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Crowd movement analysis (CMA) is a key technology in the field of public safety. This technology provides reference for identifying potential hazards in public places by analyzing crowd aggregation and dispersion behavior. Traditional video processing techniques are susceptible to factors such as environmental lighting and depth of field when analyzing crowd movements, so cannot accurately locate the source of events. Radar, on the other hand, offers all-weather distance and angle measurements, effectively compensating for the shortcomings of video surveillance. This paper proposes a crowd motion analysis method based on radar particle flow (RPF). Firstly, radar particle flow is extracted from adjacent frames of millimeter-wave radar point sets by utilizing the optical flow method. Then, a new concept of micro-source is defined to describe whether any two RPF vectors originated from or reach the same location. Finally, in each local area, the internal micro-sources are counted to form a local diffusion potential, which characterizes the movement state of the crowd. The proposed algorithm is validated in real scenarios. By analyzing and processing radar data on aggregation, dispersion, and normal movements, the algorithm is able to effectively identify these movements with an accuracy rate of no less than 88%.

Using Unoccupied Aerial Systems (UAS) equipped with optical RGB cameras and Doppler radar, surface velocity can be efficiently measured at high spatial resolution. UAS‐borne Doppler radar is particularly attractive because it is suitable for real‐time velocity determination, because the measurement is contactless, and because it has fewer limitations than image velocimetry techniques. In this paper, five cross‐sections (XSs) were surveyed within a 10 km stretch of Rönne River in Sweden. Ground‐truth surface velocity observations were retrieved with an electromagnetic velocity sensor (OTT MF Pro) along the XS at one m spacing. Videos from a UAS RGB camera were analyzed using both Particle Image Velocimetry (PIV) and Space‐Time Image Velocimetry (STIV) techniques. Furthermore, we recorded full waveform signal data using a Doppler radar at multiple waypoints across the river. An algorithm fits two alternative models to the average amplitude curve to derive the correct river surface velocity based on Gaussian models with: (a) one peak, and (b) two peaks. Results indicate that river flow velocity and propwash velocity caused by the drone can be found in XS where the flow velocity is low, while the drone‐induced propwash velocity can be neglected in fast and highly turbulent flows. To verify the river flow velocity derived from Doppler radar, a mean PIV value within the footprint of the Doppler radar at each waypoint was calculated. Finally, quantitative comparisons of OTT MF Pro data with STIV, mean PIV and Doppler radar revealed that UAS‐borne Doppler radar could reliably measure the river surface velocity. Plain Language Summary Based on the Doppler effect occurring when electromagnetic waves are reflected by a moving target, a Doppler radar can measure the river surface flow velocity. Doppler radars mounted on Unoccupied Aerial Systems (UAS) are attractive because they are suitable for real‐time velocity determination and contactless measurement under a wide variety of environmental conditions and river sites. Here, five selected cross‐sections were surveyed within a 10 km stretch of Rönne River in Sweden by using UAS Doppler radar. The recorded raw Doppler radar signals were processed to obtain the river surface velocity and the drone‐induced propwash velocity. To validate the Doppler results, river surface velocity was recorded in situ and using image‐cross correlation techniques as well. Comparisons of flow velocities derived from different techniques indicated that the UAS Doppler radar can reliably measure the river surface velocity with the footprint resolution. This paper provided processing procedures for the raw Doppler radar signals, which are useful for further development of UAS‐borne Doppler radar. Key Points Unoccupied Aerial Systems Doppler radar can measure river surface flow velocity We pick the correct river surface velocity from the raw Doppler spectra, using either a Gaussian one peak model, or a Gaussian two peak model Particle Image Velocimetry results within the Doppler footprint verify the estimated velocities from Doppler radar

Snow‐cloud microphysics over inland hills partly resembles that over high mountains, yet exhibits notable differences. During 2024–2025 winter, coordinated observations in Tokamachi City, Niigata Prefecture, Japan, were conducted using four launches of a newly developed balloon‐borne particle‐imaging radiosonde (Rainscope) together with dual X‐band polarimetric radars deployed on both sides of Uonuma Hill (approximately 700 m ASL). Snow‐particle growth processes differed markedly depending on whether airflow passed over or was blocked by hills. Graupel formation is influenced by multiple mechanisms: advection from coastal convective clouds, orographic ascent along slopes, mountain‐wave propagation leeward of the hills, and seeder‐feeder interactions upstream. The findings demonstrate that even modest inland terrain can modulate snow‐cloud microphysics substantially, highlighting the complex role of hills in winter precipitation.

Powder snow avalanches (PSAs) radiate infrasound energy, yet the source mechanism remains unclear, limiting hazard monitoring and mitigation with infrasound‐based technologies. Here, we analyze a unique data set from a large PSA to improve the understanding of the source mechanism. Through comparison of cluster activity within the airborne layers of the PSA and the recorded infrasound signal in the frequency domain, we demonstrate that infrasound is mainly generated from particle clusters suspended by turbulent eddies or ejected from the denser basal layer. Further correlating infrasound amplitudes with radar‐derived spatial distributions of these clusters, we reveal a distributed source extending hundreds of meters behind the avalanche front. Additionally, we establish a relationship between infrasound and kinetic energy of suspended particles. These findings deepen our understanding of the complex dynamics of infrasound generation, offering valuable insights for avalanche detection and early warning strategies, and fundamental comprehension of PSA dynamics. Plain Language Summary Powder snow avalanches (PSAs) generate low‐frequency sound waves below the threshold of human hearing, called infrasound. Infrasound can travel long distances, which allows for simple and effective avalanche monitoring. However, it is unclear where and how infrasound is produced, limiting the use of infrasound detection systems for avalanche risk management. To address this, we analyze data from a large naturally occurring PSA. We match the activity of suspended snow particles in the airborne layers, captured by a high‐speed camera, with the recorded infrasound. We show that infrasound may originate from particle clusters carried by turbulent eddies or expelled from the denser regions of the PSA. Using radar measurements, we map the spatial distribution of these clusters, revealing an infrasound source extending hundreds of meters behind the avalanche front. Furthermore, we find a connection between infrasound and the kinetic energy of suspended particles, offering a new approach to assess the destructive potential of PSAs. These findings deepen our understanding of infrasound generation during avalanches, providing crucial information for avalanche detection, early warning systems, and understanding the mechanisms behind PSA generation. Moreover, the findings could also be valuable for understanding and managing similar types of gravitational flows, such as pyroclastic surges during volcanic eruptions. Key Points Particle clusters suspended in the airborne layers of powder snow avalanches (PSAs) are the dominant source of infrasound Infrasound from PSAs originates from a distributed source, extending up to hundreds of meters behind the avalanche front Infrasound from PSAs is proportional to the kinetic energy of the particle clusters in suspension

The stability of the world’s largest glaciers and ice sheets depends on mechanical and thermodynamic processes occurring at the glacier–ocean boundary. A buoyant agglomeration of icebergs and sea ice, referred to as ice mélange, often forms along this boundary and has been postulated to affect ice-sheet mass losses by inhibiting iceberg calving. Here, we use terrestrial radar data sampled every 3 min to show that calving events at Jakobshavn Isbræ, Greenland, are preceded by a loss of flow coherence in the proglacial ice mélange by up to an hour, wherein individual icebergs flowing in unison undergo random displacements. A particle dynamics model indicates that these fluctuations are likely due to buckling and rearrangements of the quasi-two-dimensional material. Our results directly implicate ice mélange as a mechanical inhibitor of iceberg calving and further demonstrate the potential for real-time detection of failure in other geophysical granular materials. Calving of an outlet glacier in Greenland is consistently preceded by distinctive flow patterns in the mélange of sea ice and icebergs in front of the terminus, according to terrestrial radar observations and particle dynamic modelling of the Jakobshavn Isbræ system.

The seeder–feeder mechanism has been observed to enhance orographic precipitation in previous studies. However, the microphysical processes active in the seeder and feeder region are still being understood. In this paper, we investigate the seeder and feeder region of a mixed-phase cloud passing over the Swiss Alps, focusing on (1) fallstreaks of enhanced radar reflectivity originating from cloud top generating cells (seeder region) and (2) a persistent low-level feeder cloud produced by the boundary layer circulation (feeder region). Observations were obtained from a multi-dimensional set of instruments including ground-based remote sensing instrumentation (Ka-band polarimetric cloud radar, microwave radiometer, wind profiler), in situ instrumentation on a tethered balloon system, and ground-based aerosol and precipitation measurements. The cloud radar observations suggest that ice formation and growth were enhanced within cloud top generating cells, which is consistent with previous observational studies. However, uncertainties exist regarding the dominant ice formation mechanism within these cells. Here we propose different mechanisms that potentially enhance ice nucleation and growth in cloud top generating cells (convective overshooting, radiative cooling, droplet shattering) and attempt to estimate their potential contribution from an ice nucleating particle perspective. Once ice formation and growth within the seeder region exceeded a threshold value, the mixed-phase cloud became fully glaciated. Local flow effects on the lee side of the mountain barrier induced the formation of a persistent low-level feeder cloud over a small-scale topographic feature in the inner-Alpine valley. In situ measurements within the low-level feeder cloud observed the production of secondary ice particles likely due to the Hallett–Mossop process and ice particle fragmentation upon ice–ice collisions. Therefore, secondary ice production may have been partly responsible for the elevated ice crystal number concentrations that have been previously observed in feeder clouds at mountaintop observatories. Secondary ice production in feeder clouds can potentially enhance orographic precipitation.

The process of riming significantly impacts the microphysical characteristics of clouds. This study uses aircraft and radar observation data in stratiform clouds with convection embedded that occurred in the central and southern regions of North China on 22 May 2017. The microphysical structural characteristics and processes near the embedded convection core and in the stratiform cloud are analyzed comparatively. Particular attention is given to the effect of riming on the microphysical properties near the upper boundary of the melting layer and to the factors influencing riming efficiency. The collaborative observations reveal that the particle size distributions observed near the convection core and in the stratiform region are close, while the particle properties like habit and riming degree are quite different. Above the melting layer, larger plate-like ice particles and supercooled water droplets ( D > 50 μm) are more abundant near the convective core, leading to higher collision efficiencies between ice particles and supercooled water droplets. Larger fluctuation amplitudes of vertical airflow near the convective core also contribute to the increased riming activity and the formation of more heavily rimed particles, such as graupel. Furthermore, in situ measurements from airborne probes also revealed that above the melting layer, the riming process involves two stages: the mass of snow crystals grows as supercooled droplets merge internally without changing size, followed by external freezing that significantly enlarges the crystals.

The Cloud, Aerosol, and Complex Terrain Interactions (CACTI) field campaign was designed to improve understanding of orographic cloud life cycles in relation to surrounding atmospheric thermodynamic, flow, and aerosol conditions. The deployment to the Sierras de Córdoba range in north-central Argentina was chosen because of very frequent cumulus congestus, deep convection initiation, and mesoscale convective organization uniquely observable from a fixed site. The C-band Scanning Atmospheric Radiation Measurement (ARM) Precipitation Radar was deployed for the first time with over 50 ARM Mobile Facility atmospheric state, surface, aerosol, radiation, cloud, and precipitation instruments between October 2018 and April 2019. An intensive observing period (IOP) coincident with the RELAMPAGO field campaign was held between 1 November and 15 December during which 22 flights were performed by the ARM Gulfstream-1 aircraft. A multitude of atmospheric processes and cloud conditions were observed over the 7-month campaign, including numerous orographic cumulus and stratocumulus events; new particle formation and growth producing high aerosol concentrations; drizzle formation in fog and shallow liquid clouds; very low aerosol conditions following wet deposition in heavy rainfall; initiation of ice in congestus clouds across a range of temperatures; extreme deep convection reaching 21-km altitudes; and organization of intense, hail-containing supercells and mesoscale convective systems. These comprehensive datasets include many of the first ever collected in this region and provide new opportunities to study orographic cloud evolution and interactions with meteorological conditions, aerosols, surface conditions, and radiation in mountainous terrain.

Raindrop size sorting is a ubiquitous microphysical occurrence in precipitating systems. Owing to the greater terminal fall speed of larger particles, a raindrop’s fall trajectory can be sensitive to its size, and strong air currents (e.g., a convective updraft) can enhance this sensitivity. Indeed, observational and numerical model simulation studies have confirmed these effects on raindrop size distributions near convective updrafts. One striking example is the lofting of liquid drops and partially frozen hydrometeors above the environmental 0°C level, resulting in a small columnar region of positive differential reflectivity Z DR in polarimetric radar data, known as the Z DR column. This signature can serve as a proxy for updraft location and strength, offering operational forecasters a tool for monitoring convective trends. Beneath the 0°C level, where WSR-88D spatiotemporal resolution is highest, anomalously high Z DR collocated with lower reflectivity factor at horizontal polarization Z H is often observed within and beneath convective updrafts. Here, size sorting creates a deficit in small drops, while relatively large drops and melting hydrometeors are present in low concentrations. As such, this unique raindrop size distribution and its related polarimetric signature can indicate updraft location sooner and more frequently than the detection of a Z DR column. This paper introduces a novel algorithm that capitalizes on the improved radar coverage at lower levels and automates the detection of this size sorting signature. At the algorithm core, unique Z H – Z DR relationships are created for each radar elevation scan, and positive Z DR outliers (often indicative of size sorting) are identified. Algorithm design, examples, performance, strengths and limitations, and future development are discussed.

Radar data in some frontal systems passing over the Sierra Nevada of California show large variance on scales of ~10 km. The most prominent features are a few kilometers in scale and are similar to small-scale precipitation cells embedded in fronts seen over other mountain ranges. Other frontal systems crossing the Sierras are characterized by more uniform air motions. Updrafts in large-variance storms have characteristics of shear-induced turbulence, although buoyant instability may also contribute. Large-variance storms occur under stronger upstream winds and vertically integrated cross- and along-barrier moisture fluxes. Rain gauges indicate that large-variance storms have precipitation greater than smaller-variance storms. Stronger horizontal moisture fluxes may provide greater mean upslope condensation rates; however, it is hypothesized that accelerated microphysical processes are needed to most efficiently convert the condensate into precipitation that falls out on the lower slopes before being carried downstream. Radar data indicate that the turbulence embodied in the cellular motions of the large-variance cases is consistent with microphysical enhancement resulting from updraft elements producing pockets of liquid water conducive to riming and coalescence. In addition, radar spectrum-width data show that the cells contain strong subcell-scale turbulence conducive to particle collisions and aggregation. Polarimetric radar data just below the 0°C level show large raindrops in the cells, consistent with aggregation occurring in cells just above the melting layer. It is hypothesized that such enhanced microphysical processes in large-variance cases hasten the growth and fallout in the regions of maximum condensation over the windward slopes.