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Rare earth resource recycling is an important endeavor for environmental protection and resource utilization. This study explores the method of preparing regenerated magnets using waste magnets as raw materials based on existing processes. By utilizing existing Nd-Fe-B production equipment, various waste magnets are transformed into recycled powder. Next, nascent Nd-Fe-B powders with slightly higher rare earth content are selected as the repairing agent. The regenerated magnets are prepared by incorporating the nascent powder into the recycled powder. The focus lies in investigating the repairing effect of the nascent powder repairing agent on the microstructure of regenerated magnets and exploring the influence of sintering temperature and powder addition on the magnetic properties and microstructure of the regenerated magnets. The results showed that the nascent powder increased the proportion of grain boundary phases and effectively repaired the grain boundary structure of the regenerated magnets. In addition, the Pr element in the nascent powder replaces the Ce element in the recycled powder, which ultimately improves the magnetic properties of the regenerated magnet in a comprehensive manner. This study provides valuable insights and guidance for rare earth resource recycling and the preparation of regenerated magnets. [ABSTRACT FROM AUTHOR]

Atmospheric turbulence parameters, such as turbulent kinetic energy and dissipation rate, are of great significance in weather prediction, meteorological disasters, and forecasting. Due to the lack of ideal direct detection methods, traditional structure function methods are mainly based on Kolmogorov's assumption of local isotropic turbulence and the well-known -5/3 power law within the inertial subrange, which limits their application. Here, we propose a method for directly measuring atmospheric turbulence parameters using coherent Doppler wind lidar, which can directly obtain atmospheric turbulence parameters and vertical structural features, breaking the limitations of traditional methods. The first published spatiotemporal distribution map of the power-law exponent of the inertial subrange is provided in this study, which indicates the heterogeneity of atmospheric turbulence at different altitudes and also indicates that the power-law exponent at high altitudes does not fully comply with the -5/3 power law, proving the superiority of our method. We analyze the results under different weather conditions, indicating that the method still holds. The turbulent kinetic energy and power-law index obtained by this method are continuously compared with the results obtained with an ultrasonic anemometer for a month-long period. The results of the two have high consistency and correlation, verifying the accuracy and applicability of the proposed method. The proposed method has great significance in studying the vertical structural characteristics of atmospheric turbulence. [ABSTRACT FROM AUTHOR]

The height of the stable boundary layer is a key parameter in atmospheric transmission and diffusion, air quality, emergency response, wind energy, and numerical weather prediction models. Existing methods mainly determine the stable boundary layer height via a threshold or minimum value of the wind speed variance under a low-level jet. Based on multi-meteorological element data from a meteorological gradient observation tower, this paper revealed the limitations of existing methods from the perspective of dynamic and thermal effects. In this paper, it is demonstrated that there were four types of shapes of the wind speed variance profile under the low-level jet and a method for using the shape of the variance profile to retrieve the height of the stable boundary layer was proposed. This method distinguished different types of wind speed variance profiles and solved the problems of the misjudgment and omissions (about 34%) present in existing methods. Our experiment showed that the average absolute error of the proposed method was less than 18 m and the average relative error was less than 9%. The results showed that the proposed inversion method was extended to all kinds of wind field detection equipment for inversion of the stable boundary layer height and has very high universality. [ABSTRACT FROM AUTHOR]

The range of detection and accuracy of currently available Raman temperature LiDAR systems are primarily improved by increasing the energy or the aperture of the receiving telescope. However, this does not lead to a corresponding linear increase in the distance of detection and accuracy of the system. In this paper, the authors construct a simulation model and optimize its parameters to develop a Raman temperature LiDAR with low energy and a small aperture that has a maximum distance of detection of over 5 km during the day and over 10 km at night. The profile of the atmospheric temperature obtained through field tests was in good agreement with the results of a radiosonde. The maximum correlation between the Raman temperature LiDAR and the radiosonde was 0.94 at night and 0.81 during the day. The results showed that the proposed Raman temperature LiDAR, with low energy and a small aperture, can provide reliable data on the temperature in the troposphere throughout the day. [ABSTRACT FROM AUTHOR]

It is well-known that coastal low-level jets (CLLJs) play an essential role in transporting heat, water vapor and pollutants. However, the CLLJ characteristics in the Pearl River Estuary have not been deeply revealed due to the lack of long-term observations. Based on the long-term observations from a wind lidar, we analyze the primary climatic characteristics of the CLLJs in the Pearl River Estuary and investigate their relationships with large-scale and local-scale synoptic systems. The results show that the CLLJs mainly appear during the flood season, with the most occurrence in May. The CLLJ occurrence during the flood season is mainly influenced by the large-scale north–south pressure gradient driven by the western Pacific subtropical high and terrestrial low-pressure systems. The occurrence of the CLLJs exhibits a distinct diurnal cycle with two different peaks in different seasons. One peak appears at nighttime, mainly during non-flood seasons. The other appears in the afternoon, mainly during the flood season. In the non-flood seasons, under the influence of cold air, the inertial oscillations triggered by the land–sea thermal contrast lead to CLLJ onset at nighttime in the Pearl River Estuary. During the flood season, the strong near-surface pressure gradient contributes to CLLJ onset in the afternoon, while the topography (blocking and passing) is more conducive to the occurrence of the CLLJs in the Pearl River Estuary. These findings reveal the formation mechanisms of the CLLJs over the Pearl River Estuary, thus providing a basis for further understanding the precipitation in the Pearl River Estuary and the occurrence of the CLLJs in other coastal areas with complex mountain ranges. [ABSTRACT FROM AUTHOR]

The impacts of weather forecast uncertainties have not been quantified in current air quality forecasting systems. To address this, we developed an efficient 2‐D convolutional neural network‐surface ozone ensemble forecast (2DCNN‐SOEF) system using 2‐D convolutional neural network and weather ensemble forecasts, and we applied the system to 216‐hr ozone forecasts in Shenzhen, China. The 2DCNN‐SOEF demonstrated comparable performance to current operating forecast systems and met the air quality level forecast accuracies required by the Chinese authorities up to 144‐hr lead time. Uncertainties in weather forecasts contributed 38%–54% of the ozone forecast errors at 24‐hr lead time and beyond. The 2DCNN‐SOEF enabled an "ozone exceedance probability" metric, which better represented the risks of air pollution given the range of possible weather outcomes. Our ensemble forecast framework can be extended to operationally forecast other meteorology‐dependent environmental risks globally, making it a valuable tool for environmental management. Plain Language Summary: Weather forecasts are intrinsically uncertain, but the impacts of that uncertainty on air quality forecasts are not explicitly quantified in current air quality forecast systems. We proposed here a surface ozone ensemble forecast system, analogous to modern weather ensemble forecast systems, to represent the probability distribution of forecasted surface ozone concentrations given 30–50 possible future weather outcomes. The computation costs of this surface ozone ensemble forecast system were greatly reduced using deep learning techniques that emphasized the spatial patterns of weather. We showed that the surface ozone ensemble forecast system's accuracy met the Chinese operational requirements. However, half of the ozone forecast error was due to weather forecast uncertainties, which cannot be completely eliminated even with perfect pollutant emission estimates and chemistry models. This weather‐induced innate uncertainty in air quality forecasts should be considered for effective air quality management. Key Points: We built a deep‐learning surface ozone ensemble forecast system to quantify pollution risks given the range of possible weather outcomesDeep‐learning models accentuating the spatial patterns of weather effectively represented the ozone‐meteorology relationshipWeather forecast uncertainties contributed 38%–54% of the ozone forecast errors at 24‐hr lead time in Shenzhen [ABSTRACT FROM AUTHOR]

Under the background of global climate change, typhoons have been attracting increasing attention due to their extraordinary destructive potential and great impact on the coastal areas of the South China Sea. Although the risk of strong winds related to typhoons has long been of interest, less is known about the underlying mechanism responsible for the severe near‐surface winds. Using eddy covariance data collected at four different heights on a 365‐m meteorological tower located in a coastal region, the characteristics of the convective typhoon boundary layer and the associated turbulence structures are compared with their counterparts in the "textbook" dynamically unstable boundary layer. In the convective typhoon boundary layer, bulk wind shear predominates the generation of mechanical turbulence, enhancing the vertical correlation between vertical layers. The spectral analysis highlights the salient features of turbulent structures under the convective typhoon boundary layer, confirming that the gust disturbance with the nondimensional frequency ranging from 0.003 to 0.3 modulates not only turbulent transports but also the horizontal flow. Such gusts with reduced phase difference enhance the downward momentum transport, mainly responsible for the maintenance of the strong near‐surface winds during typhoon landfalls. Plain Language Summary: Along the China coast, the Pearl River Delta (PRD) region is situated in the most active global typhoon basin. Therefore, a comprehensive understanding of the mechanism responsible for maintaining extreme near‐surface winds during typhoon landfalls is indispensable for risk management. In this study, the characteristics of turbulence in the typhoon boundary layer are analyzed and compared to the counterpart in the general boundary layer in which wind shear dominates the turbulence generation. The results show that the gust plays a predominant role in the vertical transport of momentum in the typhoon boundary layer, resulting in the maintenance of strong near‐surface winds during typhoon landfalls. Key Points: The convective typhoon boundary layer and dynamically unstable boundary layer are compared using observations from a 365‐m towerTurbulent structures during typhoon landfalls deviate from their counterparts in the dynamically unstable boundary layerThe strong near‐surface wind is attributed to the enhanced downward momentum transport related to the gusts with minimized phase difference [ABSTRACT FROM AUTHOR]

The goal of the paper is to reveal discrepancies of turbulent variables over different surfaces (sea, island, land) based on the measurements taken on three towers during (including before and after) seven typhoon episodes from 2008 to 2018. The atmospheric stability, turbulent spectrum, friction velocity, turbulent kinetic energy, dissipative heating, and gust factor are examined. The similar turbulent characteristics over sea and on the island reinforce the previous conclusion that the turbulent measurements on the island mainly represent the sea surface. The turbulent characteristics over sea and on land are very different due to the different underlying surface roughness. The unstable (stable) condition dominates on the sea (land) surface. Turbulent spectra both over sea and on land follow the canonical Kolmogorov's power law with the −5/3 slope. The cospectra on land are more peaked than those over sea. All of the friction velocity, turbulent kinetic energy, and dissipative heating increase with increasing 10 m wind speed, and those on land are much larger than those over sea. The distributions of gust factors widen and shift to higher on land than those over sea. The distributions of gust factors at heights of 10 m and 40 m are biased to higher values than those at heights of 160 m and 320 m on land. [ABSTRACT FROM AUTHOR]

Based on the meteorological, ozone (O3), and vertical observation data of 2020, this study sought to evaluate the daily variation in O3, particularly the characteristics of nocturnal ozone pollution. We also discuss the effect of local and mesoscale horizontal transport and vertical mixing on the formation of nocturnal O3 pollution. Distinct seasonal characteristics of the daily O3 variation in Shenzhen were identified. In particular, significant nocturnal peaks were found to regularly occur in the winter and spring (November–December and January–April). The monthly average of daily variation had a clear bimodal distribution. During the period, O3 pollution frequently occurred at night, with the maximum hourly O3 concentration reaching 203.5 μg/m3. Nocturnal O3 pollution was closely associated with horizontal transport and vertical mixing. During the study period, the O3 maximum values were recorded on 68 nights, primarily between 23:00 and 03:00, with occasional observation of two peaks. The impact of horizontal transport and vertical mixing on the nocturnal secondary O3 maximum values was elaborated in two case studies, where vertical mixing was mainly associated with low-level jets, with strong wind shear enhancing turbulent mixing and transporting O3 from the upper layers to the surface. [ABSTRACT FROM AUTHOR]

Black carbon (BC) is an essential climate forcer in the atmosphere. Large uncertainties remain in BC's radiative forcing estimation by models, partially due to the limited measurements of BC vertical distributions near the surface layer. We conducted time-resolved vertical profiling of BC using a 356-m meteorological tower in Shenzhen, China. Five micro-aethalometers were deployed at different heights (2, 50, 100, 200, and 350 m) to explore the temporal dynamics of BC vertical profile in the highly urbanized areas. During the observation period (December 6–15, 2017), the average equivalent BC (eBC) concentrations were 6.6 ± 3.6, 5.4 ± 3.3, 5.9 ± 2.8, 5.2 ± 1.8, and 4.9 ± 1.4 μg m−3, from 2 to 350 m, respectively. eBC temporal variations at different heights were well correlated. eBC concentrations generally decreased with height. At all five heights, eBC diurnal variations exhibited a bimodal pattern, with peaks appearing at 09:00–10:00 and 19:00–21:00. The magnitudes of these diurnal peaks decreased with height, and the decrease was more pronounced for the evening peak. eBC episodes were largely initiated by low wind speeds, implying that wind speed played a key role in the observed eBC concentrations. eBC wind-rose analysis suggested that elevated eBC events at different heights originate from different directions, which suggested contributions from local primary emission plumes. Air masses from central China exhibited much higher eBC levels than the other three backward trajectory clusters found herein. The absorption Ångström exponent (AAE375–880) showed clear diurnal variations at 350 m and increased slightly with height. [ABSTRACT FROM AUTHOR]

Multi-year observations of aerosol microphysical and optical properties, obtained through ground-based remote sensing at 50 China Aerosol Remote Sensing Network (CARSNET) sites, were used to characterize the aerosol climatology for representative remote, rural, and urban areas over China to assess effects on climate. The annual mean effective radii for total particles (ReffT) decreased from north to south and from rural to urban sites, and high total particle volumes were found at the urban sites. The aerosol optical depth at 440 nm (AOD 440nm) increased from remote and rural sites (0.12) to urban sites (0.79), and the extinction Ångström exponent (EAE 440–870 nm) increased from 0.71 at the arid and semi-arid sites to 1.15 at the urban sites, presumably due to anthropogenic emissions. Single-scattering albedo (SSA 440nm) ranged from 0.88 to 0.92, indicating slightly to strongly absorbing aerosols. Absorption AOD 440nm values were 0.01 at the remote sites versus 0.07 at the urban sites. The average direct aerosol radiative effect (DARE) at the bottom of atmosphere increased from the sites in the remote areas (-24.4 0 W m -2) to the urban areas (-103.28 W m -2), indicating increased cooling at the latter. The DARE for the top of the atmosphere increased from -4.79 W m -2 at the remote sites to -30.05 W m -2 at the urban sites, indicating overall cooling effects for the Earth–atmosphere system. A classification method based on SSA 440nm , fine-mode fraction (FMF), and EAE 440–870nm showed that coarse-mode particles (mainly dust) were dominant at the rural sites near the northwestern deserts, while light-absorbing, fine-mode particles were important at most urban sites. This study will be important for understanding aerosol climate effects and regional environmental pollution, and the results will provide useful information for satellite validation and the improvement of climate modelling. [ABSTRACT FROM AUTHOR]

Abstract: In this study, a lightning data assimilation method based on the time‐lagged ensembles for predicting severe convection is presented. With the lightning data assimilation scheme, the background error covariances are computed using time‐lagged ensembles, which consist of deterministic forecasts from eight forecast cycles initialized every 3 hr. Pseudo‐observations of graupel mixing ratio (qg) are retrieved from total lightning rates by utilizing empirical vertical profiles obtained from the simulation results of the previous forecast cycles, and the corresponding observation errors are estimated according to the uncertainties in the lightning observations and the empirical vertical profiles of qg. The increments of the model state variables are computed with the Kalman gain matrices and are continuously ingested into the Weather Research and Forecasting model via nudging terms acting on the prognostic equations over each time step during model integration. The effect of the lightning data assimilation scheme on convection analysis and forecast was assessed through a case study of a severe convective event, which took place in the Guangdong of China. Assimilating lightning data recovered many of the observed convective cells, suppressed the spurious convection, and corrected the displacement errors of the convective systems. Quantitative verifications indicate that forecast skills were improved mainly in the convective regions with the impact of assimilating lightning data on stratiform regions being overall less effective. [ABSTRACT FROM AUTHOR]

A number of squall line passages over the Pearl River Delta (PRD) are documented for the first time based on the wind data collected by a 356 m-high meteorological tower with high temporal resolution (10 Hz). The mean wind and turbulence characteristics are studied based on a sample of six cases. The mean wind profile is consistent with the international standard for wind engineering, but the turbulence intensity profile has quite significant deviations. Moreover, the energy spectrum of the fluctuating wind is found to be consistent with the −5/3 law, as expected in the inertial subrange. For the purpose of wind gust nowcasting, the performance of a nowcasting algorithm based on upper air wind and thermodynamic profiles is examined using the limited dataset. The results highlight that the mean wind gust estimates are sufficient to nowcast the surface wind gust as measured by the anemometers, but for an extreme squall line case, the maximum wind gust estimates would be useful. The information in this paper is believed to be useful for wind engineering applications and weather nowcasting for wind gusts associated with subtropical squall lines, and, to the best of the authors' knowledge, this is the first study of its kind for the PRD region. [ABSTRACT FROM AUTHOR]

The article reports that a tropospheric wind profiler was introduced to Xi Chong, Shenzhen, China in the year 2012. This profiler was used to obsersve the typhoon Usagi crossed Shenzhen in September 2013. It operates at a microwave frequency and measures the changes in refractivity associated with atmospheric discontinuities.