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Founded in 1973, Meteorological Science and Technology（Bimonthly, ISSN：1671—6345, CN 11—2374/P）is governed by China Meteorological Administration, and jointly sponsored by CMA Meteorological Observation Centre, Chinese Academy of Meteorological Sciences, Beijing Meteorological Service, National Satellite Meteorological Center and National Meteorological Information Centre. As a comprehensive technical journal with engineering features, Meteorological Science and Technology aims to provide a platform for the exchange of knowledge, technology, and experience for scientific and technical personnel. The journal mainly publishes research articles that reflect new theories, methods, and technologies in atmospheric science and related sciences. Main columns include Atmospheric Sounding and Information Technology; Weather & Climate and Numerical Forecasting; Applied Meteorology and Scientific Experiments, and Practical Techniques.

The journal is now indexed by China Science and Technology Journal Database, CNKI Digital Library, Wanfang Data. The journal is also a source journal of A Guide to the Core Journal of China (1992, 1996, 2000, 2008, 2014), China Academic Journal CD-ROM, and Chinese Scientific and Technical Papers and Citations.

Meteorological Science and Technology is an A4-size journal published bimonthly with worldwide distribution. The annual subscription fee is 120 CNY. Readers can subscribe anytime throughout the year. Researchers, professionals, and lecturers engaged in atmospheric science and related disciplines are welcome to submit articles and subscribe to the journal.

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    2025,53(5):617-633, DOI: 10.19517/j.1671-6345.20250025
    Abstract:
    Accurate nowcasting provides key information for disaster weather warning and artificial weather operations. Nowcasting is mostly based on radar echo extrapolation, where the evolution of echoes results from complex interactions among cloud systems and various thermal-dynamic features of meteorological elements. In this study, a multi-channel radar echo extrapolation architecture (UGR) based on UNet and GAN with Radarcells is proposed, and a self-defined loss function combining weighted mean square error and binary cross-entropy is designed by introducing a penalty term in the GAN network to improve model training. Four sets of radar units (Radarcells) are encoded using radar combined reflectivity mosaic data and four types of physical elements acquired from the Beijing rapid updating circular numerical forecasting system (CMA-BJ). Then, 20 UGR-based models are trained with the Radarcells as inputs for sequential forecasting every six minutes to achieve a rolling 120-minute echo extrapolation. To verify the improvement effect after introducing weather background on echo extrapolation, UNet-based models and ConvLSTM-based models that use only radar echoes as input are trained for comparison, respectively. Critical Success Index (CSI), Probability of Detection (POD), False Alarm Rate (FAR), and Bias score (Bias) are used to evaluate the model on the test set. The results show that the echo intensity range and spatiotemporal evolution predicted by UGR-based models incorporating weather background information perform better than the UNet-based and ConvLSTM-based models driven solely by radar data, especially in predicting strong echoes more accurately. Under the reflectivity thresholds of 25 and 35 dBz, the average values of CSI, FAR, POD, and Bias calculated by UGR-based models are improveed by 10.5%, 8.6%, 10.3%, 4.8%, and 13.4%, 4.6%, 11.0%, and 7.4%, respectively, compared to those by UNet-based models. The study suggests that extrapolation models incorporating weather background information can effectively improve issues of echo blurriness and insufficient echo formation-dissipation compared with previous deep learning-based extrapolation models.
    2025,53(5):634-645, DOI: 10.19517/j.1671-6345.20250002
    Abstract:
    Polarimetric technology gradually becomes widespread in operational weather radars in China. In addition to conventional radar parameters such as reflectivity factor, Doppler velocity, and spectrum width, polarimetric weather radars also obtain dual-polarisation parameters such as differential reflectivity, differential phase, and correlation coefficient, which further expand the application range of weather radar data. Compared to conventional radar parameters, dual-polarisation parameters are more susceptible to ground clutter, requiring higher performance from ground clutter suppression algorithms. Operational weather radars currently use CMD (Clutter Mitigation Decision) and GMAP (Gaussian Model Adaptive Processing) algorithms for ground clutter identification and filtering. However, existing research indicates that these operational algorithms have insufficient ground clutter suppression capabilities, resulting in lower data quality for dual-polarisation parameters such as correlation coefficients, which affects the performance of radar products such as hydrometeor classification and melting layer identification. This paper proposes a ground clutter suppression algorithm for polarimetric weather radars, improving the existing operational algorithms in terms of ground clutter identification and filtering. For ground clutter identification, the CMD algorithm is initially executed. Based on its preliminary identification results, additional steps such as the correlation coefficient test are added for secondary identification of ground clutter, improving identification performance under low clutter-to-signal ratio conditions. For ground clutter filtering, a time-domain regression filter is used to replace the frequency-domain GMAP algorithm, avoiding the sampling information loss caused by windowing in GMAP. This ensures that ground clutter suppression no longer affects the accuracy of parameter estimation. The algorithm’s ground clutter suppression performance is evaluated based on eight precipitation events (one snowfall and seven rainfalls) observed by the S-band standard weather radar at the Changsha Meteorological Radar Calibration Centre. To quantify the performance of the ground clutter suppression algorithm, a data quality assessment metric based on correlation coefficient, differential reflectivity texture, and differential phase texture is proposed, named High-Quality Polarimetric Data Ratio (HPR). This metric characterises the extent to which dual-polarisation parameter data quality is affected by ground clutter. It is defined as the ratio of the number of range bins where the correlation coefficient, differential reflectivity texture, and differential phase texture meet specific thresholds to the total number of effective range bins, under conditions where meteorological echoes cover ground clutter within a certain distance from the radar. Evaluation results indicate that the algorithm significantly improves ground clutter suppression under low clutter-to-signal ratio conditions compared to existing operational algorithms, with an HPR value increase of about 0.4. This means that the usability of dual-polarisation parameters within a 100 km range of the radar increases by approximately 40%. Next, a more in-depth evaluation of the algorithm continues, along with the initiation of its trial operation in practical applications.
    2025,53(5):646-655, DOI: 10.19517/j.1671-6345.20250072
    Abstract:
    Radar meteorological algorithms play a crucial role in meteorological monitoring and forecasting, and their rapid deployment and application in operational systems significantly improve radar data quality and operational efficiency. To improve the data quality of weather radar and the effectiveness of localised applications, this study relies on the open interface architecture of the new generation weather radar operational software (ROSE 3.0) to carry out localised design and system integration research of radar meteorological algorithm modules. At first, the open interface functionality, modular development process, and integration methods of ROSE 3.0 are introduced in detail. Subsequently, taking the radar data quality control algorithm as the research object, a non-meteorological echo recognition model for dual-polarisation radar is developed using the fuzzy logic method. Key radar parameters such as radial velocity, differential reflectivity texture, correlation coefficient, and differential phase shift texture are utilised to implement the radar data quality control algorithm through the ROSE 3.0 standard API function and dynamic link library. Then, this radar data quality control algorithm is successfully deployed in the ROSE 3.0 operational systems of Suizhou and Jingzhou radar stations in Hubei Province. Using two radar observation cases from Suizhou and Jingzhou radar stations for operational tests, it is shown that the radar data quality control algorithm robustly and efficiently identifies and eliminates non-meteorological echoes such as ground clutter, biological targets, and aluminium foil interference, while the precipitation echoes experience no loss. By comparing and analysing the radar reflectivity factors before and after quality control, a significant improvement in the quality and reliability of radar data is found, which enhances the operational efficiency of precipitation monitoring and short-term forecasting systems. Additionally, the results of this study also validate the significant advantages of ROSE 3.0 in supporting rapid algorithm integration, flexible expansion, and business transformation, effectively promoting the localised deployment of radar meteorological algorithms. It should be pointed out that this study mainly focuses on the interface mechanism and integration process of ROSE 3.0. The effectiveness of radar data quality control is mainly analysed through case studies, and there is a lack of systematic analysis on the accuracy evaluation and localisation optimisation strategies of radar data quality control algorithms. In future research, it is necessary to continuously improve the accuracy evaluation of weather radar quality control algorithms and further expand ROSE 3.0 functionality to support multiple data formats and more complex meteorological processing techniques, in order to better serve the new needs of meteorological operational development.
    2025,53(5):656-667, DOI: 10.19517/j.1671-6345.20240387
    Abstract:
    With the continuous increase in the demand for refined meteorological forecasting, high-resolution numerical models make progress in the forecasting capability of extreme precipitation events. However, limited by factors such as errors in the initial field of the model, parameterisation uncertainties, and terrain, there are still systematic bias problems in precipitation forecasting. The convective-scale numerical model in Guangxi (GX(R1)) faces the technical bottleneck of urgently needing to improve the accuracy in short-term strong precipitation forecasting. In response to this issue, this study proposes a deep learning method based on multi-source data fusion, the MResUNet model. This model achieves performance breakthroughs through three technical improvements: first, the squeeze-and-excitation (SE) module is introduced to construct a channel attention mechanism, dynamically adjust feature weights, and suppress noise interference in the model output; second, the atrous spatial pyramid pooling (ASPP) module is integrated to fuse multi-scale features and improve the positioning accuracy of precipitation areas; third, a multi-modal data fusion framework is constructed to integrate the advantages of convective-scale numerical forecasting products in Guangxi, radar echo data, ground observation data, and the ResUNet++ model. The weighted loss function is optimised, and different weights are assigned to different precipitation intensities according to the measured rainfall data at stations, significantly enhancing the model’s sensitivity to extreme precipitation events. To verify the effectiveness of the MResUNet model, four sets of control experiments are designed: Scheme 1 retains the original output of the GX(R1) model as the benchmark; Scheme 2 uses the input containing only numerical model products (X1, X2); Scheme 3 uses only radar echo data (X3); Scheme 4 fuses the model products and radar echo data and implements a multi-source data fusion strategy. The experimental results show that all MResUNet schemes are significantly better than the original model output, and the TS (Threat Score) scores exhibit positive skill characteristics. In particular, for Scheme 4, under the thresholds of strong precipitation of ≥20 mm/h and ≥30 mm/h, the TS scores increase by 9.77% and 8.98%, respectively. It shows significant advantages in reducing the false alarm rate. The hit rate at the precipitation level of ≥30 mm is higher than that of Scheme 3 and much higher than that of Scheme 2, with an increase of 5.45% and 177%, respectively, and the prediction bias is the closest to the ideal value of 1. Further, the extreme precipitation event of “Dragon Boat Water” in Guangxi in 2023 and typical typhoon precipitation processes are selected for case verification. The analysis shows that the MResUNet effectively solves the problem of dispersed prediction of the strong precipitation centre in the GX(R1) model and demonstrates excellent prediction capabilities in both the magnitude of precipitation intensity and the location of precipitation areas. This study proves that by deeply integrating multi-source observational data and numerical model products and optimising the architecture of the deep learning model, the forecasting accuracy of different precipitation magnitudes can be significantly improved. In particular, the scheme based on multi-source data fusion shows obvious advantages in strong precipitation forecasting. The research results provide a new technical approach to solve the technical problems in short-term precipitation forecasting.
    2025,53(5):668-680, DOI: 10.19517/j.1671-6345.20250016
    Abstract:
    The historical hindcast data of different starting dates provided by the second-generation climate forecasting system (NCEP CFSv2) of the United States Environmental Forecasting Centre are used to predict the wind, temperature, and height during the two strong freezing processes in 2008 and 2011. Through comparative analysis with the actual field, the predictive ability of the CFSv2 model for severe freezing processes is evaluated. The results show that at the different starting dates within one week in advance, the NCEP CFSv2 model has a certain ability to predict the wind field characteristics of the two processes (at 850 hPa: northeasterly return flow in the northeastern part of Guizhou, southerly wind in south Guizhou, southwest wind in west Guizhou; 700 hPa southwest jet stream), temperature field characteristics (the 0 ℃ line position of 850 hPa,700 hPa and whole layer temperature field; temperature gradient of middle and low layers; temperature inversion zone of 850 hPa and 700 hPa), and height field characteristics (the variation of the 500 hPa 564 dagpm characteristic line, the subtropical westerly jet stream). However, there are deviations in the forecast of wind speed at 850 hPa, the position of the South China quasi-stationary front, the north-south position of the 0 ℃ line on the entire layer temperature field, the north-south position of the 564 dagpm characteristic line, and the intensity of the subtropical westerly jet stream. At the same time, there are situations such as the wind speed of the 700 hPa southwest jet stream being relatively small, the temperature gradient of the 850 hPa temperature field being relatively small, the 0 ℃ line position of the 700 hPa temperature field being relatively south, the intensity of the inversion zone being relatively weak and the area being relatively small, and the temperature intensity of the middle and upper layers being relatively strong. Moreover, there is basically no predictive ability for the warm-core structure of the entire floor temperature field. From the prediction effect of different starting dates, the prediction effect of 1 d in advance is obviously better than that of 4 d and 7 d in advance.
    2025,53(5):681-690, DOI: 10.19517/j.1671-6345.20250029
    Abstract:
    To investigate the spatiotemporal distribution characteristics of Convective Initiation (CI) during the warm season (May-September) over the North China region, this study utilises composite reflectivity mosaic data from regional radar networks across North China for the warm seasons spanning 2022 to 2024. An objective identification algorithm specifically designed to detect “isolated” CI events is developed. Leveraging this algorithm, a comprehensive CI database for North China is subsequently constructed. Detailed statistical analyses are then performed on this database to elucidate both the temporal and spatial patterns of CI occurrence within the region. The principal findings derived from this research are summarised as follows: (1) Sensitivity experiments focus on two key parameters within the objective CI identification algorithm: the lower threshold for convective cell area (A) and the screening radius (R). The results demonstrate a significant sensitivity in the number of identified CI events to variations in these parameters. Specifically, setting a larger threshold value for the minimum convective cell area (A) effectively filters out nascent convective cells that fail to develop further. Conversely, employing a larger screening radius (R) aids in filtering out newly initiated convective cells occurring in close proximity to pre-existing, already identified convective cells, thereby refining the detection to focus on truly isolated initiation events. (2) The temporal distribution of CI events during the warm season in North China exhibits distinct patterns. Monthly analysis reveals that the highest frequency of CI occurrences is concentrated in July and August, while May registers the lowest number. Diurnally, CI events display a pronounced unimodal structure, with a clear peak in activity observed between 13:00 and 17:00. (3) Spatially, CI events during the warm season in North China show a highly heterogeneous distribution. High-frequency CI zones are predominantly concentrated along major mountain ranges and their foothills. These include the Yinshan Mountains in Inner Mongolia, the northern Yanshan Mountains near Beijing, the Lvliang Mountains on the western flank of Shanxi Province; the Taihang Mountains along the eastern border of Shanxi Province, the Zhongtiao Mountains in southern Shanxi, the eastern extensions of the Qinling Mountains in Henan Province, and the western and northern flanks of the Taiyi Mountains in Shandong Province. Notably, exceptionally high CI frequency zones are identified within the southern segment of the Taihang Mountains (eastern Shanxi) and the eastern Qinling Mountain extensions in Henan. Conversely, regions exhibiting significantly lower CI frequency encompass the Inner Mongolia Plateau, the Hetao Plateau, the basins situated between the mountain ranges flanking Shanxi Province, and the expansive North China Plain. This clear spatial dichotomy underscores that CI hotspots are overwhelmingly associated with mountainous terrain, while CI-sparse areas predominantly coincide with relatively flat plateaus, basins, and plains. These research findings, detailing the objective identification methodology and the resulting spatiotemporal climatology of CI over North China, provide valuable insights and offer a substantive reference for enhancing CI potential forecasting and nowcasting capabilities in the region.
    2025,53(5):691-705, DOI: 10.19517/j.1671-6345.20240378
    Abstract:
    On the morning of August 26, 2017, an extreme convective heavy rainfall event occurred in the main urban area of Hangzhou, with a maximum hourly precipitation rate reaching 127.0 mm, breaking the historical record for hourly rainfall in the region. Both mesoscale regional models and global large-scale numerical models failed to forecast this extreme rainfall event. This study utilises conventional observational data, high-resolution surface observations, weather radar data, and NCEP/GFS 0.25°×0.25° 3-hourly analysis fields to investigate the synoptic background, physical parameter fields, and the development mechanisms of meso- and micro-scale systems during this event. The main findings are as follows. (1) Synoptic Background and Large-Scale Conditions: The rainfall event occurred under the influence of the western Pacific subtropical high (WPSH). At the 500 hPa level, Hangzhou was located near the ridge line of the WPSH, while in the lower troposphere and at the surface, it was situated within a saddle-shaped pressure field. This configuration resulted in weak steering flows, and the saddle-shaped structure restricted the movement of weather systems, allowing slow-moving or quasi-stationary mesoscale convective systems (MCSs) to persist, which was highly favourable for heavy rainfall. (2) Favourable Thermodynamic and Moisture Conditions: The environmental conditions exhibited strong convective instability, with a low lifting condensation level (LCL) and a deep warm cloud layer, enhancing precipitation efficiency. The boundary layer was nearly saturated, and extreme values were observed in parameters such as precipitable water (PWAT) and surface dew point temperature. Additionally, weak vertical wind shear in the environment contributed to high precipitation efficiency by allowing convective updrafts to remain vertically aligned without significant disruption. (3) Boundary Layer Convergence and Dynamic Lifting Mechanisms: The northeasterly flow at the base of a surface high-pressure system intensified and was obstructed by local topography, leading to cyclonic convergence and wind speed convergence in the boundary layer over Hangzhou and northern Shaoxing. A convergence line formed 3 hours before precipitation initiation and persisted for an extended period, providing sustained dynamic lifting for convective triggering and development. (4) Low-Level Jet and Moisture Transport: A boundary-layer easterly ultra-low-level jet (ULLJ) combined with southeasterly warm and moist flows at 850 hPa provided continuous moisture transport and energy supply, sustaining the convection and contributing to the extreme rainfall intensity. (5) Quasi-Stationary MCS: The generation, merging, and intersection of convective cells, along with the parallel but opposite directions of advection and propagation, caused the MCS to remain nearly stationary. This led to multiple heavy rainfall cores overlapping in the same region, which was a crucial factor in the extreme precipitation accumulation.
    2025,53(5):706-718, DOI: 10.19517/j.1671-6345.20240360
    Abstract:
    Using the data from ground automatic stations, the Kuihua 8 satellite, radiosonde, wind profile radar, microwave radiometer, automatic observation system minute-by-minute observation, and ERA5 reanalysis, the generation and dissipation mechanism of a thick fog process on 6 March 2024 along the coast of southern Fujian and Xiamen Airport is analysed. The results show that during the formation of the fog, the surface was under a weak pressure field ahead of the cold front, with unified southwest warm and moist air currents prevailing in the middle and lower atmospheric levels. The heavy fog first appeared on the eastern sea surface, and there was a cold water zone in the Taiwan Strait. At 1000 hPa, there was strong warm advection in the Taiwan Strait, which was superimposed on the cold water zone to produce advection cooling fog. The temperature difference between the sea and air near the sea was between 0 and 3.2 ℃. After its formation, the sea fog spread westward to the land at night, showing a good spatiotemporal coupling relationship with the westward advance of the 1000 hPa warm advection. The formation of a nocturnal surface inversion and the increase in the thickness of the weak wind layer provided stable stratification conditions for the generation and development of the fog, while the long-term water vapour saturation at the surface provided sufficient moisture conditions for the generation and development of the fog. High-resolution satellite data monitored the evolutionary process where the sea fog spread from Kinmen and Xiang’an to Xiamen Airport at night, after which the fog in Xiamen Airport and its nearby small area dissipated while the sea fog persisted. Xiamen Airport experienced heavy fog from 03:22 to 04:47 (Beijing Time) on the 6th, lasting approximately 1.5 hours. With rapid onset and dissipation, it was classified as an explosive heavy fog event. The short-term sudden changes in surface wind direction and the sudden increase in wind speed at Xiamen Airport enhanced the local cold advection transport, introducing cold air from Tong’an Bay on the northeast side into the airport, accelerating the condensation of water vapour in the near-surface layer of the airport, which was an important thermal factor for the explosive formation of the heavy fog. The enhanced long-wave radiation before the fog was another thermal cooling factor. Analysis shows that the diffusion of the fog mass in Tong’an Bay combined with the “trumpet-shaped” terrain caused passive adjustment of the wind direction at the airport, and the propagation of fluctuations from the upstream cold air southward led to short-term changes in the wind at Xiamen Airport.
    2025,53(5):719-737, DOI: 10.19517/j.1671-6345.20250015
    Abstract:
    This study systematically investigates the microphysical characteristics of warm-season precipitation over northern Zhejiang Province, China, based on comprehensive observations from six laser precipitation monitors (LPMs) and two S-band dual-polarisation weather radars (HZ-SPOL and JX-SPOL) collected between March and October 2022. In addition, the performance of dual-polarisation radar retrievals of raindrop size distribution (DSD) parameters, specifically the mass-weighted mean diameter (D0) and the normalised intercept parameter (Nw) of the gamma distribution, is quantitatively evaluated. The results reveal the following: (1) Precipitation in the northern Zhejiang region is predominantly characterised by high concentrations of small raindrops, with an average D0 of 1.0 mm and a mean Nw of 104.3m-3·mm-1, exhibiting typical features of warm-cloud precipitation. A classification approach based on the statistical properties (mean and standard deviation) of rainfall rate effectively discriminates between stratiform and convective precipitation. Stratiform precipitation shows relatively narrow DSDs and low spatial variability across sites, with low rainfall intensity (R<10 mm·h-1) and smaller drop sizes (D0 <1.0 mm). In contrast, convective precipitation exhibits significantly broader spectra, with D0 and average R values reaching up to 1.8 mm and 19 mm·h-1, respectively, and displays much greater spatial heterogeneity. Medium-sized raindrops (1.0-2.0 mm) contribute the largest fraction (33.4%) to total rainfall accumulation, while larger drops (D0 >2.5 mm), though relatively infrequent, still account for 10.3% of total rainfall volume. (2) Simulated polarimetric variables at S-band—reflectivity (Z), differential reflectivity (ZDR), and specific differential phase (Kdp)—calculated using a T-matrix scattering model based on local DSDs, show good agreement with actual radar observations, validating the applicability and robustness of the scattering model in the region. Retrieval relationships for D0 and Nw are established using the localised DSD dataset. Sensitivity analysis indicates that D0 is primarily influenced by ZDR, with a negligible bias of -0.005 mm, while Nw is influenced by both Z and ZDR and exhibits larger variability, with a mean bias of 0.029 m-3·mm-1. (3) Validation is carried out using six precipitation events observed at Changxing in 2023, comparing retrievals from two radars: Jiaxing (JX-SPOL) and Hangzhou (HZ-SPOL). The JX-SPOL retrievals of D0 show better agreement with LPM measurements, with a mean bias of 0.087 mm and RMSE of 0.418 mm, outperforming HZ-SPOL (bias -0.195 mm, RMSE 0.444 mm). For Nw, JX-SPOL yields a higher correlation coefficient (0.536) compared to HZ-SPOL (0.199), and the absolute deviation and RMSE (HZ-SPOL 1.046 m-3·mm-1 and JX-SPOL 0.819 m-3·mm-1) are relatively close, although systematic biases remain: JX-SPOL tends to underestimate by 0.395 m-3·mm-1, whereas HZ-SPOL overestimates by 0.494 m-3·mm-1. Overall, this study provides a scientific basis for improving dual-polarisation radar retrievals of precipitation microphysics in Zhejiang Province. The findings highlight the importance of localised DSD datasets in optimising retrieval algorithms and emphasise the need for further validation efforts using diverse precipitation events and multi-site observations to enhance the accuracy, stability, and generalisability of radar-based microphysical retrieval techniques.
    2025,53(5):738-751, DOI: 10.19517/j.1671-6345.20240379
    Abstract:
    The wind field has a significant impact on the spread speed, fire distribution and operational safety of forest and grassland fires. This study aims to explore the application value and practical effect of Doppler wind laser radar at the rescue site of forest and grassland fires. Based on the observation data of Doppler wind laser radar at the “3·15” forest fire rescue site in Yajiang, Sichuan, in 2024, this paper first verifies the accuracy of the three-dimensional wind field inversion using the three-dimensional variational method under complex terrain conditions with the multi-elevation plane position indicator (PPI) data of the scanning wind laser radar. On this basis, the wind field information observed at three fire points in Yajiang by the PPI scanning mode of the wind laser radar is used to conduct a preliminary analysis of the spread of the fire and the horizontal diffusion of smoke. At the same time, the vertical wind profile of the fire scene is retrieved through the Doppler beam swinging (DBS) mode data, and the vertical atmospheric motion of the fire scene is analysed in combination with the extinction coefficient. The results show that the vertical wind field retrieved by the DBS mode is used as the background field of the three-dimensional variational method. The three-dimensional wind field retrieved under complex terrain conditions has high accuracy, and the average deviations of wind speed and wind direction are -2.51% and 3.92%, respectively. The wind direction in the fire determines the direction of fire spread and smoke propagation. The vertical wind profile of the fire scene retrieved through the DBS mode captures the low-altitude jet and momentum transfer phenomenon that may cause sudden changes in fire intensity, and the vertical transport of smoke in the fire can be further analysed in combination with the extinction coefficient. The application of Doppler wind laser radar in wind field monitoring at the scene of forest and grassland fires is of great significance for improving the scientific level of command and management at the rescue site.
    2025,53(5):752-760, DOI: 10.19517/j.1671-6345.20250010
    Abstract:
    Foehn wind is a special meteorological phenomenon that occurs on the leeward side of mountains, often leading to a sudden increase in temperature, a decrease in water vapour, and an increase in wind speed. The zenith total delay (ZTD) of Global Navigation Satellite System (GNSS) signals can be used to retrieve atmospheric precipitable water vapour (PWV), which has significant application value in the field of meteorology. However, there is a lack of GNSS data analysis research focused on foehn wind processes in our country. This study analyses a typical foehn wind event based on automatic weather station (AWS) and GNSS observation data from Beijing and surrounding provinces and cities, examining the changes in meteorological elements during this process and the characteristics of GNSS water vapour. During the passage of the foehn wind, significant changes in meteorological elements were observed at the plain stations, with the influence of the foehn wind weakening as the distance from the mountainous area increased. In terms of GNSS water vapour characteristics, the passage of the foehn wind resulted in a reduction of water vapour, with changes in PWV being more pronounced than those in ZTD. Using the PWV/ZTD difference from stations at different elevation differences better reflected the characteristics of water vapour reduction caused by the foehn wind. This study suggests that the foehn wind had a significant impact on the meteorological elements and water vapour distribution in the Beijing plain area, and that GNSS data could effectively monitor the changes in water vapour during the foehn wind process. This research provides a reference for using GNSS data to conduct monitoring and related studies on foehn winds.
    2025,53(5):761-773, DOI: 10.19517/j.1671-6345.20240280
    Abstract:
    By integrating hail data collected from hail prevention sites, meteorological stations, and the China Meteorological Administration’s meteorological disaster management system, the spatiotemporal distribution characteristics of hail in Yunnan from 2012 to 2023 are statistically analysed, and the differences between them and the observation results of meteorological stations are explored to provide a basis for hail monitoring, forecasting, and scientific hail suppression. The results show that the annual average number of hail days and county days in Yunnan is 100.5 days and 324.0, with significant interannual differences and an increasing trend, with a yearly increase of 1.1 days and 6.3 county days. The seasonal characteristics of the two are prominent, with the highest values in summer, followed by spring, and significantly reduced in autumn and winter. The corresponding values are 46, 34.1, 10.8, and 9.6 days and 166.2, 110.4, 16.3, and 31.1 county days, respectively. The monthly variation can be classified into four types. The predominant pattern is dual-peak, with a primary peak in July-August and a secondary peak in March-April. The second pattern is single-peak in July-August for hail days but in March-April for hail county days, and the other patterns are single-peak in March-April for hail days but in July-August for hail county days, and both multi-peak. On average over the years, both exhibit a typical dual-peak pattern with a primary peak in July-August and a secondary peak in March-April. The daily variation of hail shows a single-peak pattern at 16:00, with hail concentrating between 13:00 and 19:00, particularly in summer and autumn. The horizontal spatial distribution of hail days is categorised into four types: scattered hail type, two band-shaped hail type, multiple hail type to the east and north of central Yunnan, and multiple hail type in southern and western Yunnan. On average over the years, the maximum number of hail days is from Qujing to Zhaotong (up to 11.8 days in Xuanwei), followed by the area from Yuxi to northern Honghe, then from Dali to Lijiang, and in Baoshan. However, there are significant differences in the seasonal and monthly horizontal distribution, with hail occurring in the western and southern regions during winter and spring, developing eastward from late spring to early summer, expanding towards the central region in summer, and retreating towards the west and south in autumn. On the vertical distribution, the number of hail days increases first and then decreases with altitude, with the most hails occurring at altitudes of 1.5-2.0 km. The number of hail days at low altitudes (0.0-1.0 km) is a single-peak pattern in April, a dual-peak pattern in April and July at mid-altitudes (1.0-2.0 km), and a single-peak pattern during July-August at high altitudes (≥2.0 km). At mid- and low altitudes, hail mainly occurs in spring, followed by summer, and least in autumn, and at mid- and high altitudes, hail mainly occurs in summer, followed by spring, and least in winter.
    2025,53(5):774-782, DOI: 10.19517/j.1671-6345.20250058
    Abstract:
    Transportation is a fundamental and service-oriented industry of the national economy, which is significantly influenced by weather and climate factors. Implementing traffic meteorological services effectively improves people’s quality of life and socio-economic benefits. In this study, based on the traffic congestion index and road automatic 〖JP2〗weather station observations from 15 November, 2022, to 14 November,〖JP〗 2024, in Beijing, the temporal characteristics of the traffic congestion index and its meteorological impact are investigated. Firstly, the concept of the meteorological congestion index is proposed, and then the traffic congestion index is decomposed to analyse the distribution characteristics of the total congestion index, basic congestion index, and meteorological congestion index. Subsequently, several major adverse meteorological conditions are discussed for their potential impact on traffic congestion. The results show that the annual average traffic congestion index during the morning and evening peak hours in the Beijing urban area is 1.69 and 1.99, respectively. The maximum congestion index during the morning peak hours of the week occurs on Monday, and that during the evening peak hours occurs on Friday. The adverse meteorological conditions that affect transportation during the morning and evening peak hours account for 32.9% and 26.4% of the total sample, respectively; moreover, the proportion of the meteorological congestion index caused by meteorological conditions during the morning and evening peak hours is 17.2% and 11.1%, respectively, with a maximum of 57.2%. This indicates that the impact of meteorological factors on transportation is greater during the morning peak hours than during the evening peak hours. Additionally, the meteorological congestion index presents seasonal differences, with the maximum value occurring in autumn. It is also found that there is a complex synergistic effect between meteorological factors and traffic congestion. The impact on urban traffic congestion is significant under the following conditions: light or heavy rain, road surface temperature close to freezing or below -10 ℃, wind speed above 10 m/s, and visibility below 1.5 km. Furthermore, the results of variance analysis show that low visibility has the highest contribution rate to the meteorological congestion index, followed by precipitation events, road surface temperature, and wind speed, with contribution rates of 27.6%, 11.7%, 7.2%, and 4.6%, respectively. The research results not only provide a basis for government departments to formulate effective traffic management measures and emergency plans, but also provide a reference for guiding residents to choose reasonable transportation modes.
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    2020,48(6):917-922, DOI:
    [Abstract] (1256) [HTML] (0) [PDF 1.07 M] (65994)
    Abstract:
    Using the meteorological observation data of Yuepuhu in Xinjiang from 1981 to 2019, combined with the growth and development of Flos Lonicerae, the relationship between the climatic conditions and the growth of Flos Lonicerae in Yuepuhu are analyzed. According to the ecological characteristics of Flos Lonicerae, the meteorological conditions of Flos Lonicerae cultivation in Yuepuhu are systematically analyzed, and the results show that the average temperature of each phenological stage of Flos Lonicerae in Yuepuhu show an obvious increasing trend; the number of sunshine hours has an obvious increasing trend; and the water source is sufficient. These are conducive to the normal growth and development of Flos Lonicerae. As the temperature rises and the number of sunshine hours increases, the planting time has been advanced from the previous mid March to early March; the planting area has expanded year by year, from tens of hectares in 2016 to 345 hm2 in 2019; and the planting mode has been adjusted from the plain cropping to inter cropping method. In the inter planting mode, the varieties are unified with Beihua No.1. The number of consecutive high temperature days of ≥38 ℃ during the growth and development of Flos Lonicerae, especially in ≥40 ℃ high temperature weather, the short term heavy precipitation weather, windy and sandy weather and other meteorological conditions have certain influence on the quality and yield of Flos Lonicerae. Exploration of the favorable climatic conditions for the development of the Flos Lonicerae planting industry in Yuepuhu provides a scientific basis for the construction of the Yuepuhu Flos Lonicerae industrial base, as well as the meteorological guarantee for the increase of income of flower farmers.
    2021,49(1):55-62, DOI:
    [Abstract] (1198) [HTML] (0) [PDF 11.58 M] (65124)
    Abstract:
    Clouds are an important part of the earth system, which can affect the radiation balance of the earth atmosphere system by affecting atmospheric radiation transmission. At present, the information obtained from three dimensional cloud observation has certain limitations, so it is necessary to obtain more accurate three dimensional cloud information by using multi source observation data merging analysis. Based on the successive correction method, 〖JP2〗the Three Dimensional Cloud Merge Analysis Operation System (3DCloudA V1.0) integrates multi source data such as numerical forecast products, geostationary meteorological satellite observation, meteorological radar observation to produce the real time 0.05°/h three dimensional cloud merging analysis product covering China and its surrounding areas (0°-60°N, 70°-140°E), which is distributed to the national and provincial meteorological departments through the China Telecommunication System. The modular system framework is considered in the operation system design and construction process, and the fault tolerant functions such as EC Flow scheduling process real time monitoring and automatic restarting are developed, which effectively improves the stability and reliability of the operation system. Evaluations show that through merging multi source observation data, the three dimensional cloud merge analysis product can describe cloud the top, inside and bottom information more accurately.〖JP〗
    2014,42(5):823-831, DOI:
    [Abstract] (1966) [HTML] (0) [PDF 2.17 M] (61882)
    Abstract:
    In order to improve the weather forecast quality over the low latitude plateau regions, the wind data retrieved with VAD (Velocity Azimuth Display) method are assimilated to the WRF (Weather Research and Forecasting) model by WRF 3DVar (3 Dimensional Variational Data Assimilation System). With different assimilation schemes, a torrential rain event occurred in Yunnan Province from 00:00UTC 30 June 2009 to 00:00UTC 1 July 2009 is numerically simulated and comparatively analyzed. The results indicate that the initial wind fields of the WRF model are markedly improved by assimilating the retrieved wind data. The WRF 3DVar can availably introduce the information of the retrieved wind to the initial conditions of the regional numerical model. The assimilation of the retrieved wind data helps enhance the wind convergence and vapor transportation over the rainy area. Furthermore, the assimilation help improve quantitative precipitation forecasts. The quantitative test of the 18 hour rainfall forecast shows that forecasts are more accurate, less pretermissions, and more rational pertinence for over 250 mm precipitation in the assimilation experimentations. The higher the assimilation frequency and the longer the assimilation time is, the more obvious the influence of data assimilation on the initial fields and forecast fields of the regional model is. But long assimilation time may increase the speed of synoptic systems and the overestimate rainfall, and so the suitable selection of frequency and time is crucial in numerical experimentations.
    2013,41(4):758-763, DOI:
    [Abstract] (2301) [HTML] (0) [PDF 26.87 M] (61656)
    Abstract:
    Through investigating the lightning disasters of ancient buildings, the distribution of ancient buildings being stricken by lightning are analyzed. It is found that animal finials and prominent parts of the like, old trees, towers and kiosks, service facilities and other parts of ancient buildings are vulnerable to lightning strikes. It is found that once an ancient building is stricken by lightning, it is probable to be stricken again by lightning. The reasons for that ancient buildings are stricken and caught fire by lightning are analyzed, and the proportions of casualties caused by ancient building lightning disasters are calculated. It is concluded that the reasons for ancient buildings stricken by lightning includes the appropriate location and structure of ancient buildings, tree triggering, internal environment changes, and water infiltration because of disrepair and other factors vulnerable to lightning.
    2017,45(6):1116-1124, DOI:
    [Abstract] (1511) [HTML] (0) [PDF 2.65 M] (50628)
    Abstract:
    Data quality assessment is an important part in model operation application. In this paper, the soil moisture observation data and China Meteorological Administration Land Data Assimilation System (CLDAS) data are used to establish the online CLDAS data quality assessment system through the MySQL database and the Web technology like html, JavaScript, HighChart， etc. The assessment analysis between the simulated soil moisture and the observed soil moisture at any of stations and provinces, times and different soil layers is implemented in the form of correlation coefficient, root mean square error, relative deviation, and mean deviation. Diagrams such as time series and scatter are visually displayed to compare the observation and simulated data in the system. The statistical indexes can be calculated immediately using JavaScript language in the Web platform. The assessment results and the comparison diagrams can be showed through the internet Web page, and the real time monitoring of the model product data quality can be achieved.
    2013,41(1):15-19, DOI:
    [Abstract] (2768) [HTML] (0) [PDF 12.84 M] (31988)
    Abstract:
    Due to the influence of the curve Earth, the fixed detection mode of the CINRAD/SA weather radar uses the minimum elevation angle of 0.5 °, so the blind area is relatively big, and the detection capability for low level precipitation echoes is limited. On the basis of experiments, the calculation formulas of the minimum height applicable when CINRAD/SA detects with positive and negative elevation angles are devised. Then the minimum detecting heights of CINRAD/SA at different distances with different elevation angles (0.5°, 0°, -0.3°,-0.5°) are calculated. Through analyzing characteristics of radar products detected under different elevation angles, some suggestions on CINRAD/SA about using negative elevation angles are presented.
    2010,38(3):289-294, DOI:
    [Abstract] (2937) [HTML] (0) [PDF 63.01 M] (30794)
    Abstract:
    With the intensive observation data and NCEP/NCAR reanalyzed data, an unusual heavy fog process occurred over the east central China from 25 to 27 December in 2006 is analyzed in aspects of the large scale synoptic condition and dynamic and thermodynamic mechanisms. It was shown that the fog occurred while the near ground wind velocity varied from 0.3 to 2.9 m/s and the dense fog occurred while the wind velocity varied from 0.3 to 2.4 m/s and the visibility was within 15 meters when velocity was from 0.8 to 1.1 m/s. Although vapor condition was bad and rainfall didn’t occur within a few days before the heavy fog, the continuous vapor transportation of the southwestern air current before a trough offered plentiful vapor for the fog. The results also show that the stable stratification gradually established before the fog.At first, the instable stratification built at higher levels after sunrise, subsequently passed downward to lower levels, and then the inversion layer destroyed and the fog dispersed and cleared off. The results indicate that the visibility changed rapidly and violently before the first stage of the severe heavy fog but it did not before the second stage.
    2010,38(3):281-288, DOI:
    [Abstract] (2520) [HTML] (0) [PDF 57.54 M] (30074)
    Abstract:
    In order to reveal the development mechanisms of heavy snowfall in Hebei Province,two heave snow processes on 14 to 16 March 2003 and 20 to 21 February 2004 are selected. A contrast analysis of their meteorological characteristics is made from aspect of synoptic situation and physical mechanism by means of numerical diagnosis with the NCEP reanalysis data and conventional observation data. The results show that the combination of south and north troughs with identical phase around 110°E at 500 hPa, the allocation of the surface pressure field with high in north and low in south, and the appearance of the ground inverted trough in the Hetao area of NW China, as well as the thermodynamic conditions with warm temperature tongue and warm advection in the lower troposphere, are the favorable large scale background for the formation of heavy snowfall. There are three important paths of water vapor in the two snow events: from southwest in front of the 500 hPa trough, from east at low level, and from low level jet. From the cross sections of vorticity, divergence, vertical velocity and vertical helicity, it is found that the vertical distribution of convergence at low level but divergence at upper level and ascending motion in the whole troposphere benefit the forming and maintaining of heavy snowfall, and the distribution of positive vorticity (vertical helicity) in the whole troposphere is most favorable. It is also suggested the temperature descending to below 0 ℃ at both 850 hPa and 925 hPa, meanwhile below 1 ℃ in the surface, is favorable to snowing. The results can be used as reference in the forecasting heavy snowfall.
    2010,38(4):432-436, DOI:
    [Abstract] (2427) [HTML] (0) [PDF 13.24 M] (25341)
    Abstract:
    A whole province range thunderstorm occurred in Zhejiang Province on 26 June 2009, and the occurrence frequency of cloud to ground lightning in this thunderstorm is the highest since the establishment of the lightning position system in 2006. By means of the observation data from the lightning position system, the intensive rainfall observation system, and Doppler radar, the characteristics of the cloud to ground lightning process are analyzed. The results indicate that lightning strokes were mainly negative; in the lightning echo image, negative strokes were mostly distributed in the area of 25 dBz to 55 dBz, and positive strokes were usually in the area of 25 dBz to 35 dBz; lightning strokes occurred mostly on the side of echo development or advancement, distributed around the area with maximum gradients, and there seldom appeared lightning strokes around a strong echo center; the frequency of cloud to ground lightning was correlated closely with the accumulated precipitation of the whole province during the thunderstorm. The peak value of precipitation lagged more than 0.5 hour behind the peak value of the frequency of cloud to ground lightning, and the accumulated precipitation of the whole province occurred 1 to 2 hours behind the peak value of the frequency of cloud to ground lightning. Therefore, the cloud to ground lightning data can be used as a basis in short range severe precipitation forecasting.
    2009,37(1):67-73, DOI:
    [Abstract] (2949) [HTML] (0) [PDF 788.79 K] (23105)
    Abstract:
    Soil moisture is a key variable in water and energy exchanges in land atmosphere interface. The passive microwave remote sensing is the most potent technology to retrieve soil moisture. A brief introduction is made to microwave theory, and a general review of soil moisture retrieval algorithms is given. Three typical cases are illustrated based on the different microwave sensors by comparing various algorithms, which correspond to the three parameter AMSR based retrieval developed by Njoku and Li, the two parameter SMMR based retrieval developed by Owe et al. and the two parameter SSM/I based retrieval developed by Wen et al. The insufficiency and potentials in the researches on soil moisture are discussed.
    2024,52(3):446-455, DOI: 10.19517/j.1671-6345.20230140
    [Abstract] (373) [HTML] (0) [PDF 17.35 M] (20335)
    Abstract:
    Under the common influence of factors including complex terrain, subtropical high pressure, and monsoon weather, the wind field in the alpine canyon areas of is complex and changeable, and it is easy to form the “narrow pipe effect”, which leads to disastrous gales that have a great impact on the construction and operation of large-scale projects. In this paper, based on Fluent, a fluid dynamics computing software, a standard turbulence model and PISO algorithm are used to study the variation of wind velocity field near the dam during dam construction and the influence of dam construction on the wind velocity field, taking the level 7 north wind in Baihetan Hydropower Station as a typical calculation condition. The research results show that the blocking effect of the dam body makes the wind velocity field at the top of the dam generate flow separation and wind field uplift, and a low wind velocity zone forms below the dam elevation. When the dam elevation is 650 m and 750 m, the wind speed within the cable platform is about 15 m/s to 16 m/s, and the channel length of the significant influence area by the wind speed vertical distribution downstream of the dam is 4.4 Ht and 4.5 Ht (Ht being the dam height). The significant influence heights of the wind velocity field at the top of the dam are 2.0 Ht and 3.0 Ht respectively. When the dam is filled to the normal water level of 825 m, the channel length of the significant influence area by the wind field downstream of the dam is 8.0 times the dam height (2.3 km), and the maximum influence channel length is 30.4 times the dam height (8.8 km). The influence height of the dam top reaches about 1500 m height, which is 3.5 times the dam height.
    2024,52(3):380-391, DOI: 10.19517/j.1671-6345.20230246
    [Abstract] (376) [HTML] (0) [PDF 14.80 M] (20322)
    Abstract:
    Flash heavy rain and the resulting low visibility make it difficult for pilots to visually assess the runway clearly, severely impacting the take-off and landing of aircraft, thereby posing a threat to aviation operational safety. Moreover, the flight delays and diversions caused by this also result in significant losses for airlines and negatively affect socioeconomic benefits. Therefore, conducting comprehensive studies on flash heavy rain is crucial for ensuring aviation safety and enhancing flight punctuality. A thorough analysis of sufficiently detailed observational data is beneficial for clarifying the dynamic mechanisms of convective organisation and enhancement. On July 15, 2022, Xiamen Airport experienced a rare flash heavy rain event triggered by a weak background gust front. During this period, the precipitation intensity peaked at 2.5 mm per minute, and runway visibility rapidly decreased to 600 m, which is relatively uncommon at Xiamen Airport. To analyse this flash heavy rain event, this study utilises minute rainfall data from both ends of the runway, conventional observational data, densified automatic weather station data, ERA5 reanalysis, and S-band dual-polarisation and X-band dual-polarisation phased array radar data of Xiamen. The results of the study indicate that this event occurred under weak weather-scale forcing, where the gust front triggered uplift by intersecting and merging with the surface convergence line during propagation. In an environment characterised by negative large values of pseudo-equivalent potential temperature (θse500-850 hPa) and a warm and humid lower atmosphere, new convection was stimulated, resulting in the rare flash heavy rain at Xiamen Airport. During heavy rain, strong water vapour convergence appeared in the boundary layer at 1000 hPa. Minute rainfall on the runway showed an inverse correlation with visibility, but this correlation weakened when the minute rainfall exceeded 1.6 mm, and the visibility minimum lagged behind the rainfall peak by 7 minutes. Observational analysis reveals that the cyclonic shear of radial velocity was consistent with the trend of minute rainfall change. The peak minute rainfall at both ends of the runway corresponded to the peak cyclonic shear at a certain height layer, indicating a good correspondence between the two. When there was cyclonic shear in the radial velocity at heights of 2-5 km, rainfall significantly intensified. When the shear intensity at two height layers exceeded 2×10-3s-1, minute rainfall could reach approximately 2 mm (equivalent to an hourly rainfall of 120 mm), which emerged as a characteristic feature of this flash heavy rain event.
    2024,52(3):347-355, DOI: 10.19517/j.1671-6345.20230189
    [Abstract] (436) [HTML] (0) [PDF 11.03 M] (20303)
    Abstract:
    In order to expand the space of meteorological business, integrate multiple fields of monitoring, and promote the development of the meteorological industry towards efficiency, convenience, and intensification, the Guizhou Province Meteorological Comprehensive Monitoring System APP is developed using mainstream mobile apps as carriers, based on the Springboot+Vue+Mybatis Plus development framework, and using multi-platform compatible development (uni-app), real-time capture of change data (FlinkCDC), and an efficient packaging framework (Mybatis-Plus) among other technical means. The article provides a detailed introduction to the framework structure and functional design adopted by the APP as an independent monitoring system, as well as the big data development technology and its business advantages involved. At the technical level, the system utilises uni-app development technology to make the APP client more compatible and can simultaneously adapt to various application platforms such as iOS, Android, Web, and various mini-programs; using Mybatis-Plus as the database driver framework to improve code reusability and reduce database performance overhead; by using FlinkCDC as a data processing and incremental synchronisation tool, resource waste caused by full data synchronisation can be avoided, simultaneously serving as a one-way synchronisation tool to enhance the security of meteorological data. At the framework level, in order to avoid security risks caused by network mixing, the system introduces a Demilitarised Zone (DMZ) to isolate the internal and external network data environments. The internal network department is responsible for collecting and storing meteorological data from various formats such as databases, static files, API interfaces, logs, etc. Then, it will be synchronised unidirectionally with the external network environment through FlinkCDC. The external network interacts with the mobile APP by receiving data pushed by FlinkCDC. The software is aimed at meteorological users at all levels of province, city, county, and station. Through preliminary research and analysis, four functional modules have been developed for different users, including regional automatic stations, weather radar stations, network connectivity, and interface service status. This provides convenience for meteorological data monitoring and equipment maintenance, and improves the timeliness of response. The system has been put into use throughout the province since 2022. The application results show that the APP adapts to multiple mobile system platforms such as Android and iOS, and has a friendly interface, simple operation, and stable operation. Since its application, the timeliness of meteorological data has improved, enriching the monitoring business methods of Guizhou Province, meeting the user needs at all levels, and playing a positive role in the development of the meteorological industry.
    2024,52(3):318-329, DOI: 10.19517/j.1671-6345.20230129
    [Abstract] (368) [HTML] (0) [PDF 75.13 M] (20197)
    Abstract:
    By introducing the relief shading method, which is often used in making the topographic maps, into the visualisation of numerical weather forecast data, this article presents the achievement in three-dimensional drawing of meteorological variables, such as air pressure and geopotential height. Based on the principle and implementation of hill shading, which uses the relationship between the illumination angle, the direction, the slope, and the orientation of the terrain to calculate the brightness value of luminous flux, the relief shading method makes use of the brightness value to display the three-dimensional sense of meteorological model data. At the same height, the steeper the terrain, the darker (brighter) the shaded (sunny) side; under the same slope, the higher the terrain, the darker (brighter) the shaded (sunny) side, which is consistent with the real-life visual effect. The colouring method of the shaded relief map is to use the brightness value (V) in the HSV colour space which is calculated on each grid point, combined with hue (H) and saturation (S) to obtain a complete HSV colour scheme. Through the conversion from the HSV colour space to the RGB colour space, the latter colour space is used for drawing a coloured shaded relief map for meteorological model data. In the shaded relief map, the high-pressure centre in the weather system is often shown as a raised peak, and the low pressure is shown as a depressed valley; a large pressure gradient can be seen as a steep slope, while a small pressure gradient can be seen as a gentle slope. Compared with the traditional isoline and colour filling analysis, it is found that the shaded relief map can help to identify high-low weather systems by concave-convex shapes and reflects the gradient changes of weather systems through the steepness of slope, thus intuitively representing the three-dimensional distribution of atmospheric circulation. In addition, the shaded relief map has the ability to visualise model data in pixel level details, identify early eddy current disturbances in small gradients, and reveal equivalent terrain effects, which helps the meteorologists better interpret the model data and provides the references for the improvements of data process functions in numerical models. Furthermore, the relief shading method is suitable for using the synthetic animations to showcase the fluid characteristics of atmospheric motion, which is conducive to popularising the concept of various weather systems, such as the high, the low, the trough and ridge, and their evolution to the public.
    2024,52(3):309-317, DOI: 10.19517/j.1671-6345.20230123
    [Abstract] (508) [HTML] (0) [PDF 8.58 M] (20046)
    Abstract:
    Aiming at the problems of data quality degradation caused by multi-channel scanning-type loads on geostationary orbit remote sensing satellites in the process of imaging, transmission and storage, i.e., the influence of texture distortion and edge blurring in the meteorological remote sensing feature recognition images on the analysis of meteorological remote sensing images, this study proposes an improved BM3D noise reduction algorithm. The algorithm combines Morlet wavelet decomposition theory (with good symmetry and its decay characteristics follow the exponential law, it is able to match the mutation signals in the meteorological remote sensing images, thus realising signal denoising) and BM3D denoising principle (a non-local filtering algorithm that includes two parts: block matching and 3D collaborative filtering. Block matching involves grouping image blocks similar to a given reference block and composing them into a 3D array). Firstly, the image decomposes using wavelet transform to get four components. Secondly, the meteorological remote sensing image decomposes into three levels with a total of ten components. Finally, each component denoises using a separate BM3D filter, and the output image of the 10 components reconstructs. The output reconstructed image views as an estimate of the desired image, capable of suppressing meteorological remote sensing image noise and preserving edge detail. Compared with the traditional BM3D denoising algorithm, the improved BM3D algorithm is able to reduce the computation by about one-fifth. The eight meteorological remote sensing images process by equalising the grayscale and adding additive Gaussian white noise with mean 0 and standard deviation σ and random impulse noise. The median filter (suitable for removing isolated noise such as pepper noise), mean filter (suitable for removing noise from images), NL-Bayes (suitable for smoothing images and preserving image details), BM3D algorithm and the improved BM3D algorithm also compare to process the images respectively, and based on the results of peak signal-to-noise ratio (according to the definition of peak signal-to-noise ratio, it considers as the main metric to evaluate the quality of an image and utilises to measure the degree of realism of an image, with higher values indicating better denoising effects) of the meteorological remote sensing images, it finds that the average PSNR gain of the algorithms proposed in this study is in the range of 0.39 dB to 4.45 dB. The above experimental results of meteorological remote sensing images indicate that the improved BM3D algorithm works better, especially in the mixed noise denoising of Gaussian white noise and impulse noise.
    2024,52(3):403-414, DOI: 10.19517/j.1671-6345.20230186
    [Abstract] (487) [HTML] (0) [PDF 25.35 M] (19989)
    Abstract:
    Based on the hourly and daily precipitation data of 61 national meteorological stations from 1961 to 2020 and 998 regional automatic meteorological observation stations from the beginning of the establishment to 2020 in Liaoning Province, we analyse the main causing factors of rainstorm and flood disaster, calculate the environmental indicators of rainstorm and flood disaster, and complete the hazard assessment of rainstorm and flood disaster in Liaoning Province. The results show that the high-risk area of rainstorms and floods is mainly located in Dandong. The high population risk areas of rainstorm and flood disaster are mainly located in Shenyang and Dalian urban areas. The high economic risk areas of rainstorm and flood disaster are mainly located in Dalian and Panjin urban areas. The high-risk areas of rice and maize are mainly located in Jinzhou, Panjin, and Dandong. The disaster risk of the rainstorm process on 28-29 July 2022 is pre-assessed using the intelligent grid forecast data of Liaoning Province. It is found that the high hazardous areas are mainly distributed in Chaoyang, Huludao, and the central part of Liaoning. The population and economic high-risk areas caused by the rainstorm disaster are mainly located in the western and central areas. The high-risk areas of rice and maize caused by rainstorm disaster are mainly located in Shenyang, Tieling, and the north of Chaoyang. It is estimated that the population affected in the high-risk area is about 4.49 million, the economic loss is about 14.32 million yuan. The affected rice area is about 10,280 hectares, the maize area is about 17,798 hectares. Through the post-disaster effect test, it is found that the pre-assessment model is effective and can be used in the actual rainstorm and flood disaster risk assessment business.
    2024,52(3):424-433, DOI: 10.19517/j.1671-6345.20230152
    [Abstract] (453) [HTML] (0) [PDF 9.05 M] (19976)
    Abstract:
    In order to further strengthen the application of satellite-to-ground lightning, the spatial-temporal distribution characteristics and spatial-temporal matching features are comparatively analysed in Zhejiang Province based on lightning data from FengYun (FY)-4A Lightning Mapping Imager (LMI) and Advanced Direction and Time-of-arrival Detecting (ADTD)-2C three-dimensional lightning location system from June to August in 2020. In addition, by combining reflectivity of Doppler radar mosaics and cloud top brightness temperature from FY-4A Advanced Geosynchronous Radiation Imager (AGRI), the spatial and temporal evolution patterns of lightning data from two observation systems are analysed during a thunderstorm process in Zhejiang Province on 15 July 2020. The results show that from June to August in 2020, the number of LMIG detected by LMI was 8483, while the number of lightning detected by the ADTD-2C three-dimensional lightning location system was 376932. The ratio of the two sets of data was approximately 1∶44.43. The monthly and spatial distributions of lightning detected by these two systems were generally consistent, while diurnal variation of which were different. Specifically, diurnal variation of LMIG presented two peaks, and diurnal variation of three-dimensional lightning showed only one peak. Besides, when the time matching window was larger than 1.8 seconds, and the latitude and longitude matching window was larger than 0.5°, the matching rate gradually tended to be stable. Furthermore, the height of three-dimensional lightning matched with LMIG was mainly concentrated below 16 km, and the lightning intensity of which was mainly concentrated below 50 kA. During the thunderstorm weather in Zhejiang Province in the afternoon on 15 July 2020, the ratio of LMIG to three-dimensional lightning was approximately 1∶25.44. The time of the first LMIG and its peak time were both later than the time of the first three-dimensional lightning and its peak time. What’s more, the lightning data observed by the two systems corresponded well with the development process of the thunderstorm. When the thunderstorm was at the developing stage, the number of lightning data detected by the two systems was both gradually increasing, and when the thunderstorm was at the mature stage, the number of lightning data detected by the two systems was both maintaining a relatively high value, and when the thunderstorms were at the dissipation stage, the number of lightning data detected by the two systems was both decreasing rapidly. When it came to the spatial distribution of the lightning, both of the two datasets corresponded well with the spatial distribution of low cloud top brightness temperature.
    2024,52(3):330-339, DOI: 10.19517/j.1671-6345.20230166
    [Abstract] (629) [HTML] (0) [PDF 1.48 M] (19704)
    Abstract:
    In order to apply the Hail Detection Algorithm (HDA) related products more extensively and correctly, for the 22 hail cases monitored in Pu’er area from 2015 to 2020, the new Radar Operational Software Engineering (ROSE2.0) is used to replay radar-based data and analyse the relevant products. The recognition effect of the HDA algorithm in the Pu’er area is evaluated with the probability of detection (POD), false alarm rate (FAR), and critical success index (CSI), and a localised parameter configuration scheme is provided after that, which is useful to improve the local hail warning ability. The results show that although the POD of the HDA algorithm in Pu’er area is close to 100%, there are also many ordinary storm cells that are identified as hail cells mistakenly. The number of false alarms is very huge, and the low CSI cannot meet the requirement of the weather forecasting operation. The warning effect of using Probability of Severe Hail (POSH) is better than that of Probability of Hail (POH) for any size of hail, and the larger the size of hail, the lower the probability of false alarm of POSH. Further analysis of the adaptation parameters of the POSH algorithm by a simulation test method shows that the height of the 0 ℃ and -20 ℃ layers has a significant impact on the recognition ability of POSH, the original default value is significantly lower in Pu’er area, correctly inputting the height of 0 ℃ and -20 ℃ layers on the day of hail can effectively reduce the FAR and improve the CSI of POSH; at the same time, it can control the situation that the maximum hail diameter predicted by the algorithm is generally too large, and the maximum expected hail size (MEHS) is closer to the observation value; the deviation percentage of small and medium-sized hail diameter decreases by 76.07%, with a significantly higher improvement effect than large hail, but the diameter prediction error of MEHS for large hail is smaller. In addition, increasing the reflectivity factor and POSH threshold can effectively control FAR, but it also leads to a rapid increase in the number of missed alarms. When the threshold is too large, the POD significantly decreases. In order to achieve a higher POD and CSI, selecting Z=50 dBz or POSH=70% as the threshold can improve the recognition effect of the HDA algorithm. Setting the optimal threshold of multiple parameters at the same time can effectively improve the recognition ability of the HDA algorithm in Pu’er.
    2024,52(3):367-379, DOI: 10.19517/j.1671-6345.20230172
    [Abstract] (357) [HTML] (0) [PDF 13.77 M] (19698)
    Abstract:
    Based on the ensemble forecast data derived from European Centre for Medium-range Weather Forecasts (ECMWF) ensemble forecast system and observation data derived from automatic observation stations in Zhejiang region, the Bayesian Model Averaging (BMA) method is used to calibrate the probabilistic forecasts of precipitation during the super long Meiyu season in 2020. In this paper, we verify the raw ensemble probabilistic forecast and BMA calibrated probabilistic forecast from 1 June to 15 July, 2020, by Mean Absolute Error (MAE), Continuous Ranked Probability Score (CRPS), Brier Score (BS), Talagrand, Probability Integral Transform (PIT) histogram, and attribute diagram. The verification results before and after calibration are compared. The analysis results are listed as follows. (1) In 8 different training periods (10 days to 80 days), 50 days correspond to smaller MAE and CRPS score values. So we set 50 days as the optimal BMA training period for ECMWF ensemble forecast calibration in the Meiyu season in Zhejiang Province. After BMA calibration in the optimal training period, the spread of ensemble forecast increases and the forecast error decreases. Analysing from the quantitative verification indicators, BMA can effectively calibrate the overall precipitation in the test stage, but it cannot calibrate the daily precipitation in the test stage. (2) For forecasting of different threshold precipitation, BMA has different calibration performance. For the thresholds of 0.1 mm, 10.0 mm, and 25.0 mm, BMA has a significant calibration effect. After BMA calibration, the CRPS of precipitation probabilistic forecast for these three thresholds (0.1 mm, 10.0 mm, and 25.0 mm) decreases by 25.92%, 19.29%, and 4.76%, respectively. However, the calibration effect of BMA weakens with the increase of precipitation threshold. For the events with total precipitation exceeding 50.0 mm, the BMA calibration effect is not as significant as that of the smaller threshold. In addition, BMA can effectively improve the forecast skills of 0.1 mm, 10.0 mm and 25.0 mm threshold precipitation and make the forecast probability more closely match the observation. (3) In the case of heavy rain, the high probability range of the raw ensemble probabilistic forecast is always wider than that of the observation. BMA has the ability to slightly calibrate the raw ensemble forecast probability. After BMA calibration, the high probability range of precipitation forecast at each threshold effectively reduces the deviation. The empty message information and the probability of empty message events also reduce after calibration. So BMA can make the calibrated high probability range of precipitation forecast more consistent with the observed range. But unfortunately, BMA cannot adjust the spatial distribution of precipitation forecast probability.
    2024,52(3):340-346, DOI: 10.19517/j.1671-6345.20230182
    [Abstract] (373) [HTML] (0) [PDF 2.24 M] (19689)
    Abstract:
    In order to achieve the goal of independent and controllable key core technologies for Meteo by 2025, the Meteo Big Data Cloud Platform (referred to as Tianqing) establishes a simulation environment based on Hygon X86 CPU and Kylin OS. However, in the operation of simulation platforms, it finds that the docker scheduling performance of data processing and assembly line subsystems based on Kubernetes is poor, which cannot meet the timeliness requirements of user integration algorithms. In response to this issue, this article adopts a comparative analysis method, selecting servers based on three types of CPU and three types of operating systems from the simulation environment and business environment for Tianqing as the research objects. A series of combined comparative test cases are designed. It finds that the kernel is the key factor affecting docker scheduling performance. Further analysis is conducted on the impact of operating system kernel settings on real-time and throughput, as well as the suitable business scenarios. Finally, a method for adjusting the Kylin OS kernel is provided. By adjusting the kernel settings, the docker scheduling performance significantly improves, meeting the timeliness requirements of the data processing system and laying the foundation for achieving self-supporting of the key core technology of Tianqing.
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    2004,32(4):251, DOI:
    [Abstract] (6336) [HTML] (0) [PDF 423.81 K] (6109)
    Abstract:
    CINRAD/SA, China Next Generation Weather Radar,was produced by the Beijing METSATAR Radar Co., Ltd, based on the NEXRAD WSR-88D technology.Its software system was modified to provide the new RHI/PPI scan mode because NEXRAD WSR-88D provides only the volume scan mode. The design and realization of the RHI/PPI scan mode on the CINRAD/SA are described.
    2008,36(6):760-763, DOI:
    [Abstract] (5915) [HTML] (0) [PDF 464.40 K] (5820)
    Abstract:
    An analysis is made of the annual, seasonal, and monthly variation characteristics of sunshine duration in recent 50 years and its relationship with total cloudiness, trying to detect the variation of sunshine duration in Chengdu by the abrupt climate change theory. The results indicate that in recent 50 years, the sunshine duration decreased with a tendency of 69.41 hours per ten years; the interannual variation amplitude was obviously greater; and the difference between the sunshine durations in 1963 and in 1989 is up to 662.8 hours. There is obvious seasonal difference in sunshine duration, with bigger decreasing amplitude in summer and winter than those in spring and autumn and a tendency of -29.77 and -20.17, -9.91 and -9.56 hours per ten years, respectively. The decreasing tendency is obviously greater in August and less in April. The annual variation of sunshine duration is consistent with sunshine percentage. The sudden change occurred around 1978, with the annual sunshine duration decreased rapidly.
    2005,33(4):340-344, DOI:
    [Abstract] (4674) [HTML] (0) [PDF 146.22 K] (7620)
    Abstract:
    In order to develop and utilize reasonably climate resources and offer a scientific basis for the sub-area management of livestock production over grasslands, an analysis was made of the Inner Mongolia grassland climate characteristics and effects of climate on the growth of pasture grass, the distribution of domestic animal breeds and the soil environment. It is found that some isolines of climatic moisture are almost superposed with the boundaries of soil, which indicates that the formation of soil zones is closely related to climatic conditions, and climate and soil environment are main influence factors for pasture types and the ecosystem. Based on the climatic moisture, in combination with the distribution characteristics of soil over Inner Mongolia, a regionalization was carried out of grassland ecological types, which is not only rational, but also stable. It is pointed out that the climatic warming and the resulting changes in recent years improved, to some extent, the productivity of the grasslands, but not changed the ecotype in Inner Mongolia.
    2008,36(4):474-479, DOI:
    [Abstract] (4654) [HTML] (0) [PDF 650.10 K] (5359)
    Abstract:
    An observational experiment was conducted on the impact of air temperature and humidity variation on soil resistivity and earthing resistance with different structures by selecting three typical soil conditions to set three vari structure lightning protecting earthing bodies in Ningxia for one year. By means of comparative and regression analysis, the impacts of different soil conditions on soil resistivity at different temperatures and humidity in different seasons, and the variation characteristics and regularities of the lightning protecting earthing bodies with different structures are studied, and accordingly the optimal requirements for the layout and structure of lightning protecting earthing bodies are presented.
    2010,38(1):1-8, DOI:
    [Abstract] (4090) [HTML] (0) [PDF 988.69 K] (8453)
    Abstract:
    An introduction of the main reanalysis data of NCEP, ECMWF, JMA and the preliminary comparison among them are given from the following aspects: (1) assimilation systems, including the assimilation module and method; (2) the data used in the reanalysis; and (3) the methods of quality control and bias correction. The main assimilation methods of all reanalysis datasets include the 3D variational method, 4D variational method, and optimum interpolation. The dominating differences of these reanalysis datasets are data types and the resolution of modules. In addition, the advantages and deficiencies of these reanalysis datasets are given by empirical analysis. It is helpful for selecting the correct reanalysis dataset. The advances in reanalysis in China ars introduced simply and some problems on the improvement of the reanalysis in China are discussed.

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