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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    FY-4A/AGRI Sea Surface Temperature Retrieval Method Based on Deep Learning
    ZHOU Lina, CUI Peng, SUN Anlai, LIANG Yonglou, ZHANG Naiqiang
    2025,53(2):153-166, DOI: 10.19517/j.1671-6345.20240135
    [Abstract] (68) [HTML] (0) [PDF 20.87 M] (83)
    Abstract:
    Sea surface temperature (SST) is an important parameter for ocean and atmospheric forecasting systems and climate change research. The National Satellite Meteorological Centre (NSMC) develops the Fengyun-4A (FY-4A)/AGRI (advanced geostationary radiation imager) SST products using the split-window nonlinear SST (NLSST) algorithm. However, the traditional regression algorithm is difficult to meet the needs of higher accuracy SST retrieval. To solve this problem, this paper proposes a FY-4A/AGRI sea surface temperature retrieval method based on deep learning, aiming to improve the retrieval accuracy of SST and provide more accurate data support for meteorological research. FY-4A/AGRI satellite data, SST climatology data, and in situ SST observations are used to construct the retrieval dataset according to quality control standards and spatio-temporal matching rules. The NLSST algorithm is used to select features, including 10.7 μm band brightness temperature, 12 μm band brightness temperature, satellite zenith angle, and SST climatology data. According to the ratio of 8∶2, the feature data are divided into a training dataset and a validation dataset, which are used for training and validation respectively. A SST retrieval model based on a deep neural network is obtained through experiments. Finally, the FY-4A/AGRI satellite data are retrieved by the DNN model to generate SST products. The model-retrieved SST products are evaluated from two dimensions of accuracy and long-term series stability based on in situ SST, and also compared with the FY-4A/AGRI official SST products. By applying the quality levels of FY-4A/AGRI official SST products to the model-retrieved SST products, the performance of model-retrieved SST products under different quality levels (excellent, good, and bad) in three periods of day, night, and dawn is analysed. The statistical results show that when the quality level is excellent, the mean bias of the model-retrieved SST products is -0.19 ℃, the root mean square error (RMSE) is 0.67 ℃, and the correlation coefficient reaches 0.992. However, the mean bias of FY-4A/AGRI official SST products is -0.49 ℃, the RMSE is 0.99 ℃, and the correlation coefficient is 0.985. The mean bias and RMSE of the model-retrieved SST products are 0.3 ℃ smaller than those of the FY-4A/AGRI official SST products, and the correlation coefficient also indicates a good correlation between the model-retrieved SST products and in situ SST. In addition, the temporal stability of the model-retrieved SST products over an extended period outperforms that of the FY-4A/AGRI official SST products. This study provides a new approach for the SST retrieval from the next-generation geostationary satellite.
    Application of Three-Cornered Hat Method to Evaluate Errors of Temperature and Humidity Profiles Derived from Various Satellites
    ZHANG Yue, GAO Yudong, REN Suling
    2025,53(2):167-176, DOI: 10.19517/j.1671-6345.20240161
    [Abstract] (40) [HTML] (0) [PDF 3.15 M] (43)
    Abstract:
    The global atmospheric temperature and humidity profiles are key datasets for studying extreme weather and climate change. However, the atmospheric profiles derived from satellite measurements include multiple error sources, such as instrument error, errors of retrieval algorithms, and quality control. Therefore, evaluating the errors of atmospheric profiles accurately is beneficial to understanding the features of derived atmospheric profiles and applying them in operations and research. The Three-cornered Hat (3CH) method, using the error model of Xi=truth+b+ei, estimates the errors of various datasets by solving linear equations. Unlike the single data evaluation method, the 3CH method uses uncorrelated datasets and does not assume that any reference dataset is error-free. In this study, the errors of atmospheric temperature and humidity profiles derived from the Fengyun-3D polar-orbiting satellite (FY-3D), the Suomi National Polar-Orbiting Partnership (NPP), and the Constellation Observing System for Meteorology, Ionosphere and Climate 2 (COSMIC2) in 2021 are evaluated by the 3CH method. The differences between the 3CH method and the single data evaluation method, using ECMWF Reanalysis v5 (ERA5) as the reference dataset, are also discussed. The results show that: (1) The errors of three temperature and humidity profiles present similar vertical distributions. Especially around 700-300 hPa, the errors of all temperature profiles are less than 2 K, illustrating all temperature profiles are consistent and accurate in the middle and lower troposphere. In comparison of three humidity profiles, the FY-3D and NPP profiles present the largest and smallest errors, respectively. (2) Compared with all-sky situations, the errors of temperature and humidity profiles derived from FY-3D decline obviously in clear-sky situations. The differences in NPP profile errors between all-sky and clear-sky are very small, illustrating the effects of clouds on NPP profiles are minute. The COSMIC2 profile errors become a little larger at lower layers, because the occultation observation is affected by the super-refraction phenomenon over the ocean. (3) The errors estimated by the 3CH method are different from the results estimated by the ERA5 dataset, because the error of the ERA5 dataset and the correlations between three atmospheric profiles and the ERA5 dataset are included in the 3CH method. For the COSMIC2, the errors of temperature and humidity profiles estimated by the 3CH method increase by about 0.4 K and 0.3 g kg-1 in the lower troposphere, respectively. In contrast, the errors of FY-3D and NPP profiles estimated by the 3CH method become smaller, which are more accurate than the results estimated by the ERA5 dataset.
    Applicability Analysis of FY-4A Land Surface Temperature Products in Guangxi Region
    LIU Jiang, MA Jun, LIN Jianling, LI Yanping, HUANG Jie, LI Yeqing
    2025,53(2):177-190, DOI: 10.19517/j.1671-6345.20240187
    [Abstract] (40) [HTML] (0) [PDF 17.78 M] (64)
    Abstract:
    Land surface temperature (LST) plays a critical role in the water cycle and energy balance at global and regional scales. Large-scale LST estimates can be obtained from satellite observations; however, there are still uncertainties and challenges in the applicability of LST retrieval based on satellite data. In this study, to assess the accuracy and applicability of LST products from the Advanced Geostationary Orbit Radiation Imager (AGRI) based on the Fengyun-4A (FY-4A) satellite in the Guangxi region, the FY-4A LST products are compared with the Moderate Resolution Imaging Spectrometer (MODIS) LST products, the surface temperature (0 cm) observed by 91 meteorological stations, and the surface temperature measured by a thermal infrared radiometer. By calculating statistical indicators such as bias, root mean square error, and correlation coefficient, the difference between two sets of remote sensing LST products and their potential relationship with surface conditions are comprehensively analysed, and the consistency between FY-4A LST products and ground-observed LST is deeply evaluated. In addition, a standardised anomaly analysis method is used to evaluate the monitoring ability of FY-4A LST products and station-observed LST on high-temperature and cold-wave events. The results show that the average difference in temperature between FY-4A LST and MODIS LST is about 2 ℃, and significant differences occur in areas with high elevation and sparse tree coverage. The correlation coefficients of the time series between FY-4A LST and MODIS LST exceed 0.9 in most areas. It is also found that there is a good consistency in temporal change between the FY-4A LST products and the LST obtained by the two ground observations. However, the FY-4A LST products exhibit systematic underestimation bias compared with the ground-observed LST due to the difference in observation methods, especially in the afternoon. Based on case analyses of extreme weather events such as high temperatures and cold waves, the FY-4A LST products have a close temporal and spatial relationship with the standardised anomalies of the station-observed LST, which can monitor large areas of abnormal temperature signals with standardised anomalies >2. In general, FY-4A LST products show good monitoring capabilities and applicability in the Guangxi region, especially in supplementing the observation of surface temperature in remote mountainous areas with sparse station distributions. The results of this study demonstrate that satellite observations can comprehensively characterise the spatio-temporal variation of the LST and allow us to better use satellite-based LST products in response to changing climate in the future.
    Experimental Study on Automatic Recognition of Freezing Rain by Random Forest Machine Learning Method
    WANG Xiaolan, QIU Jianhua, LI Cuicui, TAO Fa, LIANG Jingshu, QIN Jianfeng
    2025,53(2):191-200, DOI: 10.19517/j.1671-6345.20240255
    [Abstract] (45) [HTML] (0) [PDF 20.51 M] (40)
    Abstract:
    There is still a lack of automatic monitoring for freezing rain in the current meteorological observation field. The Random Forest (RF) machine learning method is introduced here, and an automatic recognition method for freezing rain is established using the data from Ka-band Millimetre-Wave Cloud Radar (MWCR). This provides a possibility to make up for the lack of automatic recognition and continuous observation of freezing rain. Firstly, the distribution characteristics of echo intensity and skewness values of Ka-band MWCR with different precipitation phenomena (rain, freezing rain, snow, and mixed rain and snow) during two freezing weather processes occurring in the Wuhan area in February 2024 are analysed. Significant differences in the value range and vertical height distribution are found. Then, echo intensity, skewness values, and near-surface temperature are determined as identification variables. Automatic recognition models for freezing rain using the RF machine learning method are established for several freezing processes in Wuhan and Guizhou respectively. After training and verification calculations, the test recognition accuracy rate (Acc) exceeds 90%, and the freezing rain hit rate (Pod) exceeds 80%. Independent freezing rain examples are used for verification, and the verifying Acc reaches 80%. Compared with wire icing observation, this method can automatically and continuously identify freezing rain phenomena in minutes, which is also feasible for business application. Since the echo intensity and skewness values of MWCR during the freezing rain process have obvious regional characteristics, freezing rain sample data from different regions should be collected to establish recognition models for different regions. The recognition accuracy can be improved by expanding samples and optimising model parameters and indicators, as well as reducing the False Alarm Rate (Far).
    Research and Application Analysis of Lightning Proxy Radar Echo in Different Geomorphic Regions
    ZHOU Wei, WEI Qing, ZHAO Xuan, WANG Binyan, ZHANG Wulong, ZHOU Changchun
    2025,53(2):201-210, DOI: 10.19517/j.1671-6345.20240102
    [Abstract] (30) [HTML] (0) [PDF 3.69 M] (37)
    Abstract:
    This study delves into the relationship between lightning frequency and radar echo intensity across three distinct geomorphological regions in Sichuan Province (Sichuan Basin, Western Sichuan Plateau, and Panxi Region) based on lightning and radar echo data from 47 typical thunderstorm events occurring from June to August in 2020 and 2021. Employing boxplot analysis and logarithmic fitting methods, the study selects the maximum echo value within 0.03°×0.03° grid points from SWAN radar echo mosaics as the fitting factor for radar echoes and establishes a specific time window to accumulate lightning frequencies, thereby constructing a comprehensive sample dataset. The results reveal that the median and mean values of lightning frequency and radar echo intensity are relatively close in all three regions, with a generally symmetric data distribution. As lightning frequency increases, echo values tend to converge with reduced dispersion. Despite setting a minimum echo intensity threshold, the span of echo intensities corresponding to lightning frequencies in the Sichuan Basin remains relatively wide. A logarithmic distribution function is adopted to fit lightning frequency and radar echo, yielding satisfactory results in the Sichuan Basin and Western Sichuan Plateau, particularly in the Sichuan Basin where the goodness-of-fit for both the median and mean echo values versus lightning frequency reaches 0.909, indicating a strong correlation and high-precision fit. Conversely, the fit in the Panxi Region is less satisfactory, suggesting a weaker correlation between radar echo values and lightning frequencies in this area. The study further observes that as lightning frequency increases, the median and mean fitting curves of radar echo values in all three regions initially rise rapidly before levelling off, albeit with regional variations. These findings not only uncover the intricate relationship between lightning frequency and radar echo intensity but also provide a scientific basis for regional lightning warning and monitoring. From the perspective of individual case validation of fitted echoes, the fitting results in these three regions exhibit a tendency towards underestimation, likely due to the relatively low grid-point lightning density frequency used in calculations to reduce dispersion and ensure data stability. Nevertheless, the proxy echoes still accurately reflect high-value centre information consistent with observations, which holds significant value for thunderstorm forecasting and warning as well as the application of lightning data. In the future, further validation through more individual cases can be conducted to optimise the fitting algorithm, formula, and method, thereby enhancing the fitting results. Additionally, the fitting formula can be incorporated into model experiments to explore its application effects in different topographical and geomorphological regions.
    Study on Trends of Extreme Temperature in China Considering Data Homogenization and Autocorrelation
    HU Yichang
    2025,53(2):211-221, DOI: 10.19517/j.1671-6345.20240199
    [Abstract] (32) [HTML] (0) [PDF 5.15 M] (33)
    Abstract:
    China frequently experiences extreme temperature events, which often have severe impacts on social production and daily life. Therefore, it is of great importance to study the long-term trends of extreme temperature changes. The homogenisation of the observation dataset is crucial for detecting temperature change trends. In the meantime, whether to consider time series autocorrelation can also affect the detection results. Failure to consider the homogenisation of the temperature dataset or the autocorrelation of the temperature time series brings about uncertainty in research conclusions. In addition, the higher the spatial coverage of observation sites, the more advantageous it is to reveal spatial differences in change characteristics. This study analyses the trends of extreme temperature changes in China during the period of 1961-2021 using a homogenised daily station temperature dataset with the most spatial coverage currently, while taking into account the impacts of time series autocorrelation. For China as a whole, the annual warm nights (days), where daily minimum (maximum) temperature is above its 90th percentile, have an increasing trend of 10.3 (5.9) d/10a, while the annual cold nights (days), where daily minimum (maximum) temperature is below its 10th percentile, have a decreasing trend of -7.8 (-3.6) d/10a on space average, respectively. The warming rates of the annual coldest night (TNn), warming night (TNx), coldest day (TXn), and warmest day (TXx) are 0.52, 0.30, 0.30, and 0.21 ℃/10a on space average, respectively. For the regional average time series of extreme temperature in China, the percentage differences between the original trend and the decorrelation trend are all less than 5%. For a single station, the impact of time series autocorrelation on the magnitude of long-term linear trend is less than 10% for most stations, but there are also some stations with impacts exceeding 50%. There are great differences between extreme temperature changes and average temperature changes. For example, although the summer warming trend is the weakest in terms of the regional average minimum and maximum temperatures in China, the increasing trend of the regional average warm nights and warm days is the strongest during summer, while the increasing trend is the weakest during winter. With higher spatial coverage of station datasets, this study reveals more details of extreme temperature changes in China. For example, TXx shows an especially pronounced warming trend in urban agglomerations such as the Yangtze River Delta, Pearl River Delta, Beijing-Tianjin-Hebei, and Chengdu-Chongqing. Further research is needed to determine whether this is related to urbanisation.
    Analysis of Characteristics and Cause of a Missing-Forecast Extreme Thunderstorm Gale Weather Process Based on Multi-source Observation Data
    LI Guocui, WU Chong, QIAN Weimiao, Duan Yuhui, Cao Yue
    2025,53(2):222-234, DOI: 10.19517/j.1671-6345.20240143
    [Abstract] (43) [HTML] (0) [PDF 21.57 M] (67)
    Abstract:
    There was an extreme thunderstorm gale weather event that occurred in central Hebei Province on 24 July 2023, which was missed in forecasting. The maximum wind speed at 6 national observation stations broke the record for the maximum value or ranked in the top two, with the maximum wind speed being 30.6 m/s, which appeared at the Yuanshi station. The large-scale weather background of this event was the weak northwest wind at the upper air weather chart, and the weather system was not obvious, which led to the failure of forecasting the thunderstorm gale disaster in the middle and short-term weather forecast. Using ERA5 reanalysis data, dual-polarisation weather radar, wind profile radar, L-band radiosonde, minute-level ground encryption observation station data, and other multi-source high spatial and temporal resolution observation data, the evolution characteristics and causes of the extreme thunderstorm gale weather event are analysed. The results show that: (1) The process of thunderstorm wind belonged to the high-altitude dry and cold advection weak forcing type, and there was an unstable atmospheric junction of low-level warm and upper-altitude weak cold. The CAPE value was 1544.8 J/kg, SI was -4.31 ℃, and the temperature difference between 850 hPa and 500 hPa exceeded 30 ℃, with the vertical wind shears of 0-3 km and 0-6 km being moderate-to-slightly weak. (2) The wind speed of the single-peak and the first stage of the double-peak were characterised by strong sudden onset, large instantaneous wind speed, and short duration. The corresponding radar echoes of the convection system included three categories: storm cells, bow echoes, and gust front, which were characterised by ZDR column, KDP column, low CC value, large wind core above 17 m/s, velocity ambiguity, and radial convergence of 3-8 km in the middle layer. The surface meteorological elements were thunderstorm high pressure with centre pressure above 1006 hPa and surface cold pool with temperature variations of one hour less than -3.5 ℃, corresponding to the steep rise of pressure, the sudden drop of temperature, the valley value of zero layer height, and weak precipitation. Compared with the first stage, the wind in the second stage of the double-peak type was significantly weaker, with a smaller impact range and a short duration, accompanied by no precipitation or only weak precipitation, corresponding to the weak radar echo type, which was caused by the regenerative weak echo after the main radar echo and the cold pool density current. (3) Extreme winds were also related to the new relocation station with few obstacles.
    Comparative Analysis of Characteristics and Water Vapor Sources of Two Different Types of High-Impact Fog Processes
    2025,53(2):235-246, DOI: 10.19517/j.1671-6345.20240208
    [Abstract] (28) [HTML] (0) [PDF 21.29 M] (40)
    Abstract:
    Two high-impact processes of advection fog on 31 December 2021 and radiation fog on 19 January 2022 occurred in Hunan. Using conventional weather observations, highway disaster data, and NCEP reanalysis data, the weather background, meteorological elements, physical quantity fields, their effects on highways, and the water vapour source of HYSPLIT backward trajectory simulation of the two processes are compared and analysed. The results show that during the two fog processes, the middle and high latitudes of 500 hPa show a circulation situation of two troughs and one ridge, there are multi-layer inversions, the atmospheric stratification is stable, and the relative humidity of the ground is above 98%. In terms of water vapour transport, there is a rapid sinking transport of water vapour in the north. The main and strongest water vapour transport in the near-surface channel is a short-distance and slow-moving channel entering Hunan through the mountainous area of western Hubei, and the contribution rate of water vapour flux accounts for more than 50%, indicating that the continuous and slow infiltration of cold and wet air near the ground layer is conducive to the cooling and condensation of the gas block to form droplets. There are obvious differences in the low-level, ground situation and meteorological elements during the two heavy fog processes. The first advection fog process has a strong warm advection development at 700-600 hPa, and the ground is controlled by weak cold high pressure, accompanied by the thickening of the inversion layer. The second radiation fog process is controlled by the northerly airflow behind the trough at 500 hPa, and the ground is a weak pressure field. During the fog, the whole layer turns to cold advection. The temperature during the advection fog process is lower than that during the radiation fog process. There are obvious differences in water vapour sources and the height of water vapour channels between the two processes. The radiation fog transports cold air in the northern channel, two in the upper and two in the lower layers. The dry cold air is quickly transported to the fog area with two high-level water vapour channels, and the wet cold air is slowly transported to the fog area with two low-level channels. The water vapour channels of advection fog input half from the north and half from the south. The southern channel transports warm and humid air, and the northern channel transports cold air. The analysis and research results are helpful for forecasters to improve the accuracy of forecasting and early warning of two types of fogs. At the same time, it provides a reference for the precise control of fog weather in the transportation department.
    Distribution Characteristics and Forecast Diagnosis of Supercooled Water in Precipitating Stratiform Clouds in Shanxi Province
    YANG Xiao, SUN Hongping, LI Peiren, YANG Junmei, HAO Kui
    2025,53(2):247-258, DOI: 10.19517/j.1671-6345.20240167
    [Abstract] (37) [HTML] (0) [PDF 5.52 M] (40)
    Abstract:
    Supercooled water is a crucial parameter for assessing the potential for weather modification in stratiform clouds. Utilising data from 32 aircrafts detected by the Airborne Meteorological Detection Device from 2017 to 2022, we conduct a statistical analysis of the altitude characteristics where supercooled water is present, along with temperature, humidity, vertical wind speed, and other atmospheric parameters. We also examine the variation of supercooled water content in relation to these environmental factors. Based on these findings, we develop a diagnostic forecasting method for supercooled water content in clouds over the Shanxi region. The study reveals the following insights: (1) The supercooled water content obtained by the Airborne Meteorological Detection Device shows good agreement with the liquid water content detected by the Cloud Particle Probe (when the temperature is below 0 ℃, the liquid water content detected by the CDP is the supercooled water content), which indicates that both instruments are better at detecting the supercooled water content in the cloud. (2) The supercooled water content predominantly ranges from 0.06 to 0.22 g·m-3, with an average value of 0.18 g·m-3. Its probability density function (PDF) exhibits a distinct single-peaked normal skewed distribution, and the cumulative distribution function (CDF) growth rate decreases as the supercooled water content increases. (3) The supercooled water region is predominantly found between 3589 and 4667 metres, approximately 1011 to 2316 metres above the 0 ℃ isotherm. The temperature range is from -8.52 ℃ to -3.52 ℃, humidity levels vary between 86.68% and 100%, and the supercooled water area is predominantly influenced by updrafts. (4) The supercooled water content tends to increase with decreasing altitude from the 0 ℃ isotherm, rising temperature, increasing relative humidity, and stronger updrafts within the clouds. (5) The relationships between the content of supercooled water and various factors such as temperature, relative humidity, altitude above the 0 ℃ isotherm, and vertical wind speed are determined through polynomial fitting. The analysis reveals that the inversion magnitude is substantial when the supercooled water content is low, and conversely, it is minimal when the content is high. However, when considering the overall distribution, there is a distinct positive correlation between the two variables. The retrieval results for six cases outside the statistical sample suggest that some supercooled water is also forecasted during periods when it is actually detected, with the trends of the two being largely consistent and accuracies exceeding 65%. However, the forecasted values are slightly higher than the observed values. This diagnostic method for forecasting supercooled water can, to a certain extent, qualitatively assess the magnitude of supercooled water content under specific conditions, locate areas rich in supercooled water, and offer guidance for the scientific advancement of artificial weather modification operations.
    Temporal and Spatial Evolution of Soil Moisture in Yunnan and Surrounding Areas and Its Correlation with Environmental Factors
    ZHAO Pingwei, WANG Jiani, ZHANG Yunqiu, ZHAO Jianping, YOU Wenlong, LI Silan
    2025,53(2):259-270, DOI: 10.19517/j.1671-6345.20240074
    [Abstract] (38) [HTML] (0) [PDF 23.54 M] (39)
    Abstract:
    In order to enhance the understanding of the spatiotemporal evolution of soil moisture in the subtropical monsoon climate region, the study focuses on Yunnan and its surrounding areas (90°-107°E, 15°-30°N). Utilising ERA5-Land reanalysis soil moisture data and employing various statistical methods such as Theil-Sen Median trend analysis and Mann-Kendall (M-K) non-parametric test, this research analyses the spatiotemporal variations of soil moisture in the Indochina Peninsula and its response to hydrothermal changes, exploring the responses of different soil moisture levels to climate change. The results indicate: (1) During the study period (1950-2020), the study area experiences alternating dry and wet soil moisture conditions, with drier years concentrated in 1955-1961 and 2001-2020, and wetter years mainly distributed in 1951-1954, 1961-1968, and 1971-1978. After entering the 21st century, soil drying becomes more pronounced, with positive anomalies in soil moisture at different depths from January to December, and a stronger drying trend during the dry season for SM1 to SM3. (2) Between 1950 and 2020, there is a clear dry-wet axis in the study area’s soil moisture, with the difference between the dry and wet axes decreasing with depth, and a trend of narrowing dry axis bands and expanding wet axis bands. (3) In the first and last years of the study period, soil moisture remains stable in most regions of the study area, with only 21.4% to 26.2% of the area experiencing drying, primarily transitioning from the (0.4, 0.45］ interval to the (0.35, 0.4］ interval. (4) There is significant spatial heterogeneity in soil moisture changes at different levels, with an overall weak drying trend. Of the area, 37.7% to 61.5% experiences soil moisture changes ranging from -0.001 to 0 m3·m-3·10a-1, and areas with increasing soil moisture are less than 20%. (5) After entering the 21st century, soil moisture in most months of the dry season becomes drier compared to earlier periods, with abrupt changes occurring in 2003 and 2008. (6) The temporal-latitudinal mean high-value centre of soil moisture extends with the increase in soil depth, and the high-value centre of soil moisture expands northward (eastward); the overall variation in soil moisture increases with latitude (longitude), and the seasonal differences in soil moisture decrease with depth and latitude (longitude). (7) The impact of evapotranspiration, precipitation, soil temperature, and Normalised Vegetation Index (NDVI) on soil moisture has a lag of 1 to 5 months. Apart from the negative correlation with NDVI, soil moisture is significantly positively correlated with the other three climate factors. Soil moisture is synergistically influenced by environmental factors, among which precipitation has the strongest impact on soil moisture.
    Characteristics of Phenological Changes of Nilaparvata Lugens and Its Response to Climate Change in Quanzhou, Guangxi from 1979 to 2023
    TANG Guangtian, HUANG Yixuan, ZOU Lixia, LI Binglan, HUANG Guojing, MO Yanwen
    2025,53(2):271-284, DOI: 10.19517/j.1671-6345.20240195
    [Abstract] (25) [HTML] (0) [PDF 2.67 M] (33)
    Abstract:
    Based on the data of brown planthopper (Nilaparvata lugens (Stal)) and meteorological factors including temperature and precipitation in the Quanzhou region of Guangxi Province from 1979 to 2023, this study utilises Sen's slope, wavelet analysis, M-K trend, and mutation testing to analyse variation characteristics of the Nilaparvata lugens's phenological periods and its response to climate change in this region over the past 45 years. The results show that the initial appearance date shows an early trend at a rate of 0.43 days per year (p<0.05), and the final disappearance date and residence time show a delayed or prolonged trend at rates of 0.42 days per year and 0.85 days per year (p<0.01) respectively. No variation occurs in the phenological periods, and they remain relatively stable over time. The initial appearance date, final disappearance date, and duration of stay undergo mutations in 2009, 2003, and 2007, respectively. There are also multiple periodic variation characteristics. The first main period of the initial appearance date is 26 years, while the first main period of the final disappearance date and duration of stay is 28 years. The average temperatures in spring, summer, and autumn have increased extremely significantly and undergo mutations in 2001, 2021, and 2012, respectively. Seasonal precipitation has large inter-annual fluctuation and the change trend is not obvious. The significant increase in temperature in different seasons has a profound impact on the ecological environment. The large fluctuations in seasonal precipitation make the water environment more variable, which in turn affects the living conditions of the brown planthopper. Although the trend of precipitation change is not clear, its inter-annual variability still poses challenges to the adaptation of the brown planthopper. The initial appearance date has a highly significant response to spring temperature, and a warm spring can lead to an earlier initial appearance date. The final disappearance date is positively correlated with the autumn temperature element, and a warm autumn will make the final disappearance date of brown planthoppers later. Warm spring and warm autumn both prolong the staying time of brown planthoppers. The initial appearance date is negatively correlated with the precipitation in March, and the final disappearance date is positively correlated with the precipitation and the number of days in November. This shows that temperature and precipitation in specific seasons have specific regulatory effects on the phenological period of brown planthoppers. The relationship between temperature and phenological period reflects the direct impact of thermal conditions on the growth and development rhythm of brown planthoppers. The correlation between precipitation and phenological period indicates that water availability also plays an important role in determining the key life cycle nodes of brown planthoppers.
    Design and Flow Field Quality Test of First Weather Modification Subsonic Cloud Environment Wind Tunnel in China
    HU Yong, YANG Yang, ZHAO Liwei, DENG Yupeng, HOU Shaoyu, LI Lin
    2025,53(2):285-292, DOI: 10.19517/j.1671-6345.20240178
    [Abstract] (29) [HTML] (0) [PDF 2.79 M] (33)
    Abstract:
    With the development of artificial weather modification efforts, the importance of aircraft for cloud seeding becomes increasingly significant. The effectiveness of aircraft for cloud seeding heavily relies on the stability of onboard detection equipment. To effectively simulate the dynamic operational environment of airborne detection equipment used in artificial weather modification and to enhance the detection capabilities of such equipment, this study presents a design for a recirculating closed-circuit wind tunnel. The primary structure comprises several sections: the test section, diffuser section, corner section, power section, heat exchange section, stabilisation section, contraction section, and reserved section. The interior contains built-in components such as corner guide deflectors, cellular devices, damping screens, heat exchangers, etc. The wind tunnel is arranged horizontally, with a centreline length of 28.09 m and a short axis distance of 5.71 m. The maximum dimensions of the wind tunnel are 31.33 m×10.18 m×5.436 m (length×width×height), while the cross-sectional dimensions of the test segment measure 1.2 m×1.2 m with a stable wind speed range from 30 to 150 m/s. The actual sizes of the airborne detection instruments are taken into account in the design of the test section. Based on a contraction ratio of 12.25, the stable section is designed with a square cross-section of 4.2 m×4.2 m. The diameter of the power section is set at 2.4 m. To prevent damage to the fan blade from test pieces or other objects, a protective net is installed in front of the power section. To verify the rationality of the wind tunnel design, the flow field quality of the wind tunnel is tested according to the “Low-Speed and High-Speed Wind Tunnel Flow Field Quality Requirements” (GJB1179A-2012) and the “Wind Tunnel Control System Design and Checking Guidelines” (GJB 5221-2004). Following flow field calibration tests, various quality indicators-including wind speed range, dynamic pressure stability, drop coefficient, turbulence intensity, airflow temperature variations, axial static pressure gradient as well as directional and dynamic pressure fields are confirmed to meet GJB1179A-2012 standards and adequately fulfil the testing requirements for airborne equipment. Specifically, the dynamic pressure stability is less than 0.5%, and the turbulence intensity is less than 0.2%. When the wind speed is 100 m/s, the temperature rise is 1.31 ℃/h. The aerodynamic and structural design principles applied in this wind tunnel are reasonable and may serve as valuable references for future designs and constructions of similar facilities.
    Design and Validation of a Distributed Transmission Model for National Emergency Early Warning
    SONG Yingying, HAN Qiang, WANG Jiahe, HUI Jianzhong, SU Jingwen
    2025,53(2):293-300, DOI: 10.19517/j.1671-6345.20240112
    [Abstract] (39) [HTML] (0) [PDF 2.74 M] (41)
    Abstract:
    The National Early Warning Release System (NEWRS) is an essential part of the National Emergency Command and Dispatch Platform System. It serves as a key transmission hub connecting various departments and plays a very important role in disseminating warning information. With the increase in the variety and volume of warning data, the NEWRS faces challenges. The capacity and throughput of the NEWRS are under intense restrictions. Problems like low transmission efficiency, limited data processing capability, and high system failure are serious. These problems affect the timely availability of disseminating warning information. The phenomenon that a large amount of data can only exist in the original system is significant. These data are not shared, which does not help to integrate data. It also limits data mining and advanced warning decision-making services. The paper presents a distributed transmission plan for warning data. It promotes a warning transmission model to solve these problems. The transmission model can serve four levels of application: national, provincial, municipal, and county levels. However, it is implemented at national and provincial levels to relieve the instability of the NEWRS caused by multi-level deployment. Meanwhile, it enhances data transmission with caching services using message-oriented middleware technologies. Provincial nodes can serve as a caching function. Once the fault is fixed, provincial nodes can resume transmission automatically. Besides, the transmission model employs distributed clustering technologies to help increase the scalability of the system and reduce the possibility of large-scale failures. It can continue to work when there are some node errors. The warning transmission model improves message-oriented middleware by designing a message data structure, so the transmission model can support dynamic expansion for data types. At the same time, security authentication and data consistency verification for data exchange have been strengthened. All these functions are provided as interface services to facilitate integration with other business systems. To verify these capabilities of the warning transmission model, we conduct experiments in data carrying capacity. Writing a Common Alert Protocol message data requires around 6.7 milliseconds, and reading it takes about 11.4 milliseconds. In timely recovery response, the experiments also show the model is effective. Notably, the transmission model achieves remarkable results in the pilot application in Guizhou Province. The results show that the transmission efficiency of the model is confirmed to be about 94.5 times higher compared to the NEWRS. It has been shown as a practical solution with the potential for nationwide implementation. This will improve the efficiency of communication between national and provincial levels.
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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] (961) [HTML] (0) [PDF 1.07 M] (65327)
    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] (918) [HTML] (0) [PDF 11.58 M] (64250)
    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] (1705) [HTML] (0) [PDF 2.17 M] (61411)
    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] (2063) [HTML] (0) [PDF 26.87 M] (60974)
    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] (1267) [HTML] (0) [PDF 2.65 M] (49865)
    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] (2565) [HTML] (0) [PDF 12.84 M] (31201)
    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] (2767) [HTML] (0) [PDF 63.01 M] (30086)
    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] (2308) [HTML] (0) [PDF 57.54 M] (28963)
    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] (2214) [HTML] (0) [PDF 13.24 M] (24294)
    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] (2738) [HTML] (0) [PDF 788.79 K] (22691)
    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.
    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] (227) [HTML] (0) [PDF 25.35 M] (19211)
    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.
    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] (192) [HTML] (0) [PDF 17.35 M] (19174)
    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] (245) [HTML] (0) [PDF 11.03 M] (19164)
    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.
    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] (195) [HTML] (0) [PDF 14.80 M] (19153)
    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.
    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] (163) [HTML] (0) [PDF 75.13 M] (19152)
    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.
    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] (353) [HTML] (0) [PDF 1.48 M] (19038)
    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.
    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] (316) [HTML] (0) [PDF 8.58 M] (19007)
    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.
    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] (178) [HTML] (0) [PDF 2.24 M] (18990)
    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.
    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] (234) [HTML] (0) [PDF 9.05 M] (18937)
    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.
    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] (155) [HTML] (0) [PDF 13.77 M] (18919)
    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.
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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] (5973) [HTML] (0) [PDF 423.81 K] (5602)
    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] (5538) [HTML] (0) [PDF 464.40 K] (5444)
    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.
    Observational Experiment on Spatial-Temporal Distribution of Soil Resistivity in Ningxia
    Liu Chunquan, Hou Junxue, Zhang Wei
    2008,36(4):474-479, DOI:
    [Abstract] (4452) [HTML] (0) [PDF 650.10 K] (4998)
    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.
    Regionalization of Grassland Climate Characteristics and Ecotypes in Inner Mongolia
    Chen SuHua;Gong ChunNing
    2005,33(4):340-344, DOI:
    [Abstract] (4209) [HTML] (0) [PDF 146.22 K] (7088)
    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.
    Comparative Analysis of NCEP/NCAR, ECMWF and JMA Reanalysis
    Deng Xiaohua, Zhai Panmao, Yuan Chunhong
    2010,38(1):1-8, DOI:
    [Abstract] (3884) [HTML] (0) [PDF 988.69 K] (8086)
    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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