in the height range of 4 to 12 km. Vertical profiles of radar reflectivity and cloud ice/liquid water content (IWC/LWC) exhibit similar trends under different precipitation intensities. The main differences are observed below 4 km, where both radar reflectivity and IWC/LWC generally increase with increasing precipitation intensity. These findings contribute to a better understanding of cloud characteristics in the South China region, enhance the accuracy of model simulations, and provide a scientific basis for accurate forecasting and warning of meteorological disasters. [ABSTRACT FROM AUTHOR]

Soil moisture plays an important role in crop yield estimation, irrigation management, etc. Remote sensing technology has potential for large-scale and high spatial soil moisture mapping. However, offline remote sensing data processing is time-consuming and resource-intensive, and significantly hampers the efficiency and timeliness of soil moisture mapping. Due to the high-speed computing capabilities of remote sensing cloud platforms, a High Spatial Resolution Soil Moisture Estimation Framework (HSRSMEF) based on the Google Earth Engine (GEE) platform was developed in this study. The functions of the HSRSMEF include research area and input datasets customization, radar speckle noise filtering, optical-radar image spatio-temporal matching, soil moisture retrieving, soil moisture visualization and exporting. This paper tested the performance of HSRSMEF by combining Sentinel-1, Sentinel-2 images and in-situ soil moisture data in the central farmland area of Jilin Province, China. Reconstructed Normalized Difference Vegetation Index (NDVI) based on the Savitzky-Golay algorithm conforms to the crop growth cycle, and its correlation with the original NDVI is about 0.99 (P < 0.001). The soil moisture accuracy of the random forest model (R2 = 0.942, RMSE = 0.013 m3/m3) is better than that of the water cloud model (R2 = 0.334, RMSE = 0.091 m3/m3). HSRSMEF transfers time -consuming offline operations to cloud computing platforms, achieving rapid and simplified high spatial resolution soil moisture mapping. [ABSTRACT FROM AUTHOR]

The armyworm, Mythimna separata (Walker) (Lepidoptera: Noctuidae), is an important polyphagous pest with a strong migratory ability. Recently, third-generation larvae have become an increasingly serious pest threat in Jilin Province of northeast China. To investigate the population source of this species, scanning entomological radar observations and insect mitochondrial cytochrome oxidase I (COI) genes were used in this study. Five main results were found: (1) The peak period in captured second-generation moths was from mid to late July. The temperature and wind speeds were optimum for the moths to have migrated. Strong southwesterly winds occurred during the peak migration period. (2) Radar observations indicated that most of the moths' migration took place at a height of 600 m, often in a dense layer which formed at heights of 350-800 m. (3) Analyses of adult ovarian development and larval haplotypes showed third-generation larvae were progeny of both locally produced progeny and immigrant moths. (4) Based on our back-tracking and haplotype analyses, immigration led to an outbreak originated in the same source area to the southwest. (5) Emigration of second-generation moths was confirmed by both radar observation and mtDNA analysis. Forward trajectories indicated that the moths were capable of immigrating far from their overwintering range. These results are useful for improving the forecasting systems of this insect pest species., (© The Author(s) 2022. Published by Oxford University Press on behalf of Entomological Society of America.)

The detection of lava tubes beneath the surfaces of the Moon and Mars has been a popular research topic and challenge in planetary radar observation. In recent years, the Moon–based ground penetrating radar (GPR) carried by the Chinese Chang'e–3/–4 mission, the RIMFAX radar carried by the Mars mission Perseverance, and the RoSPR radar and MOSIR radar carried by China's Tianwen–1 orbiter have extensively promoted the exploration of the underground space of extraterrestrial bodies, which is crucial for the future utilization and development of these spaces. This paper expounds on the principles, methods, and detection results of using GPR to detect lava tubes on the Moon and Mars. First, lava tubes' formation mechanism and morphological characteristics are outlined, followed by an introduction to GPR's working principles and classification. The advantages, disadvantages, and prospects of different types of radar in detecting the lava tubes are analyzed. Finally, the distribution of lava tubes on the Moon and Mars is briefly summarized, and the potential utilization of lava tubes is discussed. We believe that the GPR technique is an effective geophysical method for exploring the underground structures of the Moon and Mars, and the lava tubes beneath the surface of extraterrestrial bodies can provide important references for selecting future Moon and Mars bases. [ABSTRACT FROM AUTHOR]

Understanding the diurnal variation of horizontal wind in the atmospheric boundary layer is important for weather and climate research and wind energy applications. Here we analyze the hourly data from 91 wind profiler radar sites in China and observe that the power spectral density of horizontal wind in lower troposphere approximately follows the −5/3 power law in the mesoscale range over the ocean and coastal areas. However, in inland areas, the slopes of the power spectra are significantly greater than −5/3. We characterize the temporal and spatial variations of maximum wind speed and low level jets and find that the thermal wind effect may partially contribute to the high percentage of low‐level jets observed in the southeastern coast of China and Hainan Island. While the ERA5 reanalysis reproduces wind spectrum well for time scales >1 day, its spectrum diverges significantly from that of profiler data at shorter time scales. Plain Language Summary: Understanding how the horizontal wind changes throughout the day in the lower part of the atmosphere is important for studying weather and climate and using wind energy. In this study, we looked at data from 91 radar sites in China that measure wind every hour. We found that the pattern of how the wind changes follows a specific mathematical relationship, called a power law, where the wind decreases in a particular way with decreasing spatial and temporal scales. This pattern holds true mostly over the ocean and coastal areas, but in areas further inland, the wind behaves a bit differently. We also studied how the low‐level jet (LLJ), which are fast winds at low altitudes, change over time and space. We discovered that the difference in temperature across the region contributes to the occurrence of these LLJs in coastal areas in southeast China and Hainan Island. Finally, we compare our findings with the ERA5 reanalysis, which demonstrates excellent agreement in reproducing the wind spectrum for time scales greater than 1 day. However, the spectrum derived from the ERA5 reanalysis diverges significantly from the profiler data at shorter time scales. Key Points: Wind spectrum density from wind profiler radars over China shows a less negative slope over inland sites than the −5/3 power law over oceanTemporal and spatial variation of maximum wind speed in the lower troposphere and low level jets are characterizedWind spectrum from ERA5 reanalysis is realistic (deficient) for time scales >1 day (<1 day) compared with profiler data [ABSTRACT FROM AUTHOR]

The Chinese-French Oceanography SATellite (CFOSAT) jointly developed by the Chinese National Space Agency (CNSA) and the Centre National d'Etudes Spatiales (CNES) of France carries a wave spectrometer (Surface Waves Investigation and Monitoring, SWIM). SWIM has one nadir and five off-nadir beams to measure ocean surface waves. These near-nadir beams range from 0° to 10° at an interval of 2°. In this work, we investigated the performance of wave parameters derived from wave spectra measured by SWIM at off-nadir beams during the period 2020 to December 2022, e.g., incidence angles of 6°, 8° and 10°, which were collocated with the wave simulated by Simulating Waves Nearshore (SWAN). The validation of SWAN-simulated significant wave heights (SWHs) against National Data Buoy Center (NDBC) buoys of National Oceanic and Atmospheric Administration (NOAA) exhibited a 0.42 m root mean square error (RMSE) in the SWH. Our results revealed a RMSE of 1.02 m for the SWIM-measured SWH in the East Pacific Ocean compared with the SWH simulated by SWAN, as well as a 0.79 correlation coefficient (Cor) and a 1.17 squared error (Err) for the wave spectrum at an incidence angle of 10°, which are better than those (i.e., the RMSEs were > 1.1 m with Cors < 0.76 and Errs > 1.2) achieved at other incidence angles of SWH up to 14 m. This analysis indicates that the SWIM product is a relevant resource for wave monitoring over global seas. The collocated wave retrievals for more than 300 cases from Gaofen-3 (GF-3) synthetic aperture radar (SAR) images in China Seas were also used to verify the accuracy of SWIM-measured wave spectra. The energy of the SWIM-measured wave spectra represented by SWH was found to decrease with an increasing incidence angle in a case study. Moreover, the SWIM-measured wave spectra were most consistent with the SAR-derived wave spectra at an incidence angle of 10°, yielding a 0.77 Cor and 1.98 Err between SAR-derived and SWIM wave spectra under regular sea state conditions (SWH < 2 m). The error analysis indicates that the difference in SWH between SWIM at an incidence angle of 10° and SWAN has an increasing tendency with the growth in sea surface wind and sea state and it stabilizes to be 0.6 m at SWH > 4 m; however, the current and sea level have less influence on the uncertainties of the SWIM product. [ABSTRACT FROM AUTHOR]

China's BeiDou navigation system has been completed and is currently in operation. As the newest constellation, BD-3 is composed of 30 satellite configurations. The application of BD-3 has improved rapidly, however, using the BD-3 signal as a signal resource in the global navigation satellite system (GNSS) passive radar domain to monitor deformation has not been proven to be feasible. The authors of his paper designed a BD-3 passive radar model and carried out a proof-of-concept experimental demonstration for deformation monitoring. As a result, a method based on the B3I signal as a signal resource for GNSS radar (GNSS-R) deformation monitoring is proven to be feasible. The experimental scenarios include laboratory simulation and proof of concept field displacement deformation. The test error reaches a value of 0.023 m for a simulation scenario, 0.0435 m for a field scene of deformation based on a target translation measurement, and 0.1011 m for a field scene of deformation based on a target rotation measurement. [ABSTRACT FROM AUTHOR]

China accomplished a historic milestone in 2020 when the mission Chang'e-5 (CE-5) to the Lunar's surface was successfully launched. An extraordinary component of this mission is the "Lunar Regolith Penetrating Radar" (LRPR) housed within its lander, which currently stands as the most advanced payload in terms of vertical resolution among all penetrating radars employed in lunar exploration. This provides an unprecedented opportunity for high-precision research into the interior structure of the shallow lunar regolith. Previous studies have achieved fruitful research results based on the data from LRPR, updating our perception of the shallow-level regolith of the Moon. This paper provides an overview of the new advancements achieved by the LRPR in observing the basic structure of the shallow regolith of the Moon. It places special emphasis on the role played by the LRPR in revealing details about the shallow lunar regolith's structure, its estimated dielectric properties, the provenance of the regolith materials from the landing area, and its interpretation of the geological stratification at the landing site. Lastly, it envisions the application and developmental trends of in situ radar technology in future lunar exploration. [ABSTRACT FROM AUTHOR]

Recent upgrades to China's radar network now allow for polarimetric measurements of convective systems in central China, providing an effective data set with which to evaluate the microphysics schemes employed in local squall line simulations. We compared polarimetric radar variables derived by Weather Research and Forecasting (WRF) and radar forward models and the corresponding hydrometeor species with radar observations and retrievals for a severe squall line observed over central China on 16 March 2022. Two microphysics schemes were tested and were able to accurately depict the contrast between convective and stratiform regions in terms of the drop size distribution (DSD) and reproduce the classical polarimetric signatures of the observed differential reflectivity (ZDR) and specific differential phase (KDP) columns. However, for the convective region, the simulated DSDs in both schemes exhibited lower proportions of large drops and lower liquid water content; by contrast, for the stratiform region, the proportion of large drops was found to be too high in the Morrison (MORR) scheme. The underprediction of ice-phase processes in the convective region, particularly the riming processes associated with graupel and hail, was likely responsible for the bias toward large raindrops at low levels. In the stratiform region, raindrop evaporation in the WRF Double-Moment 6-Class (WDM6) scheme, which partially offsets the overestimation of ice-phase processes, produced ground DSDs that more closely matched the observational data, and did not exhibit the overly strong warm-rain collisional growth processes of MORR. [ABSTRACT FROM AUTHOR]

Since early 2019, the Lunar Penetrating Radar (LPR) onboard Chang'e‐4 (CE‐4)'s Yutu‐2 rover has been gathering data relating to the subsurface structure of the Von Kármán crater within the South Pole‐Aitken Basin (SPA) on the lunar farside. Low‐frequency radar data have the potential of carrying geological information of about 300 m worth of strata below the traversed path. Forty‐two days' data have revealed a bifurcated structure within the layered structure beneath the CE‐4 surveying area for the first time, affecting the overlying reflectors between 90 and 310 m. This study suggests that, based on the morphological characteristics, thickness, depth (timing sequence) and direction of the newly found structure, its origin might be linked to the deposition of ejecta from the Schrödinger impact. The local stratigraphy is interpreted as consisting of distinct geological layers, corresponding to the superposition of ejecta from different impact craters, paleo‐regolith, and basaltic lava flows. Plain Language Summary: A radar (the Lunar Penetrating Radar, or LPR), built to look at the rocks below the surface, is presently traveling across an area of the lunar farside onboard a rover, called Yutu‐2 sent by China to shed some light on the striking difference between the Earth‐facing side of the Moon and its farside. So far, the radar has revealed layered structures interpreted as distinct volcanic flows, thus helping to unravel their history. The rover has been surveying the floor of the Von Kármán crater inside one of the oldest and largest impact structures of the Moon, the South Pole‐Aitken (SPA) Basin. By analyzing 42 lunar days of data, we found a new layer with a hunched upper surface and a relatively flat bottom inserted into a multilayered structure. Based on the morphology, thickness, depth, and direction of the new feature, we argue that its source could represent the ejecta deposition from one of the ancient lunar impact basins: Schrödinger. The subsurface structure revealed by the radar shows a complicated geologic history on the farside including multiple lava eruption events, the deposition of ejecta from different impact craters and weathering layers that develop during the quiescent stage. Key Points: The CH‐1 Lunar Penetrating Radar data of Chang'e‐4 reveals ∼300 m deep subsurface stratigraphy of the lunar farsideA unique bifurcated structure that resembles an ejecta discontinuity affects the overlying and underlying strataThe geologic evolution of the Von Kármán crater and the ejecta layer might be connected to the Schrödinger basin [ABSTRACT FROM AUTHOR]

In this study, the quantitative precipitation estimation (QPE) capability of three X-band dual-polarization phased array radars (PAR) in Guangzhou, South China, was demonstrated, with an S-band operational dual-polarization radar as the benchmark. Rainfall rate (R) estimators based on the specific differential phase (KDP) for summer precipitation for both X-band and S-band radars were derived from the raindrop size distributions (DSDs) observed by a 2-dimensional video disdrometer (2DVD) in South China. Rainfall estimates from the radars were evaluated with gauge observations in three events, including pre-summer rainfall, typhoon precipitation, and local severe convective precipitation. Observational results showed that radar echoes from the X-band PARs suffered much more severely from attenuation than those from the S-band radar. Compared to S-band observations, the X-band echoes can disappear when the signal-to-noise ratio drops to a certain level due to severe attenuation, resulting in different estimated rainfall areas for X- and S-band radars. The attenuation corrected by KDP had good consistency with S-band observations, but the accuracy of attenuation correction was affected by DSD uncertainty and may vary in different types of precipitation. The QPE results demonstrated that the R(KDP) estimator produced better rainfall accumulations from the X-band PAR observations compared to the S-band observations. For both the X-band and S-band radars, the estimates of hourly accumulated rainfall became more accurate in heavier rainfall, due to the decreases of both the DSD uncertainty and the impact of measurement errors. In the heavy precipitation area, the estimation accuracy of the X-band radar was high, and the overestimation of the S-band radar was obvious. Through the analysis of the ZH-ZDR distribution in the three weather events, it was found that the X-band PAR with the capability of high spatiotemporal observations can capture minute-level changes in the microphysical characteristics, which help improve the estimation accuracy of ground rainfall. [ABSTRACT FROM AUTHOR]

Different from the aircraft TC reconnaissance flight missions before, a tropical cyclone (TC) field campaign project with a Doppler radar equipped on an airship that could hang over on the top of a TC (about 20 km) has been recently carried out in China. To understand the impact of airship-borne radar radial wind observations in TC forecasting, this work conducted quick observation simulation system experiments (QuickOSSE) by assimilating simulated airship-borne Doppler radar radial winds with an Ensemble Kalman Filter (EnKF) algorithm. The results show that airship-borne radial winds assimilation reproduces the forecasted track and minimum sea level pressure of the nature run. The forecast of dynamic and thermodynamic TC structures, such as tangential wind, secondary circulation, and warm core, are also improved. In addition, two determining factors, the radar depression angle (D-ang) and the distance from the airship to the TC center (DIS), are found to primarily affect the forecast of the TC track and intensity, respectively. Benefiting from a larger horizontal coverage, observations under a smaller D-ang improved the track more significantly. Meanwhile, the intensity forecast error with a DIS around the radius of the maximum wind is the smallest among several sensitive experiments, which may because the peak-velocity winds representing the TC's intensity could be observed by radar. The results are expected to help establish an observational strategy for upcoming airship flight missions in practice. [ABSTRACT FROM AUTHOR]

Based on the 20-year high-resolution precipitation data from TRMM and GPM radar products, diurnal features over complex terrains along the Yangtze River (YR) are investigated. Using the Fast Fourier Transform (FFT) method, the first (diurnal) and second (semi-diurnal) harmonic amplitude and phase of precipitation amount (PA), precipitation frequency (PF), and intensity (PI) are analyzed. The diurnal amplitudes of PA and PF have a decreasing trend from the west to the east with the decreasing altitude of large-scale terrain, while the semi-diurnal amplitudes of PA and PI depict the bimodal precipitation cycle over highlands. For the eastward propagation of PA, PF is capable of depicting the propagation from the upper to the middle reaches of YR, while PI shows the eastward propagation from the middle to the lower reaches of YR during nighttime and presents sensitivity to highlands and lowlands. According to the contribution of different-sized precipitation systems to PI over the highlands and lowlands, the small (<200 km2) ones contribute the least while the large ones (>6000 km2) contribute the most, but the medium ones (200–6000 km2) show a slightly larger contribution over the highlands than over the lowlands. The propagation of each scaled precipitation system along the YR is further analyzed. We found that small precipitation systems mainly happen in the afternoon without obvious propagation. Medium ones peak 2–4 h later than the small ones, with two eastward propagation directions at night from the middle reaches of YR to the east. The large ones are mainly located in lowlands at night, with two propagation routes in the morning over the middle and lower reaches of YR. Such a relay of the propagation of the medium and large precipitation systems explains the eastward movement of PI along the YR, which merits future dynamic studies. [ABSTRACT FROM AUTHOR]

Copyright of Advances in Atmospheric Sciences is the property of Springer Nature and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

During the pre-summer rainy season, heavy rainfall occurs frequently in South China. Based on polarimetric radar observations, the microphysical characteristics and processes of convective features associated with extreme rainfall rates (ERCFs) are examined. In the regions with high ERCF occurrence frequency, sub-regional differences are found in the lightning flash rate (LFR) distributions. In the region with higher LFRs, the ERCFs have larger volumes of high reflectivity factor above the freezing level, corresponding to more active riming processes. In addition, these ERCFs are more organized and display larger spatial coverage, which may be related to the stronger low-level wind shear and higher terrain in the region. In the region with lower LFRs, the ERCFs have lower echo tops and lower-echo centroids. However, no clear differences of the most unstable convective available potential energy (MUCAPE) exist in the ERCFs in the regions with different LFR characteristics. Regardless of the LFRs, raindrop collisional coalescence is the main process for the growth of raindrops in the ERCFs. In the ERCFs within the region with lower LFRs, the main mechanism for the rapid increase of liquid water content with decreasing altitude below 4 km is through the warm-rain processes converting cloud drops to raindrops. However, in those with higher LFRs, the liquid water content generally decreases with decreasing altitude. [ABSTRACT FROM AUTHOR]

Since Mars is far away from Earth, the propagation delay between Mars and Earth is very large. To ensure the effective use of the link transmission bandwidth, China's first Mars exploration mission has put forward a demand for data compression for all scientific payloads. The on-board mature algorithms for data compression are mainly focused on optical images and microwave imaging radar applications. No articles have been published on data compression methods that are applied to subsurface-penetrating radar. Based on the background of this application, this paper proposes a logarithmic lossy compression algorithm which can meet the mission requirements for high compression ratios of 4:1 and 2.5:1. Its compression error is less than that of the block adaptive quantization (BAQ) algorithm. The algorithm is not only easy to implement on field-programmable gate array (FPGA) platforms, but also offers simple ground decompression and fast imaging. The experimental results show that high compression ratios of 4:1 and 2.5:1 can be realized, even if the data in and between traces do not have a strong correlation. And its relative error is less than 2%, which is a new type of high-efficiency data compression method that can be implemented on-board to meet with the demand of subsurface penetrating radar. [ABSTRACT FROM AUTHOR]

The Rover-mounted Subsurface Penetrating Radar (RoSPR) is one of the scientific payloads onboard China's first independent Mars exploration mission, Tianwen-1. The radar aims to characterize the thickness of the upper Martian soil and investigate the subsurface stratigraphy by collecting and processing the data. This article is mainly divided into two parts, the introduction of data pre-processing and analysis of pre-processed radar signals, aiming at helping scientists make more effective use of radar data. The first part describes the operating principle of the RoSPR and the procedure of radar data pre-processing at all levels. Data pre-processing is mainly designed to transfer the raw data format to a common PDS (Planetary Data System) and eliminate the influence of the instrument. In the signal analysis part, the performances of both self-check signals and echo signals of low- and high-frequency channels are analyzed, which indicate a stable radar system and are useful for background removal. Phase and time calibration is of great importance for improving data quality and making the radar data more accurate. Moreover, further processing is required to obtain clear radar images, such as filtering, background removal and gain setting. [ABSTRACT FROM AUTHOR]

The mine roadway built in the same thick rock stratum will not change the lithologic medium in front of the roadway under the influence of the small structure of the mine, which makes the mine radar face many difficulties in structural interpretation. In the coal measure strata in southwest China, the coal seam roof is the weak aquifer of the Kayitou (T1k) group. The mine structure is the excellent drainage boundary of an aquifer, resulting in the water content of the structural belt being different from that of the surrounding rock. This paper proposes a method to identify hidden structures in mine roadways using the autoregressive and moving average power spectrum energy enveloping medium water content inversion technique. Based on the actual water content of strata in the study area, 48 roadway models are constructed. The finite‐difference time‐domain algorithm was used to obtain the forward data and calculate the volumetric water content of the model. The structure of the roadway model is accurately identified by the water content difference. In the numerical simulation study, the segmentation frequency of high‐frequency and low‐frequency envelope of the autoregressive and moving average spectrum of 100‐MHz radar antenna is determined to be 155 MHz, and the value range of water content calculation regulation parameter k is determined. The high‐ and low‐frequency envelope inversion characteristics of the autoregressive and moving average spectrum of different tunnel media models are summarized and analysed. To solve the calculation problem of energy envelope selection of autoregressive and moving average power spectrum of engineering data, the k‐nearest neighbour machine learning algorithm was used to learn and classify the power spectrum features of different tunnel models. The detection application is analysed through the whole‐rock medium and coal and rock medium roadway in the study area. The results show that the method can effectively identify the location and strike characteristics of the hidden structures in front of the roadway. [ABSTRACT FROM AUTHOR]

Wavenumber–frequency spectra obtained with coherent microwave radar at upwind-grazing angle consist of energy along the ocean wave dispersion relation and additional features that lie above this relation labeled as "high-order harmonic" and below this relation known as "group line." Due to these nonlinear features, low-frequency components appear in the radar-estimated wave spectrum and the energy and peak frequency of the dominant wave spectrum decrease, which are responsible for the overestimation of radar-measured wave period. According to the component distribution in the wavenumber–frequency spectrum, a mean wave period inversion method based on a dispersion relation filter for coherent S-band radar is proposed. The method filters out the "group line" and preserves the high-order harmonic to compensate for the energy loss caused by the decrease of peak frequency of the dominant wave spectrum. A two-dimensional inverse Fourier transform is applied to the filtered wavenumber–frequency spectrum. Then the radar-measured velocity sequence is selected to obtain the velocity spectrum via a one-dimension Fourier transform. The wave height spectrum is estimated from the one-dimensional velocity spectrum by the direct transform relationship between the one-dimensional velocity spectrum and the wave height spectrum. Later, mean wave periods can be derived by the first moment of the wave height spectrum. A 13-day dataset collected with a shore-based coherent S-band radar deployed at Zhelang, China, is reanalyzed and used to retrieve mean wave periods. Comparisons between the measurements of radar and wave buoy are conducted. The results indicate that the proposed method improves the wave period measurement for coherent S-band radar. Significance Statement: This work provides a mean wave period inversion method for coherent S-band radar. The mean wave period is always overestimated due to the "group line" in the wavenumber–frequency spectrum and the energy loss caused by the decrease of peak frequency of the dominant wave spectrum. Therefore, dealing with these estimation errors is important. [ABSTRACT FROM AUTHOR]

We report for the first time a case of wavelike structures of E‐region irregularities observed by an all‐sky radar at Ledong (18.44°N, 108.97°E), China. The wavelike structures covered up to 250 km zonally, fluctuated in the vertical and horizontal planes, and were observed in the directions perpendicular and significantly off‐perpendicular to the geomagnetic field. The wavelength, and vertical and horizontal oscillating amplitudes were estimated at about 20–70, 5, and 2 km, respectively. Eventually, the large‐scale wavelike structure broke into spatially separated small‐scale patches and disappeared. The case provides observational evidence for the wave modulating sporadic E (Es) mechanism, which suggests that the wavelike structures of E‐region irregularity were primarily generated by wind shears and modulated by gravity waves. The wavelike structure was possibly an intermediate state between the continuous‐type and quasiperiodic‐type E‐region irregularities. The mechanism responsible for the echoing structure observed in off‐perpendicular directions is unclear. The possible contributions from refraction and reflection by intense Es layer/structure were discussed. Plain Language Summary: The E‐region irregularities were usually observed using narrow‐beam very high frequency radars. Due to the limited field‐of‐view (FOV) of the narrow‐beam radars, the spatial morphology of large‐scale irregularity structures could not be obtained. Over low latitudes, the E‐region irregularities were traditionally classified into two main types: the continuous type linked with the tidal sporadic E (Es) layer and the quasiperiodic (QP) type due to the drift of small irregularity patches. Facilitating from the very large FOV of the all‐sky radar at Ledong, we report a case of E‐region irregularities with different echo patterns from the continuous and the QP types. These E‐region irregularities showed wavelike structures covering up to 250 km in the zonal direction and were observed in directions both perpendicular and significantly off‐perpendicular to the geomagnetic field. In combination with the collocated Es and neutral wind measurements, the possible mechanisms responsible for the wavelike irregularity structures are discussed. Key Points: Wavelike structures of E‐region irregularities elongating up to 250 km are reported at low latitudes for the first timeThe wavelike structures were most likely generated by wind shears and modulated by gravity wavesThe wavelike structures may be an intermediate state between the continuous‐type and quasiperiodic‐type E‐region irregularities [ABSTRACT FROM AUTHOR]

Much of the Martian surface is covered by a weathering layer (regolith or soil) produced by long-term surface processes such as impact gardening, eolian erosion, water weathering, and glacial modifications. China’s first Martian mission, Tianwen-1, employed the Mars Rover Penetrating Radar (RoPeR) to unveil the detailed structure of the regolith layer and assess its loss tangent. The RoPeR radargram revealed the local regolith layer to be highly heterogeneous and geologically complex and characterized by structures that resemble partial or complete crater walls and near-surface impact lenses at a very shallow depth. However, comparable radar data from the Lunar far side are rather uniform, despite the two surfaces being geologically contemporary. The close-to-surface crater presented in this study shows no detectable surface expression, which suggests an accelerated occultation rate for small craters on the surface of Mars as compared to the rate on the Moon. This is probably due to the relentless eolian processes on the Martian surface that led to the burial of the crater and thus shielded it from further erosion. The high loss tangent indicates that the regolith at the Tianwen-1 landing site is not dominated by water ice. [ABSTRACT FROM AUTHOR]

Weather radars are commonly used to track the development of convective storms due to their high resolution and accuracy. However, the coverage of existing weather radar is very limited, especially in mountainous and ocean areas. Geostationary meteorological satellites can provide near global coverage and near real-time observations, which can compensate for the lack of radar observations. In this paper, a deep learning method was used to estimate the radar composite reflectivity from observations of China's new-generation geostationary meteorological satellite FY-4A and topographic data. The derived radar reflectivity products from satellite observations can be used over regions without radar coverage. In general, the deep learning model can reproduce the overall position, shape, and intensity of the radar echoes. In addition, evaluation of the reconstruction radar observations indicates that a modified model based on the attention mechanism (Attention U-Net model) has better performance than the traditional U-Net model in terms of all statistics such as the probability of detection (POD), critical success index (CSI), and root-mean-square error (RMSE), and the modified model has stronger capability on reconstructing details and strong echoes. [ABSTRACT FROM AUTHOR]

In this study, the spatiotemporal distribution and characteristics of different precipitation types (stratiform, convective, and snow) over China are analyzed using the radar mosaic images during the summer season over 4 years (from 2018 to 2021). The convective precipitation occurs most frequently along the eastern coast regions. In June, the strong convection center is located in Southern China and moves northward to Eastern China in July, while the lowest frequency occurs in August. Stratiform precipitation dominates summer precipitation over China and mainly distributes in inland regions, with the highest frequency in August. Snowfall primarily presents in the mountains and plateau regions of Western China with the frequency of occurrence around 20%. The snowfall area in July is significantly smaller than that in June and August. The convective, stratiform, and snowfall show strong diurnal variation in terms of solar standard time (LST) especially for snowfall. The convective precipitation demonstrates a bimodal pattern, with the highest peak in the afternoon (15–16 LST) and the secondary peak in the early morning (04–07 LST). Stratiform precipitation is mainly active from the afternoon to the next morning (14–05 LST). Snowfall is significantly more common in the nighttime (around 12%) than in the daytime (around 4%). The occurrence ratio of snowfall at midnight in July is significantly higher than that in June and August. It is expected that this study on summer precipitation over China can be used as a reference to hydrometeorological research and also to improve the understanding of radar precipitation research over China. [ABSTRACT FROM AUTHOR]

In order to change the energy supply structure of traditional thermal power generation with excessive carbon emissions, more and more offshore wind turbines are being installed and put into operation worldwide. However, the dynamic monitoring of offshore wind turbines is still an emerging problem to be solved at a global scale. This paper proposes an effective approach for dynamic detection of offshore wind turbines by machine learning from spaceborne synthetic aperture radar (SAR) Sentinel-1 satellite data. First, the radar images are preprocessed to reduce the speckle noise and ocean wave clutter. Specifically, the time series radar data are cumulatively averaged according to the monthly interval to eliminate the influence of moving temporary objects such as ships; then, the speckle noise is suppressed using refined lee filter; the imagery affected by ocean wave clutters are also mitigated by using a constant false alarm rate (CFAR) technique. Next, representative data are carefully selected as the labeled training data set; and the random forest (RF) model is trained on the Google Earth Engine (GEE) cloud computing platform. Validation demonstrates an overall accuracy of 99.99%, a producer accuracy of 100%, and an user accuracy of 94.12%. Then, mathematical morphology-based time series spatial data differentiation is proposed for monitoring the change of wind turbine. Finally, the dynamic change of the offshore wind farms in the Yellow Sea of China and the North Sea of Europe are monitored by using the proposed approach from 2015 to 2021. Cross-comparisons with ground truth data show an accuracy of 93.67% for dynamic detection of offshore wind turbines. From a large number of experimental results, it is shown that the proposed approach has the advantages of large scale monitoring and high precision, and can be used for global dynamic detection of offshore wind turbines. [ABSTRACT FROM AUTHOR]

We present the first continuous observations of three‐dimensional spatially resolved wind fields and atmospheric motions in the mesosphere and lower thermosphere in the mid‐latitudes of the Northern Hemisphere. Our observations were performed during a 19‐month campaign from January 2022 to July 2023 and exploited the composite data from the first multistatic meteor radar system in China and an adjacent monostatic meteor radar. To retrieve the atmospheric kinetic properties, we introduce an improved volume velocity processing method including coordinate transformations and non‐linear constraints to minimize errors. The vertical winds are estimated separately from the iteration of the horizontal divergence to avoid potential biases or contamination from the horizontal winds. The winds and air motions show annual/semiannual variation characteristics within certain altitudes, usually more variable around the equinoxes. The vertical winds are basically within the magnitude of 1 m/s and are upward as expected at the mesopause during the summer, which corresponds to the adiabatic cooling. Plain Language Summary: The mesosphere and lower thermosphere (MLT) is a coupling region between the upper and lower atmosphere and contains various dynamic and chemical processes. Meteor is a convenient and reliable tool for MLT mean horizontal wind observations. Multistatic meteor radars can investigate the more sophisticated dynamic properties of the MLT winds from different viewing angles. In this work, for the first time, we reported 3‐dimensional spatially resolved MLT winds and atmospheric motions in the mid‐latitudes of the Northern Hemisphere. To minimize errors in the retrieved winds, we proposed improvements to the volume velocity processing method by performing coordinate transformations and adding non‐linear constraints. The mean winds and air motions show annual/semiannual variations and are more variable near the equinoxes. Due to the small value of the vertical wind, we estimated it from the integration of the horizontal divergence and obtained a reasonable range of less than 1 m/s. The upwelling in the summer mesopause corresponds to the adiabatic cooling. Key Points: The first continuous observations of 3‐D spatially resolved winds and air motions in the Northern Hemisphere mid‐latitudes are reportedA newly developed volume velocity processing method including coordinate transformations and non‐linear constraints is introducedThe vertical wind is basically less than 1 m/s and is upward at the mesopause during summer, corresponding to the adiabatic cooling [ABSTRACT FROM AUTHOR]

In the early stages, uncontrolled groundwater extraction led to the Hangjiahu (HJH) Plain becoming one of the areas with the most severe land subsidence in China. Since the beginning of this century, comprehensive measures have been taken to control the continuous aggravation of large land subsidence patterns in some areas; however, urban land subsidence issues, influenced by various factors, still persist and exhibit complex geographical distribution characteristics. In this study, we utilized Sentinel-1A images and the SBAS-InSAR technique to capture surface deformation over the HJH Plain in Zhejiang from 16 March 2017 to 20 January 2023. Through a comparative analysis with geological conditions, changes in surface mass loading, rainfall and groundwater, and land use types, we discussed the contributions of natural and anthropogenic factors to land subsidence. Augmented with optical remote sensing images and field investigations, we conducted a correlation analysis of the land subsidence status. The preliminary findings suggest that changes in surface mass loading and short-term heavy rainfall under extreme weather conditions can lead to periodic land subsidence changes in the region. Additionally, extensive infrastructure construction triggered by urbanization has resulted in significant and sustained land subsidence deformation. The research findings play an important guiding role in formulating scientifically effective strategies for land subsidence prevention and control, as well as urban planning and construction. [ABSTRACT FROM AUTHOR]

A summer convective precipitation case, occurring in eastern China on 16–17 July 2020, is selected to investigate the impact of joint assimilation of ground-based profiling platforms and weather radars on forecasting convective storms using observational system simulation experiments (OSSEs). The simulated profiling platforms include the Doppler wind lidar (DWL), a wind profiler (WP), and a microwave radiometer (MWR). Results show that joint assimilation of WP and radar data produces a better analysis of convective dynamical structure than joint assimilation of DWL and radar data, since WP detects deeper layer winds. Joint assimilation of MWR and radar data enables rapid adjustment of temperature and humidity and thus, avoids the potential errors introduced by the latent heat term of the radar diabatic initialization in the early stage. Profiling observations in a horizontal spacing of 80 km provide fewer benefits for convective forecasting, while reducing the spacing to 40 km can dramatically improve model analysis and forecasts. Joint assimilation of multiple profiling observations in a 20-km horizontal spacing with radar data exhibits a beneficial synergistic effect and mitigates "the ramp-down issue" during the forecast stage. Assimilating profiling observations with an update interval less than 30 min does not have as pronounced an effect on convective forecasts as horizontal spacing. Furthermore, assimilating profiling observations at a 20-km horizontal spacing can obtain accurate mesoscale background environment and forecast storms with an ability comparable to radar data assimilation. This work emphasizes the need to consider implementing a joint mesoscale detection system that incorporates weather radars and profiling observations for leveraging convective storm forecasting. [ABSTRACT FROM AUTHOR]

A new dual-frequency Stratospheric Tropospheric (ST) / Meteor radar has been built and installed at the Langfang Observatory in northern China. It utilizes a novel two-frequency system design that allows interleaved operation at 53.8 MHz for ST mode and at 35.0 MHz for Meteor mode, thus optimizing performance for both ST wind retrieval and meteor trail detection. In dedicated meteor mode, the daily meteor count rate reaches over 40,000 and allows wind estimation at finer time resolutions than the 1-hour typical of most meteor radars. The root mean square uncertainty of the ST wind measurements is better than 2 m/s when estimating the line of best fit with radiosonde winds. Preliminary observation results for one month of winter gravity wave (GW) momentum fluxes in the mesosphere, lower stratosphere and troposphere are also presented. A case of waves generated by the passage of a cold front is found. [ABSTRACT FROM AUTHOR]

Interferometric synthetic aperture radar (InSAR) has developed rapidly over the past years and is considered as an important method for surface deformation monitoring, benefiting from growing data quantities and improving data quality. However, the handing of SAR big data poses significant challenges for related algorithms and pipeline, particularly in large-scale SAR data processing. In addition, InSAR algorithms are highly complex, and their task dependencies are intricate. There is a lack of efficient optimization models and task scheduling for InSAR pipeline. In this paper, we design parallel time-series InSAR processing models based on multi-thread technology for high efficiency in processing InSAR big data. These models concentrate on parallelizing critical algorithms that have high complexity, with a focus on deconstructing two computationally intensive algorithms through loop unrolling. Our parallel models have shown a significant improvement of 10–20 times in performance. We have also developed a parallel optimization tool, Simultaneous Task Automatic Runtime (STAR), which utilizes a data flow optimization strategy with thread pool technology to address the problem of low CPU utilization resulting from multiple modules and task dependencies in the InSAR processing pipeline. STAR provides a data-driven pipeline and enables concurrent execution of multiple tasks, with greater flexibility to keep the CPU busy and further improve CPU utilization through predetermined task flow. Additionally, a supercomputing-based system has been constructed for processing massive InSAR scientific big data and providing technical support for nationwide surface deformation measurement, in accordance with the framework of time series InSAR data processing. Using this system, we processed InSAR data with the volumes of 500 TB and 700 TB in 5 and 7 days, respectively. Finally we generated two maps of land surface deformation all over China. [ABSTRACT FROM AUTHOR]