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.

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    A Visibility Detection Method Based on Ordinal Consistency Constraints
    GUO Rui, GUO Wenjing, WU Dan, LI Meiqi, HUANG Yaping, WANG Yuefeng
    2025,53(6):783-791, DOI: 10.19517/j.1671-6345.20250183
    [Abstract] (31) [HTML] (0) [PDF 2.20 M] (31)
    Abstract:
    To enhance visibility observation capability along highways and improve the accuracy of visibility detection based on video surveillance images, this paper builds upon prior research by focusing on the ordinal relationships between visibility levels. By transforming the traditional visibility level classification task into a series of ordered binary classifiers, it imposes consistency constraints on visibility level detection results. This approach leads to a novel visibility detection method based on ordinal consistency constraints, resulting in more stable model predictions. Two datasets collected from real highways—JS-FHVI (Jing-Shi Foggy Highway Visibility Images) and DG-FHVI (Da-Guang Foggy Highway Visibility Images)—are used for experimental design and validation. Images are randomly partitioned into training (70%), validation (10%), and test (20%) sets. Visibility is categorised into six levels: ≤50 m, 50-100 m, 100-200 m, 200-500 m, 500-1000 m, and ≥1000 m. Image annotations are derived from meteorological station data nearest to the camera locations, with verification and corrections by professional meteorologists. A model based on ordinal consistency constraints (OCC) is designed, and an ordinal consistency constraint loss function is introduced, enabling the model to prioritise samples with inconsistent ordinal predictions. Further ablation studies compare four ordinal consistency measurement methods, revealing that Intersection over Union (IoU) yields optimal results and is adopted as the consistency metric. Subsequently, five scaling functions—linear, exponential, exponential square root, logarithmic, and softmax scaling—are evaluated, with exponential square root scaling achieving the highest classification accuracy. Based on these findings, two weighting strategies for hard samples are designed and tested. The strategy of increasing weights for hard samples proves more effective. To verify the performance of the proposed method, AlexNet, VGG16, ResNet-18, ResNet-50, EfficientNetB1, original ordinal regression, and the ordinal regression method with Ordinal Consistency Constraint (OCC) are employed as backbone networks to detect the visibility level of each highway image. The results demonstrate that the detection accuracy of the OCC-based method surpasses all other approaches. On the JS-FHVI test set, the method’s accuracy achieves 93.75%, and on the DG-FHVI test set, it achieves 86.94%. Its effectiveness is further validated through ablation studies. Cross-testing is conducted using models trained on JS-FHVI, DG-FHVI, and a unified model trained on merged data. Results demonstrate that models trained on specific highway data perform better locally, while the unified model exhibits superior generalisation across scenarios. Extensive experiments confirm that the proposed OCC-based method significantly enhances visibility detection accuracy. The current work focuses on discrete-level visibility detection; future efforts may extend to continuous numerical estimation to improve practical precision. Additionally, given the dynamic evolution of fog, short-term visibility forecasting or trend prediction remains a critical direction for further research.
    Assessment of Visibility Levels for Mountainous Highways Based on Hybrid Models
    PAN Cen, CAI Lujin, NIU Diyu, LIAO Bo, DU Zhengjing, HE Junjie
    2025,53(6):792-803, DOI: 10.19517/j.1671-6345.20250217
    [Abstract] (24) [HTML] (0) [PDF 20.18 M] (33)
    Abstract:
    Guizhou Province ranks the fifth in China in terms of expressway mileage, yet the deployment of traffic meteorological stations remains sparse. Frequent low-visibility weather events, influenced by mountainous terrain, pose severe threats to road safety. Deep learning-based image recognition methods for visibility level classification assist in rapid assessment for traffic management during foggy conditions. However, conventional neural networks (CNNs) suffer from limited classification accuracy due to insufficient global feature extraction. To address this issue, this study integrates both local and global feature representations by constructing a hybrid network model, cTrans-Net, which combines CNNs and Transformer architectures. Surveillance video images from typical mountainous expressway sections in Guizhou are selected for model training and testing to achieve precise five-level visibility classification (L0-L4) that impacts traffic safety. Experimental results demonstrate that cTrans-Net achieves an overall accuracy of 89.17%, with an area under the curve (AUC) of 0.9822, outperforming several mainstream deep learning models. The overall accuracy of the independent validation set remains 87.75%. In evaluating low-visibility conditions (<500 m), which significantly affect traffic, the model attains the highest recognition recall of 90.66% for the most frequently occurring L2 level (100-200 m). For the less frequent L0 (>500 m) and L4 (≤50 m) categories, the recognition recall reaches 92.31% and 90.45%, respectively, indicating the model’s robustness in handling imbalanced datasets. Feature visualisation reveals that cTrans-Net effectively focuses on key regions such as road markings and fog distribution, which are critical for visibility assessment. This study provides a technical solution for fog-related visibility recognition in intelligent transportation systems, offering practical value for real-world applications in mountainous expressway environments. The proposed cTrans-Net demonstrates strong adaptability to imbalanced data scenarios and exhibits superior performance in critical low-visibility conditions, making it a viable tool for enhancing traffic safety management under adverse weather conditions.
    Development and Implementation of Mobile Application System for Jiangsu Decision-Making Meteorological Services with Coupling of Knowledge and Scenarios
    CHEN Shengjie, WANG Xiaohua, XU Xiaolong, TIAN Xinru, WU Hongyan, LIU Dan, RUI Zishun, LYU Runqing, ZHOU Wenjun, QIAN Xinwei
    2025,53(6):804-815, DOI: 10.19517/j.1671-6345.20250134
    [Abstract] (22) [HTML] (0) [PDF 22.85 M] (32)
    Abstract:
    To enhance the efficiency of real-time meteorological data access for local disaster prevention and mitigation authorities, the Jiangsu Meteorological Bureau spearheads the development of a specialised Decision-Meteorological Service Mobile Application (APP). The APP, driven by user needs, adopts a strategic approach to prioritise key decision-making factors while enhancing the user experience. The APP integrates multi-source meteorological data, expertise, and diverse application scenarios to provide comprehensive and scenario-based meteorological services. By deploying behaviour-driven and weather-integrated recommendation algorithms, it enables personalised service customisation for different user groups. Leveraging the “DeepSeek-R1-Distill-Qwen-32B” large language model and integrating speech recognition and dynamic dialogue state tracking technologies, the meteorological conversation robot “Su Xiaoce” is developed to support intelligent question-and-answer and function navigation to deliver conversational services. Given its precision-tailored and operationally effective service, the APP is fully implemented across key disaster prevention departments in Jiangsu Province. The system provides preemptive early warnings, real-time emergency alerts, and sustained operational support during disaster weather prevention and mitigation, offering a replicable and promotable technical path for the construction of decision meteorological service capabilities.
    Research on Extreme Precipitation in Shanxi: Improvement of Climate Distribution and Extreme Weather Forecast Index Application
    HAO Jingyu, YAN Hui, MA Yanzhi, MA Li, MIAO Qing, SUN Yingshu
    2025,53(6):816-828, DOI: 10.19517/j.1671-6345.20250105
    [Abstract] (36) [HTML] (0) [PDF 12.22 M] (26)
    Abstract:
    Based on the daily precipitation observation data from 109 national stations in Shanxi from July to August 1990 to 2022, the ECMWF numerical precipitation data, and the EFI (Extreme Weather Forecast Index) products from the ECMWF ensemble prediction system from July to August 2022, the different percentile values (maximum, 99%, 95%) of historical extreme precipitation in Shanxi are calculated using the percentile method. The actual situation of extreme precipitation from July to August 2022 is analysed, and the forecast performance of two precipitation forecast products at different lead times (0-24 h, 24-48 h, 48-72 h) is evaluated. A new method for forecasting extreme precipitation is proposed by combining the EFI with the ECMWF high-resolution model. The results show that: (1) The historical extreme precipitation values in Shanxi in July are generally higher than those in August, and the possibility of abnormal extreme precipitation is greater. The extreme precipitation values in the north of Shanxi are lower than those in the central and southern regions, and the centre of the maximum extreme precipitation value has a significant relationship with the topographic distribution. (2) The precipitation in most areas of Shanxi exceeds the historical extreme precipitation in 2022, with occurrences in the central and southern regions in July, and in most areas in August. (3) Both the EFI and the ECMWF models have certain forecasting capabilities for extreme precipitation in July and August 2022. The forecasting ability of EFI for more extreme precipitation is superior to ECMWF’s. (4) The new extreme precipitation forecast based on the ECMWF model improves the forecasting effect on the 95th percentile values of western Shanxi, the 99th percentile values, and the maximum extreme precipitation of the central region in July, the 95th percentile values in central and southern Shanxi, and the 99th percentile values of the northwestern region in August. The forecasting effect for more extreme precipitation improves significantly.
    Analysis of Precipitation Forecast Deviation of Numerical Models over Jilin Province in Warm Seasons under Background of Northeast Cold Vortex
    YAO Kai, ZHU Xiaotong, TU Gang, CHEN Changsheng, QIN Yulin
    2025,53(6):829-841, DOI: 10.19517/j.1671-6345.20240327
    [Abstract] (23) [HTML] (0) [PDF 2.57 M] (22)
    Abstract:
    Numerical models serve as critical reference bases for weather forecasting. Effective application of numerical models for forecasting first requires understanding the models’ forecasting performance, which is derived from verification. This study researches the forecasting capabilities of different numerical models in terms of precipitation associated with the Northeast Cold Vortex in Jilin Province. Utilising hourly precipitation observation data from 1436 stations in Jilin Province during the Northeast Cold Vortex period from May to September 2021-2023, a comparison analysis is conducted between the precipitation forecasting products of six numerical models, namely, EC, CMA-MESO, CMA-GFS, CMA-TYM, CMA-SH9, and CMA-BJ. The aim is to reveal the characteristic differences in forecasting capability and deviation contributions between three-hour-interval precipitation forecasts in plain and hilly areas using quantitative assessment, graded assessment, and diurnal variation forecast comparison. The results indicate that: (1) The observed precipitation associated with the Northeast Cold Vortex and the precipitation forecasting capability of numerical models are closely related to topographic distribution. In the plain group, both the precipitation amount and the number of observation stations are smaller, while the precipitation intensity is stronger, and the mean relative error (MRE) and mean absolute error (MAE) of the stations are larger. In contrast, the hill group shows opposite trends: larger precipitation amount, more station numbers, weaker intensity, and smaller MRE and MAE. (2) EC demonstrates the best performance in forecasting diurnal variations of precipitation in both plain and hilly groups; however, it lacks the ability to predict the peak of precipitation intensities, with a notable overestimation of precipitation frequency occurring around midday. In contrast, CMA-MESO and CMA-SH9 are more effective in capturing the diurnal peak or trend characteristics of precipitation frequency and intensities. (3) The weak precipitation forecasts under various models are overly frequent, while the forecasting capabilities for moderate and heavy precipitation are influenced by topographical differences, where the performance in hilly areas surpasses that in plain areas. Additionally, CMA-MESO and CMA-TYM outperform global models, with global models exhibiting significant dry deviations. (4) The forecasting skill clock plots indicate that the excessive forecast of frequency by EC around midday is mainly due to overforecasting weak precipitation, while the significant underforecast of strong precipitation throughout the day results from missed occurrences. Furthermore, CMA-MESO exhibits stronger forecasting capabilities for heavy precipitation compared to EC, successfully predicting evening peak values and the occurrence of heavy precipitation stations. Its errors arise from location deviation in the forecasts.
    Climate Characteristics of Winter Snowfall in Xinjiang Changji Prefecture from 1982 to 2022
    ALHADEH Haderhan, ARAY Ayden, WANG Chunyan, WANG Jianghua, Saltanat, APAR Ruzi
    2025,53(6):842-853, DOI: 10.19517/j.1671-6345.20250185
    [Abstract] (36) [HTML] (0) [PDF 4.73 M] (25)
    Abstract:
    The study of winter snowfall holds great significance for Changji Prefecture, located in the northwestern arid region. Abnormal winter snowfall frequently leads to heavy snowfall, which results in snow disasters and avalanches. Furthermore, blizzards and strong winds often cause snowdrifts that block traffic and severely reduce visibility. Therefore, it is essential to conduct investigations in this area. A notable example occurred in December 2015, when Changji Prefecture experienced an extremely rare blizzard characterised by widespread snowfall and a high number of stations reporting heavy snow, with many stations breaking historical records. Therefore, systematic research on winter snowfall is necessary. This study focuses on the Changji area. Based on daily precipitation records from 10 national meteorological stations between 1982 and 2022, the characteristics of snowfall amount, snowfall intensity, and the number of snowfall days are analysed using methods such as linear regression, the Mann-Kendall test, and wavelet analysis. The results show that, based on the winter daily snowfall observation data from 10 national stations in Changji Prefecture from 1982 to 2022, this study analyses the climatological characteristics of winter snowfall amount, snowfall days, and snowfall intensity using methods such as linear trend estimation, Morlet wavelet analysis, Mann-Kendall mutation test, and ArcGIS inverse distance weighting interpolation. The results reveal several noteworthy findings: (1) Significant regional differences exist in winter snowfall changes. The snowfall amount shows a significant increasing trend in the plain area and the Beitashan region, with rates of 2.6 mm/10a and 2.8 mm/10a, respectively, while the trends in the Tianchi and Caijiahu regions are not significant. The dominant months contributing to the increase differ, with December being the primary contributor in the plain area and February in the Beitashan region. (2) The reduction in snowfall days across various regions is consistently attributed to a significant decrease in light snowfall days. Concurrently, the number of heavy snowfall days increases significantly in the plain and Tianchi areas, and the winter snowfall intensity enhances significantly, indicating a trend towards more intense snowfall events. (3) Topography is a key factor influencing snowfall distribution, with both snowfall amount and heavy snowfall days exhibiting a spatial pattern of high values in mountainous areas (Tianchi), medium values in oasis-plain areas, and low values in desert (Caijiahu) and arid mountainous (Beitashan) areas. This study reveals the characteristics of “increasing amount, decreasing days, and increasing intensity” of winter snowfall in Changji Prefecture against a warming and wetting background, providing references for regional water resource assessment and snow disaster prevention.
    Mesoscale Characteristics and Causal Analysis of a Widespread Extreme Thunderstorm Gale Event in Henan Province
    DUAN Zhongxia, ZHU Feng, WANG Fujing
    2025,53(6):854-868, DOI: 10.19517/j.1671-6345.20250128
    [Abstract] (25) [HTML] (0) [PDF 29.31 M] (31)
    Abstract:
    On July 25, 2022, a widespread and extreme thunderstorm gale event suddenly struck Henan Province, with the maximum instantaneous wind force reaching Level 13 and the maximum instantaneous wind speed at 12 national meteorological stations exceeding the historical extreme values for the same period since their establishment. Based on multi-source data, including conventional observation data, FY-4 high-resolution satellite data, dual-polarisation radar data, and minute-level ground observation data, this study analyses the evolutionary characteristics and formation mechanisms of the extreme gale-force winds in this event. The results indicate: (1) The event occurred on the margin of the subtropical high under the background of an eastward-moving trough, which was jointly triggered by surface convergence lines and weak cold air. During the initial stage, strong radiative warming occurred at the surface in the afternoon, combined with the development of warm and moist advection in the lower atmosphere overlapped with the upper-level cold trough, forming a strongly thermally unstable stratification. The upper-dry and lower-moist structure was conducive to the occurrence of thunderstorm gales. During the development and maintenance stage, the eastward movement of the trough led to a significant increase in dynamic lifting, vertical wind shear, and carrying layer wind, which was conducive to the maintenance of gales. (2) This extreme gale event exhibited three distinct stages: In the initial stage, small bow echoes formed by the forward propagation of scattered convection in northwestern Henan, with localised extreme gales first occurring at the rear of these echoes and near supercell storms. During the development stage, the system gradually organised into linear convection in central and western Henan, with extreme gales concentrated in the regions near the apex of the bow echo embedded in the linear convection and the strong divergent regions on its rear. In the maintenance and weakening stage, the linear convection evolved into a larger-scale typical bow echo in central and eastern Henan, with extreme thunderstorm gales appearing sporadically near the locations with the maximum curvature of the bow echo and the hook echoes. Mesocyclones, γ-mesoscale vortices, low-level gale zones, deep radial convergence, and areas of low differential reflectivity factor (ZDR) and low specific differential phase (KDP) had certain indicative significance for the early warning of extreme thunderstorm gales. (3) Strong downdrafts, downward momentum transport, cold pool density currents, and topographic effects were the primary causes of this extreme thunderstorm gale event. In the initial stage, negative buoyancy was the main factor leading to strong downdrafts. During the development stage, the combined dynamic forcing of negative buoyancy, precipitation drag, and γ-mesoscale vortices dominated the formation of strong downdrafts, superimposed with the synergistic effect of downward momentum transport, cold pool density currents, and downdraft divergent airflow, leading to an increase in the intensity and expansion of the extreme gales. In the maintenance and weakening stage, downward momentum transport and cold pool effects were predominant. Additionally, the convergence lines caused by topography significantly promoted the organised development of the convective system, while the superposition of local trumpet-shaped and narrow-tube terrain effects further enhanced the extremeness of near-surface wind speeds.
    Research on Potential Prediction of Cold Cloud Seeding Based on CMA-GFS Model
    SUN Jing, SHI Yueqin, ZUO Dongfei, MAI Rong, AN Yingyu, CHEN Yingying
    2025,53(6):869-879, DOI: 10.19517/j.1671-6345.20250077
    [Abstract] (18) [HTML] (0) [PDF 1.92 M] (20)
    Abstract:
    The implementation of weather modification operations involves the advance planning and deployment of equipment and personnel. If the direction of the weather system and the nature of the cloud formations can be accurately forecasted one week in advance, it plays a significant and meaningful role in the allocation of field operation resources. Supercooled water clouds are the primary targets for weather modification operations such as rain enhancement, rain suppression, and hail suppression. The formation of supercooled water depends on specific environmental conditions, including temperature, humidity, and vertical motion. To support operational forecasting for weather modification, it is necessary to accurately characterise supercooled water and its environmental fields at least one week in advance. Using the temperature and humidity forecast parameters from the CMA-GFS global model, the cloud-top temperatures for different cloud layers are calculated. The CIP (Crystal Icing Potential) algorithm is improved into a supercooled water content potential algorithm. By establishing a relational function between SLW (Supercooled Liquid Water) content and key parameters including temperature, relative humidity, and cloud-top temperature, this enhanced algorithm enables effective identification of SLW potential conducive to precipitation enhancement. A cold cloud seeding potential forecast product with a 168-hour forecast period is developed. The supercooled water potential algorithm is evaluated using both the binary classification method for icing events and the probability of detection (POD) method, incorporating 91 aircraft icing observations. Additionally, the cold-cloud seeding potential forecast results for spring 2024 are validated against 10 weather modification aircraft observations. The results show that the supercooled water potential algorithm effectively represents the likelihood of supercooled water occurrence. Validation of the supercooled water potential algorithm is conducted using 91 aircraft observation cases. When applying a 100% threshold, the icing detection rate reaches 54.5%. The icing detection rate is 97.7% and the no-icing detection rate is 66.0% when using a 15% threshold. The TSS score is 0.74 when the threshold is 25%. The cold cloud seeding potential forecast product is applied during the spring 2024 weather modification operations for rain enhancement. Out of 8 flight cases involving icing, the forecast accuracy is 87.5%, and both the 2 flight cases without icing are accurately predicted. The predictable forecast time ranges between 60 to 168 hours, and the potential reflects the intensity of icing and supercooled water, showing certain advantages over quantitative supercooled water forecasts. This product provides technical support for the process forecasting and operational outlook of weather modification activities up to one week in advance.
    Characteristics of Raindrop Size Distributions for Different Seasons and Precipitation Clouds in Yellow River Delta Nature Reserve
    ZHAO Yong, SHI Qian, LI Jianming, MA Zhaoyue, KONG Wenxiu
    2025,53(6):880-894, DOI: 10.19517/j.1671-6345.20250164
    [Abstract] (20) [HTML] (0) [PDF 4.73 M] (18)
    Abstract:
    To gain an in-depth understanding of the raindrop size distribution (DSD) and microphysical characteristics of precipitation in the Yellow River Delta Nature Reserve, and to better understand the regulatory effects of precipitation on vegetation, hydrology, and ecosystems, we analyse data from 2021 to 2024 collected by precipitation disdrometers and automatic weather stations at the two national basic meteorological stations closest to the northern and southern parts of the reserve. We examine the characteristics of DSDs across different seasons and cloud types (stratiform, convective, and mixed), as well as the relationships between the parameters of the Gamma distribution. The results show that: (1) DSDs exhibit notable spatial and typological differences. In the northern region, precipitation in spring and summer, as well as from stratiform and convective clouds, shows a bimodal distribution, while autumn, winter, and mixed clouds exhibit a unimodal distribution. In contrast, the southern region displays unimodal DSDs across all seasons and cloud types. In both regions, raindrop concentration is dominated by small and medium-sized drops. However, rainfall is primarily contributed by medium and large drops in summer and from convective clouds, whereas small and medium drops play a major role in winter and in stratiform and mixed clouds. (2) The normalised intercept parameter (lgNw) shows a consistent seasonal order of autumn > summer > winter > spring in both regions, while the mass-weighted mean diameter (Dm) follows summer > spring > autumn > winter. For different cloud types, both parameters decrease in the order: convective > stratiform > mixed. Both lgNw and Dm increase with rainfall intensity (R). The increase in R is mainly attributed to an increase in Dm (i.e., a broadening of the drop size spectrum) and, to a lesser extent, to an increase in lgNw (i.e., a higher drop concentration). Convective precipitation in both regions exhibits transitional continental-maritime characteristics. (3) Seasonal variations in the shape (μ) and slope (λ) parameters differ between the two regions: in the north, the order is autumn > winter > spring > summer, while in the south, it is winter > autumn > summer > spring. For cloud types, the order is mixed > stratiform > convective clouds in both regions. Both μ and λ decrease with increasing R. (4) The classic Z-R relationship (Z=300R1.4) performs well for autumn and winter precipitation in the northern region but systematically overestimates rainfall in northern spring and summer, as well as in all seasons in the southern region. To improve quantitative precipitation estimation (QPE) accuracy, we derive localised Z-R relationships: for the northern region, Z=331.4R1.56 is recommended for spring, and Z=276.3R1.48 for the spring-summer-autumn period; for the southern region, Z=413.5R1.54 for spring and Z=339.8R1.45 for the spring-summer-autumn period. These localised relationships significantly reduce estimation errors.
    Characteristics of Cloud Condensation Nuclei Distribution in Liupan Mountains and Its Meteorological Influences
    LI Longyan, CHANG Zhuolin, LUO Run, WANG Xueni, HOU Junxue, MU Jianhua
    2025,53(6):895-904, DOI: 10.19517/j.1671-6345.20250067
    [Abstract] (15) [HTML] (0) [PDF 3.72 M] (19)
    Abstract:
    Using the observation data of cloud condensation nuclei (CCN) under 0.1%, 0.2%, 0.3%, 04%, 0.6%, and 0.8% supersaturations and meteorological data in the Liupan Mountain area from September 2022 to August 2023, this study explores the variation characteristics of CCN in Liupan Mountain and their influencing factors. The results show that, affected by meteorological factors, pollution sources, supersaturation, etc.: (1) The average concentration of CCN in the Liupan Mountain area is 589 cm-3. The number distribution of CCN particles under each supersaturation shows a unimodal pattern. With the increase in supersaturation, the peak particle size of the number of particles increases, and the peak particle size under 0.8% supersaturation is 3.5 to 4.0 μm. The monthly variation of CCN number concentration shows the highest in June and the lowest in February; the diurnal variation shows that the concentration increases in the afternoon and evening. (2) The CCN number concentration is relatively high when the snowfall in the winter half-year is less than 2.5 mm and the rainfall in the summer half-year is less than 0.5 mm; in non-precipitation weather, the CCN number concentration is relatively high when the relative humidity is 30% to 90%, the wind speed is less than 15 m/s, the wind direction is easterly in the winter half-year, and the wind direction is 135° to 180° in the summer half-year. The CCN number concentration mean spectrum in non-snowfall weather in the winter half-year is higher than that in snowfall weather and the summer half-year. (3) When the rain intensity is 1.1 mm·h-1 and 6.7 mm/h, the CCN number concentration reduction rates are 10.16 cm-3·h-1 and 20.11 cm-3·h-1, respectively; by fitting the CCN activation spectra, it is found that the parameter C of the CCN activation spectrum is significantly large in most periods (greater than 1000), and the fitting coefficient k is high (about 0.7 or more), indicating that the area often has obvious continental characteristics.
    Spatio-Temporal Variation of Comfortable Days over China during 1963-2022
    LIU Qiufeng
    2025,53(6):905-914, DOI: 10.19517/j.1671-6345.20240204
    [Abstract] (22) [HTML] (0) [PDF 6.45 M] (22)
    Abstract:
    Human climatic comfort has a significant impact on architectural design, human health, outdoor activities, and so on. Based on the daily average temperature, relative humidity, and wind speed of 1866 meteorological stations throughout China during 1963-2022, the human climatic comfort index is calculated, and the spatial distribution and temporal variation characteristics of comfortable days over China are analysed. The results show that the human climatic comfort level in China is dominated by cold to comfortable levels. The annual comfortable days are 100 days in China during 1963-2022, and the number of comfortable days is the highest in May and June, with 16.7 and 16.4 days, respectively. In terms of spatial distribution, the southeastern region has more annual comfortable days, exceeding 80 days, while the Qinghai-Xizang Plateau has the fewest annual comfortable days, less than 50 days. Under the background of climate change, the increase rate of the annual comfortable days is 1.5 d/10a. It increases most obviously in spring and autumn, while it shows a slight decreasing trend in summer, which has the most comfortable days. The annual comfortable days increase by about 5.8 days in the last 30 years (1993-2022) compared with the first 30 years (1963-1992). The annual comfortable days are on the rise in most parts of China, while they decrease in the central and southern parts of North China, the northern part of East China, and the southern part of South China. On the regional scale, Southwest China has the most annual comfortable days, reaching 133.2 days, mainly concentrated in spring, summer, and autumn. South China follows with 115.4 days, mainly occurring in spring, autumn, and winter. The annual comfortable days in North China, East China, Central China, and Xinjiang Regions are close to 100 days. Northeast China has 83.7 days. Northwest China and Inner Mongolia Region are around 74 days. The Tibet Region has the fewest annual comfortable days, with 6.6 days, only occurring in summer. Northeast China, Xinjiang, and Inner Mongolia regions have more than 60 comfortable days in summer, significantly higher than other regions. On the whole, the average annual comfortable days in all regions increase. Inner Mongolia, Xinjiang, and Northwest China have relatively large increases, while South China, Central China, East China, North China, and Southwest China see smaller increases. Moreover, the number of comfortable days in summer in these regions decreases to varying degrees. In general, climate warming is conducive to improving climatic comfort in China.
    Temporal and Spatial Distribution Characteristics and Impacts of Continuous Rain on Soil Moisture Conditions during Period of Summer Harvesting and Sowing in Jiangsu Province
    REN Yifang, XIANG Ying
    2025,53(6):915-926, DOI: 10.19517/j.1671-6345.20250083
    [Abstract] (26) [HTML] (0) [PDF 4.44 M] (27)
    Abstract:
    Against the backdrop of global warming, understanding the occurrence patterns of continuous rain during the summer harvest and planting period is crucial for avoiding the increasingly frequent risks of continuous rain disasters during the maturation and harvest stages of rapeseed/wheat, as well as the sowing and emergence stages of rice/dryland crops. Using data on meteorology, soil moisture, and crop production progress from 1981 to 2020, this study calculates the continuous rain intensity index based on the start and end times of the summer harvest and planting period and the criteria for determining continuous rain. It establishes the corresponding relationship between the continuous rain intensity index and the increment of 10 cm soil relative humidity and defines the impact levels of continuous rain intensity during the summer harvest and planting period. By employing spatial-temporal statistics and EOF (Empirical Orthogonal Function) methods, the study classifies different regions, decades, intensity levels, and stages to analyse the spatial-temporal distribution characteristics and occurrence patterns of continuous rain during the summer harvest and planting period in Jiangsu Province. The results show that, in terms of time, the number of continuous rain occurrences in southern, central, and northern Jiangsu is 0.38 times/year, 0.72 times/year, and 0.98 times/year, respectively. The high-incidence period is concentrated in 2010-2020, with the occurrence intensity showing an upward trend of 0.15-0.25 per decade. The periods of strong occurrence are concentrated in 2001-2020, and mild, strong, extra strong continuous rains mostly occur in late May-early June and late June. In terms of space, the frequency and intensity of continuous rain show a pattern of “more in the south and less in the north” and “lighter in the north and heavier in the central and southern regions.” The number of occurrences of continuous rain at all intensity levels follows the order: southern Jiangsu > central Jiangsu > northern Jiangsu. In terms of typical years, the intensity of continuous rain in the Lixiahe region of Jiangsu is the strongest in 2003, 2015, and 2020; the intensity is relatively strong in the north-central part of the area between the Yangtze and Huaihe Rivers in 2003, 2006, and 2012; and the intensity is relatively strong in the central part of southern Jiangsu in 2003, 2015, and 2020. In actual production, focus should be placed on the frequent and severe occurrence regions and periods of continuous rain during the summer harvest and planting period, so as to scientifically prevent farmland waterlogging, optimise the allocation of agricultural machinery and equipment, and rationally achieve risk transfer.
    Research on Seeding AgI Agent Technologies Using Turbojet Engines
    YANG Bixuan, TIAN Xian, QIAO Yougang, LIU Lili, WEI Jiajia, WANG Xiaojun, HE Xiangyong
    2025,53(6):927-934, DOI: 10.19517/j.1671-6345.20250110
    [Abstract] (23) [HTML] (0) [PDF 20.51 M] (29)
    Abstract:
    To enhance the silver iodide (AgI) seeding capability of the catalytic operation aircraft, this paper proposes a method that utilises the high-temperature, high-speed exhaust flame of a turbojet engine for efficient AgI seeding agent combustion and seeding. Based on theoretical and simulation analysis, a systemic architecture integrating storage, delivery, combustion, and control is designed, and a prototype is developed. A specialised seeding agent formulation with 40% AgI content is developed to adapt to the exhaust flame environment. Ground tests are conducted to evaluate the seeding agent’s stable combustion within the exhaust flame, the particle size distribution of the generated aerosols, and their ice-nucleating ability in a cloud chamber. The results show that this technology generates sub-micron-sized (less than 0.5 μm) artificial ice nuclei. Both the ice nucleus concentration and the ice formation efficiency meet operational requirements and are comparable to the performance of conventional AgI flares. This technology significantly improves effective payload and seeding efficiency, offering a new technical approach for UAV (unmanned aerial vehicle)-based weather modification operations.
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    Climatic Condition Analysis of Flos Lonicerae Planting in Yuepuhu of Xinjiang
    Kerimu ABASI, Nu’erpatiman MAIMAITIREYIMU, MENG Fanxue, Patiman ABUDUAINI, XIE ye, Kanjiguli WUSHOU’ER
    2020,48(6):917-922, DOI:
    [Abstract] (1399) [HTML] (0) [PDF 1.07 M] (66228)
    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.
    Research and Development of Three-Dimensional Cloud Merging Analysis Operation System (3DCloudA V1.0) in China
    ZHU Zhi, SHI Chunxiang, LIU Ruixia, ZHANG Tao, GU Junxia
    2021,49(1):55-62, DOI:
    [Abstract] (1354) [HTML] (0) [PDF 11.58 M] (65380)
    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〗
    Assimilation of Retrieved Winds from Single Doppler Radar over Low Latitude Plateau
    Li Huahong, Cao Jie, Wang Man, Hu Juan, Min Ying
    2014,42(5):823-831, DOI:
    [Abstract] (2108) [HTML] (0) [PDF 2.17 M] (62072)
    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.
    Characteristics of Ancient Building Lightning Disasters
    Zhang Huaming, Yang Shigang, Zhang Yijun, Lu Xi, Li Yunfei, Tao Biao
    2013,41(4):758-763, DOI:
    [Abstract] (2426) [HTML] (0) [PDF 26.87 M] (61879)
    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.
    Design and Implementation of an Online CLDAS Data Quality Assessment System
    Li Xianfeng, Shi Chunxiang, Hu Jiajun, Han Shuai, Jiang Zhiwei
    2017,45(6):1116-1124, DOI:
    [Abstract] (1623) [HTML] (0) [PDF 2.65 M] (50865)
    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.
    Analysis of Detection Capability of CINRAD/SA Using Negative Elevation Angle
    Zhang Yangcheng, You Wenhua, Gao Xiangyu, Cheng Hui, Liu Xiang
    2013,41(1):15-19, DOI:
    [Abstract] (2897) [HTML] (0) [PDF 12.84 M] (32241)
    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.
    Causal Analysis of an Unusual Winter Heavy Fog in 2006
    Lei Zhengcui, Xia Wenmei, Zhou Linhua, Qian Wei, Zhang Duanyu
    2010,38(3):289-294, DOI:
    [Abstract] (3042) [HTML] (0) [PDF 63.01 M] (31058)
    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.
    Contrast Analysis of Two Heavy Snowfall/Snowstorms in Hebei Province
    Zhao Bin, Zhao Cuiping, Yan Jusheng, Ma Xiaoshan, Feng Tianqing
    2010,38(3):281-288, DOI:
    [Abstract] (2635) [HTML] (0) [PDF 57.54 M] (30293)
    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.
    Characteristics of a Cloud to Ground Lightning Event during a Large Scale Strong Storm
    Pan Yaying, Wang Yayun, Qian Wugang, Huang Xinqing, Den Xiajun
    2010,38(4):432-436, DOI:
    [Abstract] (2528) [HTML] (0) [PDF 13.24 M] (25503)
    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.
    Advances in Soil Moisture Retrieval Using Passive Microwave Remote Sensing
    Wang Lei, Wen Jun, Zhong Tangtang, Liu Rong, Liu Yuanyong
    2009,37(1):67-73, DOI:
    [Abstract] (3071) [HTML] (0) [PDF 788.79 K] (23276)
    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.
    Observation and Analysis of a Flash Heavy Rain Event Caused by Collision of Gust Fronts
    SU Lei, CHEN Guoqing, WU Fulang, LIANG Qiufeng, HU Kaiwen
    2024,52(3):380-391, DOI: 10.19517/j.1671-6345.20230246
    [Abstract] (490) [HTML] (0) [PDF 14.80 M] (20569)
    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.
    Study on Influence of Dam Elevation on Wind Field Characteristics Near Dam in Canyon Area
    SONG Wenwen, SHI Yicheng, TAO Li, ZHENG Hao
    2024,52(3):446-455, DOI: 10.19517/j.1671-6345.20230140
    [Abstract] (492) [HTML] (0) [PDF 17.35 M] (20568)
    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.
    The Design and Implementation of Guizhou Meteorological Comprehensive Monitoring System Based on Mobile APP
    BAI Tienan, TAN Haibo, JIN Shisheng, TANG Weiyao, GUO Xi, LIU Guoqiang, LIAO Tingting
    2024,52(3):347-355, DOI: 10.19517/j.1671-6345.20230189
    [Abstract] (550) [HTML] (0) [PDF 11.03 M] (20562)
    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.
    Application of Relief Shading Method in Meteorological Model Data Visualization
    WO Weifeng, WANG Yan, ZHAO Changyu, XU Rong, XU Difeng
    2024,52(3):318-329, DOI: 10.19517/j.1671-6345.20230129
    [Abstract] (495) [HTML] (0) [PDF 75.13 M] (20450)
    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.
    Research on Pre-processing Method of Meteorological Remote Sensing Image Denoising
    ZHAO Libin, LIU Hao, MA Guozhong, GUO Yingru, HE Zheng, WANG Yue
    2024,52(3):309-317, DOI: 10.19517/j.1671-6345.20230123
    [Abstract] (626) [HTML] (0) [PDF 8.58 M] (20287)
    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.
    Risk Assessment and Pre-assessment of Refined Rainstorm and Flood Disaster in Liaoning Province
    AO Xue, ZHAI Qingfei, ZHAO Chunyu, ZHOU Xiaoyu, CUI Yan, LI Jingwei, LING Mingqian
    2024,52(3):403-414, DOI: 10.19517/j.1671-6345.20230186
    [Abstract] (580) [HTML] (0) [PDF 25.35 M] (20228)
    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.
    Comparative Analysis between FY-4A/LMI Lightning Data and Three-Dimensional Lightning Data in Zhejiang Province
    ZHANG Yi, BIAN Xuewen, XU Zhenyu, WANG Kangting, WANG Fang
    2024,52(3):424-433, DOI: 10.19517/j.1671-6345.20230152
    [Abstract] (579) [HTML] (0) [PDF 9.05 M] (20188)
    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.
    Evaluation of CINRAD/CC Radar Hail Detection Algorithm and Parameter Localization in Pu’er on ROSE2.0
    CHEN Zhuo, GUO Xiaomei, YAO Ziwei, ZHOU Baopeng, DUAN Wei
    2024,52(3):330-339, DOI: 10.19517/j.1671-6345.20230166
    [Abstract] (774) [HTML] (0) [PDF 1.48 M] (19934)
    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.
    Application and Verification of Probabilistic Forecast of Precipitation During Super Long Meiyu Season in 2020
    YAO Mengying, LOU Xiaofen, LIU Xueqing, QIU Jinjing
    2024,52(3):367-379, DOI: 10.19517/j.1671-6345.20230172
    [Abstract] (472) [HTML] (0) [PDF 13.77 M] (19911)
    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.
    Research on Optimization of Docker Scheduling Performance for Simulation Environment of Meteorological Big Data Cloud Platform
    WU Peng, HAN Tongxin, CHEN Shiwang, NIE Yuanding, ZHENG Xiaozhi
    2024,52(3):340-346, DOI: 10.19517/j.1671-6345.20230182
    [Abstract] (462) [HTML] (0) [PDF 2.24 M] (19872)
    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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    Design of RHI/PPI Scan Mode of CINRAD/SA Radar
    Meng Zhaolin Wang Ping Lu Yaping Wang Hongyan
    2004,32(4):251, DOI:
    [Abstract] (6494) [HTML] (0) [PDF 423.81 K] (6270)
    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.
    Variation Characteristics of Sunshine Duration in Chengdu in Recent 50 Years
    Chen Bihui, Zhang Ping, Hao Kejun, Luo Lei
    2008,36(6):760-763, DOI:
    [Abstract] (6063) [HTML] (0) [PDF 464.40 K] (5961)
    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.
    Regionalization of Grassland Climate Characteristics and Ecotypes in Inner Mongolia
    Chen SuHua;Gong ChunNing
    2005,33(4):340-344, DOI:
    [Abstract] (4802) [HTML] (0) [PDF 146.22 K] (7778)
    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.
    Observational Experiment on Spatial-Temporal Distribution of Soil Resistivity in Ningxia
    Liu Chunquan, Hou Junxue, Zhang Wei
    2008,36(4):474-479, DOI:
    [Abstract] (4767) [HTML] (0) [PDF 650.10 K] (5507)
    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.
    Comparative Analysis of NCEP/NCAR, ECMWF and JMA Reanalysis
    Deng Xiaohua, Zhai Panmao, Yuan Chunhong
    2010,38(1):1-8, DOI:
    [Abstract] (4201) [HTML] (0) [PDF 988.69 K] (8613)
    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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