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

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

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

  • Current Issue
  • Archive
  • Latest Accepted
  • Most Downloaded
  • Most Read
  • Most Cited
    Article Search
    Search by issue
    Select AllDeselectExport
    Display Method:
    Application of Bispectral Approach in FY-4B/AGRI Sea Surface Temperature
    CUI Peng, WANG Sujuan
    2024,52(6):763-774, DOI: 10.19517/j.1671-6345.20240095
    [Abstract] (47) [HTML] (0) [PDF 10.90 M] (46)
    Abstract:
    Fengyun-4B is the first operational satellite of the second-generation FengYun geostationary meteorological satellite. The Advanced Geostationary Radiation Imager (AGRI), a multiple channel radiation imager, which adds a low-level water vapour detection channel and an adjusted spectrum range of four channels to improve the quality of observation, is one of the primary payloads onboard FY-4B. As one of the basic quantitative remote sensing products of FY-4B/AGRI, the operational sea surface temperature (SST) derives from the split-window nonlinear SST (NLSST) algorithm in real time. The stripe noise is a common issue in sea surface temperatures (SSTs) retrieved from thermal infrared data obtained by satellite-based multidetector radiometers. It degrades not only image quality but also the accuracy of retrieved SSTs. The stripe noise is observed in FY-4B/AGRI SSTs. It is more obvious in the brightness temperature difference (BTD) of the split window data, but the stripe noise is invisible in brightness temperature (BT) images. The stripe noise originates from the relative noise in the BTD. It propagates into SSTs by degrading the atmospheric correction. The bispectral filter approach for removing the stripe noise is applied to FY-4B/AGRI data. The bispectral filter is a Gaussian filter and an optimal estimation method for the differences between the data obtained at the split window. A kernel function based on the physical processes of radiative transfer has made it possible to reduce stripe and random noise in retrieved SSTs without degrading the spatial resolution or generating bias. For the assessment of the bispectral filter approach, the retrieved FY-4B/AGRI SST is validated against in-situ SST measurements available from in-situ SST Quality Monitor (iQUAM). Robust statistics are used to assess the impacts of the bispectral filter on SST accuracy. The accuracy and precision of the bispectral filter approach are assessed by determining the robust standard deviation and median bias between FY-4B/AGRI SST and quality-controlled in-situ SST from May to Norember 2023. The matchup space-time window is 4 km and 30 mins from the buoys’ location to the centre of the SST pixel. The validation results demonstrate the effectiveness of the bispectral filter, which reduces stripe noise in the retrieved FY-4B/AGRI SSTs. The image of a bispectral-filtered BTD is clearer than that of an unfiltered BTD. It also improves the accuracy of the SSTs by about 0.04 K to 0.06 K in the robust standard deviation. Furthermore, the bispectral filter approach is based on a simple Gaussian filter and is easy to implement. However, the bispectral filter cannot remove the stripe noise in BT. Such noise should be removed before applying the bispectral filter.
    Thunderstorm Identification in Meteorological Satellite Images Based on an Improved DeepLabv3+ Network
    WU Ankun, GUO Juncheng, WANG Qiang, LENG Yu
    2024,52(6):775-786, DOI: 10.19517/j.1671-6345.20240030
    [Abstract] (45) [HTML] (0) [PDF 21.71 M] (43)
    Abstract:
    To achieve pixel-level classification and identification of thunderstorm activity ranges, research on image segmentation technology of meteorological geostationary satellite images is conducted. Taking Guizhou Province and surrounding areas (24°-30°N, 103°-110°E) as an example, the radiation data of Fengyun geostationary satellite water vapour and long-wave infrared channels (6.25-13.5 μm) are selected as features. By integrating ground-based very low frequency/low frequency (VLF/LF) lightning monitoring and spaceborne Lightning Mapping Imager (LMI) data, labelled data is constructed to establish a deep learning dataset. The improved DeepLabv3+ semantic segmentation network along with added training strategies is used to identify the thunderstorm activity range in geostationary satellite images. The research results show that by adopting deep learning training strategies such as data augmentation, adaptive sampling in active learning, Combo Loss combination loss, and Ranger21 optimiser, the impact of thunderstorm small sample data training on network model performance can be effectively reduced, and the problem of data imbalance can be solved. When further comparing different backbone networks, including MobilenetV2, Xception, ResNet_101, ResNet_50, and HRNetV2-48 for feature extraction, it is found that MobilenetV2 has the fastest running speed while ResNet_101 has the best segmentation performance. In addition, by introducing the convolutional block attention module (CBAM) in the encoder and decoder, the model’s ability to learn target features and fuse information at all levels is greatly enhanced. As a result, both pixel accuracy and average intersection are significantly improved, further enhancing the model’s segmentation accuracy. Through extensive ablation experiments on the test dataset comparing SegNet, UNet, FCN, Lraspp, and the original DeepLabv3+ semantic segmentation network model, it is evident that the improved DeepLabv3+ model is superior to all other models. It achieves a pixel average accuracy of 96.82% and an average intersection over union (MIoU) of 76.93%. This not only showcases its superiority but also to a certain extent addresses the problem of high accuracy but low MIoU of the training model on the test set due to imbalanced sample data. This research extends the RGB three-channel data in image recognition to meteorological multi-dimensional data with more than three channels, aiming to mine thunderstorm characteristic information in satellite images more accurately and efficiently and lay a solid foundation for the next step of applying spatio-temporal recurrent neural networks to thunderstorm activity prediction. This study holds great promise for improving our understanding and prediction of thunderstorm activities.
    Particle Spectral Characterization of a Rain-to-Snow Event and Identification Process of DSG5 Precipitation Weather Phenomenometer
    SHEN Gaohang, LIU Tingting, WANG Ziyue, GAO Anchun, SONG Yinghua
    2024,52(6):787-796, DOI: 10.19517/j.1671-6345.20230364
    [Abstract] (56) [HTML] (0) [PDF 8.18 M] (48)
    Abstract:
    In this paper, the relationship between the data at all levels formed by DSG5 in a rain-snow transition weather process and its identification process of weather phenomena are analyzed. The variation characteristics of the precipitation particle spectrum and meteorological elements such as air temperature, ground temperature and grass surface temperature in the process of rain-snow transition are studied. The ECMWF model data and dual-polarization Doppler radar data are used to explore the weather background of rain-snow transition and the spatial distribution of precipitation particles in different phases. It is found that: Before the start of precipitation, a cold air layer formed at the bottom of the warm air layer below 2 km above the station due to the influence of the backflow cold air, and the snowflakes in the upper layer experienced different degrees of melting after falling into the warm air layer. With the enhancement of the backflow cold air, the cold air layer near the ground gradually became thicker, the temperature became colder, and the warm layer gradually became thinner. The station experienced three main precipitation stages: raindrops, raindrops plus ice particles, and ice particles plus snowflakes. The phase change of precipitation particles over the station was clearly reflected in the spatial distribution of the correlation coefficient of the dual-polarisation Doppler radar. In the process of changing from rain to snow, the scale spectrum of surface precipitation particles obviously widened, and the velocity spectrum obviously narrowed. The raindrop scale time spectrum and velocity time spectrum better reflected the changes in the phase state of precipitation particles. The distribution of parameters such as the correlation coefficient of dual-polarisation Doppler radar and the changes of air temperature, ground temperature, and grass surface temperature assisted DSG5 in judging the precipitation weather phenomenon. In general, the identification results of DSG5 precipitation weather phenomenon were consistent with the analysis results of dual-polarisation Doppler radar and other observation data. To avoid interference, the particle number threshold was adopted by DSG5, which made the start time of precipitation judged by DSG5 lag by 5 minutes, the end time of precipitation advance by 6 minutes, and the total duration of precipitation judged by DSG5 was obviously shorter. According to the continuity of the precipitation process and radar echo, the time periods before and after the precipitation process identified by DSG5 were included in the corresponding weather process, and the identification results of DSG5 were optimised to overcome the problem that the total precipitation time of DSG5 was too short.
    Design and Practice of Long-Term Sequential Grid Data Management Platform
    JIA Xiaozhen, HU Jiangkai, WANG Dapeng, LIANG Chen
    2024,52(6):797-806, DOI: 10.19517/j.1671-6345.20230430
    [Abstract] (35) [HTML] (0) [PDF 1.71 M] (45)
    Abstract:
    With the rapid development of numerical weather prediction services, the resolution and forecasting lead time of meteorological models have significantly improved, leading to an exponential growth in the volume of forecast data output. As a national meteorological model research and operational centre, CMA Earth System Modeling and Prediction Center (CEMC) currently produces daily gridded data outputs of 0.76 TB, with an annual output reaching 155.12 TB. Given the enormous data volumes, researchers’ preferences for data access are evolving. Wagemann predicts that future scientific users increasingly prefer cloud platforms or other interfaces for data access rather than solely relying on downloads. To address these issues, this paper proposes a lightweight distributed parallel processing framework for gridded data management, aiming to streamline data management processes and enhance data access speed. The core design philosophy revolves around leveraging search engine technology for rapid metadata retrieval and gridded data decoding techniques for efficient data acquisition. To mitigate performance penalties from repetitive decoding, the framework decodes gridded data files once and supports multiple retrievals and extractions, significantly accelerating data access. Additionally, it supports cross-platform data access, facilitating easier data acquisition for researchers. The framework adopts a three-tier architecture: the data layer stores data, the algorithm layer implements core search and cataloguing algorithms, and the business layer interfaces directly with user needs. The framework implements crucial functions such as gridded data cataloguing, extraction, and clipping. During cataloguing, users invoke the cataloguing interface and input parameters (e.g., original data file paths, index names, index types), and the system automatically parses file metadata and generates indexes. For data extraction, users call the retrieval interface with specific parameters to obtain designated data. Moreover, the framework supports precise extraction of specified latitudinal and longitudinal data segments by configuring cropping parameters. It reduces decoding time by creating indexes based on binary storage characteristics, utilises an inverted index value-id model for rapid data location retrieval, enhances processing performance through GlusterFS shared storage and Celery distributed message queues, and ensures efficient and stable data transmission using gRPC technology for C/S communication. Practical tests and applications demonstrate the framework’s exceptional performance in handling massive meteorological data. Notably, it successfully processes petabyte-scale gridded data during the Beijing Winter Olympics meteorological support services, significantly improving data access efficiency. Additionally, the framework supports flexible processing and scalable upgrades for various file formats to meet diverse user needs. By integrating advanced search engine technology, gridded data decoding methods, and a distributed cluster framework, the platform not only enables rapid data retrieval and efficient access but also satisfies researchers’ urgent demand for cross-platform data access. As meteorological data continues to grow, this platform holds significant potential to play a pivotal role in various fields, offering more robust data support for weather forecasting, scientific research, and operational applications.
    Rolling Fusion Extrapolation Method of Nowcast and Its Applicability Assessment
    GUO Wenxin, LI Rong, YU Wanrong, LI Jianqiang, ZHENG Yu, CHEN Xiaojian, LIU Xin, LIU Sichen, NIU Liumin, YANG Jie, CHE Huizheng
    2024,52(6):807-815, DOI: 10.19517/j.1671-6345.20240021
    [Abstract] (24) [HTML] (0) [PDF 5.24 M] (37)
    Abstract:
    In the realm of meteorological forecasting, the integration of various nowcasting extrapolation methods is critical for enhancing accuracy and reliability. This paper introduces an innovative method for radar echo extrapolation called Rolling Fusion (RF), specifically designed to improve radar composite reflectivity (CREF) extrapolation. RF represents a novel synthesis of Optical Flow (OF) and Deep Learning (DL) methodologies, targeting the enhancement of nowcasting weather predictions. Central to the RF approach is RFNet, a sophisticated tool that employs a two-layer convolutional neural network. This network is optimised using Particle Swarm Optimisation (PSO), a computational methodology inspired by the social behaviour of birds and fish. PSO is particularly valuable in refining the network’s parameters to tackle the prevalent issue of CREF intensity imbalance, which can skew forecasting results. By optimising these parameters, RFNet ensures a balanced and accurate representation of various intensity levels, crucial for predicting severe weather conditions. The training process for RFNet is meticulously structured, utilising 10 steps of CREF data extrapolated from both OF and DL methods to anticipate the subsequent 10 steps. This dynamic approach not only enables high accuracy in nowcasting predictions but also enhances training efficiency by using the initially trained RFNet as a pre-trained model for further training cycles. This layered training process reduces computational demands, making the system both time-efficient and resource-efficient. Empirical results from this study reveal that RFNet effectively mitigates common drawbacks associated with deep learning predictions, specifically intensity attenuation and echo structure blurring. These enhancements allow RFNet to provide clearer and more accurate forecasts. Performance assessments across various intensity thresholds from 20 to 50 dBz demonstrate the method’s robustness. At lower thresholds, such as 20 and 30 dBz, RFNet and DL exhibit comparable performance, both of which surpass the capabilities of OF. In these scenarios, RFNet’s advanced integration of methodologies ensures superior forecasting precision. At a 40 dBz threshold, DL initially excels within the first 30 minutes of forecast duration. However, RFNet outperforms DL beyond this timeframe, highlighting its strength in extended forecasting scenarios. Notably, at the 50 dBz threshold, RFNet displays a significant performance advantage over both DL and OF, maintaining superior forecasting ability for up to 42 minutes. This capability is particularly valuable in predicting high-intensity weather events, where rapid changes necessitate agile and accurate forecasting models. Additionally, the research indicates a trend where RFNet’s extrapolation performance improves as CREF intensity surpasses 40 dBz. This improvement underscores the system’s adaptability and effectiveness in handling severe weather conditions, ultimately contributing to more reliable and actionable nowcasting weather forecasts.
    Weather Classification and Forecast Focuses of Extreme Thunderstorms and Gales on Background of Cold Votex in Shandong
    ZHANG Qin
    2024,52(6):816-829, DOI: 10.19517/j.1671-6345.20230431
    [Abstract] (26) [HTML] (0) [PDF 50.30 M] (30)
    Abstract:
    In order to gain a deeper understanding of the statistical characteristics and forecasting focuses of extreme thunderstorm gusts with a magnitude of 11 or above that occur in Shandong under the background of cold vortices and cause disasters, the paper analyses the large-scale circulation background, radar characteristics, vertical wind shear, and parameter features related to the intensity potential and momentum downward transmission of extreme thunderstorm winds. This is done by analysing the maximum hourly wind speed of automatic precipitation data, MICAPS data, radar wind profile, North China radar, lightning positioning data and NCEP reanalysis data during 2013-2021, through statistical methods, weather diagnosis, and synthetic analysis, etc. The main conclusions are as follows: (1) The extreme thunderstorm gale events above grade 11 are divided into 6 categories: low trough type, northwest airflow type, transverse trough type, upper cold vortex type, subtropical high marginal type and warm shear type. (2) There are five types of thunderstorms that produce extreme thunderstorm wind: bow echo, multi-cell storm, squall line, supercell and ordinary thunderstorm, among which bow echo and multi-cell storm are the main forms, accounting for 63% of the total number of occurrences. Squall lines and supercells are also forms of extreme thunderstorm winds, accounting for 17% and 13% respectively. (3) The middle front of the bow echo is the region with a high probability of extreme thunderstorm and gale. The right front of the moving direction of the multi-cell storm, the front of the squall line and the right front of the moving direction of the supercell are also the key areas of the extreme thunderstorm and gale. (4) When the extreme thunderstorm and gale occur, the top height of the echo is usually above 15 km. The extreme thunderstorm gale appears in the front or right front of the moving direction of the high centre of the Echo Top. (5) When the strong hourly pressure change over 2.5 hPa appears on the ground, the cold pool centre is lower than the surrounding atmosphere, and the environmental wind field in the middle and lower troposphere is obviously strengthened, the moving direction of the storm should be combined, to determine in advance the direction of the storm ahead, especially the right front, whether there is the possibility of extreme thunderstorm gale.
    Analysis on Formation Reason of an Extreme Gale in Sichuan Basin
    ZHOU Yanqiu, YU Qinkun, LIU Aiwei, LIU Bojun, MENG Nina
    2024,52(6):830-840, DOI: 10.19517/j.1671-6345.20230368
    [Abstract] (26) [HTML] (0) [PDF 28.18 M] (32)
    Abstract:
    Convective extreme gale is one of the main types of severe convective weather that causes meteorological disasters. It has the characteristics of strong locality, short life history, and difficulty in forecasting. In recent years, extreme gale events occur frequently in China, causing serious economic losses to the society and public. However, the characteristics, impact systems, and causes of extreme gale vary in different regions. At present, there are many studies on the background of extreme gales in the Sichuan Basin, but research on convective potential and Doppler radar characteristics is still relatively limited. Therefore, it is necessary to conduct detailed research on typical cases of extreme gales that occur. On 11 April 2022, a rare extreme gale process occurred in Sichuan Basin with maximum wind speed reaching 37.4 m/s. During this period, there were also hail and short-time heavy rain. To explore the causes of this extreme gale process, this paper conducts research and analysis on circulation situation, convective environmental conditions, and meso-small scale system characteristics by using surface hourly meteorological observation data, upper-air observation data, Doppler radar products, and black body temperature data from the FY-2H satellite, providing reference for future forecasting of extreme gale weather in the Sichuan Basin. The conclusions are as follows: (1) This extreme gale process was triggered by the dry and cold air entering the basin, and the forced uplift of the ground convergence line strengthened the storm weather; the unstable stratification featuring “upper dry and lower humid”, a large temperature lapse rate, vertical wind shear with moderate intensity, and high CAPE value, all provided favourable convective environmental conditions for this extreme gale process, (2) The severe weather of this process mostly occurred during the period of severe development and consolidation of the Mesoscale Convective System, and was located in the high-value area of TBB gradient in front of the convective cloud clusters and near the low-value centre of TBB, (3) The main factors causing extreme strong wind on the ground included the cold pool effect when the squall line passed through, and the strong pressure gradient and density current, (4) The front inflow and the rear inflow of the storm together with the strong mid-altitude radial convergence were favourable conditions for the emergence of extreme strong wind; the sharp decrease of the reflectivity factor core and the maximum vertically integrated liquid water implied the humid critical strike flow caused by a sharp drop in temperature in the system, which increased the intensity of strong wind.
    Evolution Characteristics of GNSS Zenith Tropospheric Delay and Horizontal Gradient during a Heavy Rainfall Event
    TU Manhong, OU Shuyuan, LIU Yimeng, CAO Yunchang, LIU Jia, GUO Fenghe
    2024,52(6):841-849, DOI: 10.19517/j.1671-6345.20230332
    [Abstract] (19) [HTML] (0) [PDF 15.14 M] (24)
    Abstract:
    In order to fully utilize the capabilities of the densely distributed Global Navigation Satellite System (GNSS) network, this study has developed a comprehensive near real-time GNSS retrieval system for analyzing Zenith Total Delay (ZTD) and Horizontal Gradients (HG). This system is specifically applied to investigate the evolution characteristics of ZTD and HG during the heavy rainfall event on 7 May 2017 in Guangzhou. The analysis incorporates gridded precipitation products from the China Meteorological Administration and ERA5 reanalysis data, ensuring a robust comparison and validation of the results. The study’s findings reveal that the temporal variations in ZTD and HG had the potential to capture early indicators of precipitation, offering valuable insights into the atmospheric conditions preceding rainfall events. Specifically, the increase in ZTD values was observed to coincide with the onset of precipitation, suggesting that ZTD could serve as a precursor to heavy rainfall. Meanwhile, the horizontal gradients (HG) exhibited distinct directional patterns that correlated with the movement and intensity of rainfall, indicating that HG not only reflected the presence of precipitation but also provided information on its spatial distribution and dynamics. Furthermore, the vector characteristics of HG were found to reveal certain critical features related to rainfall, such as the direction of moisture convergence and the intensity of localised convective activity. Areas with high Horizontal Gradient (HG) delay tended to have higher Integrated Water Vapor (IWV) and were more likely to experience precipitation. In summary, the spatiotemporal characteristics of ZTD and HG, as derived from the GNSS network, offered significant potential for improving short-term precipitation forecasting, particularly for extreme weather events such as heavy rainfall. By providing early warning signals and detailed insights into the evolving atmospheric conditions, these GNSS-derived parameters served as a valuable auxiliary tool for meteorologists and researchers engaged in the nowcasting of severe weather. The integration of ZTD and HG data into existing forecasting models could have enhanced the accuracy and lead time of predictions, thereby contributing to better preparedness and risk mitigation efforts in regions prone to sudden and intense precipitation events.
    Observation and Analysis of Surface Water Temperature and Air Temperature in Lake Qinghai in Summer and Autumn of 2022
    LI Wantong, ZHANG Zhilong, LI Xiaoxia, WANG Xinlong, WU Jianxun, LIU Yuan, SHI Jing, ZHANG Haonan
    2024,52(6):850-857, DOI: 10.19517/j.1671-6345.20230424
    [Abstract] (24) [HTML] (0) [PDF 3.47 M] (24)
    Abstract:
    Lakes are important parts of land water resources, and their surface water temperatures are the most sensitive and rapid response to climate and environmental changes. An accurate understanding of their changing characteristics is highly important for analysing and understanding global climate change and improving the ecological environment of lakes. In July 2022, the Meteorological Observation Centre of China Meteorological Administration and the National Satellite Meteorological Centre jointly deploy drift buoys at the China Radiometric Calibration Site of remote sensing satellite (CRCS) to carry out the Fengyun Satellite “lake-sea” cooperative observation experiment. Two sets of drift buoys are deployed on the line from Haixin Mountain to the southeast of Lake Qinghai. In this paper, we use data from the drift buoy from 10 July to 30 September, 2022, combined with data from four sets of automatic meteorological stations on the land around Lake Qinghai, to analyse the characteristics and correlations between the changes of water temperature and air temperature in Lake Qinghai, and the differences in the characteristics of the changes of air temperature on the lake and land. To ensure the reasonableness of the test data, quality control of the test data is conducted, including spatial consistency checks, climatological threshold checks and temporal consistency checks, and a total of 13488 sets of water temperature data and 20232 sets of air temperature data are screened out. The analysis results of the above data indicate that there is a certain correlation between water temperature and air temperature in Lake Qinghai, the correlation coefficient of the minute value is 0.71, and the correlation coefficient of the daily mean value is 0.73. The diurnal variations of water temperature and air temperature are unimodal, and the rising and falling stages are basically the same; however, the diurnal variations of water temperature are obviously smaller than those of air temperature, and the decreasing time is earlier than that of air temperature. The diurnal variations in lake and land air temperatures exhibit a certain off-peak phenomenon, the peak land air temperature is advanced, and the valley value is lagging. The factors influencing the correlation between air and water temperatures are diverse and are related not only to subsurface characteristics and the distance from the observation location but also to solar and surface radiation. The contributions of multisource observational data, such as total radiation, shortwave radiation, cloud remote sensing products and high-resolution satellite observations, to the difference between air and water temperatures are analysed during the day and night and in different seasons in future work. The study of the difference between air and water temperatures can provide technical support for analysing heat exchanges between the lake and the atmosphere of Lake Qinghai.
    A Study on Lightning Activities and Environmental Physical Characteristics in China from 2010 to 2019
    GUAN Liang, TIAN Fuyou, ZHENG Yongguang, CAO Yanchao, LIU Zimu
    2024,52(6):858-868, DOI: 10.19517/j.1671-6345.20230404
    [Abstract] (18) [HTML] (0) [PDF 11.23 M] (24)
    Abstract:
    Based on the lightning monitoring data from the Chinese ADTD (Advanced TOA and Direction system) lightning locator network and the NCEP (National Centers for Environmental Prediction) reanalysis data from 2010 to 2019, this analysis combines weather verification indicators such as TS scores and forecast deviations to provide the physical characteristics of environmental conditions related to lightning in different regions in China. The characteristics of lightning activity show a pattern of more lightning in the south and less in the north, with the highest lightning density in South China, followed by the eastern parts of Jiangnan and the eastern regions of Southwest China. Regarding monthly frequency variations, except for June, which sees a higher occurrence of lightning in South China, August records the highest lightning frequency nationwide and in most regions. In terms of diurnal variation, cloud-to-ground (CG) lightning activity is most concentrated in the afternoon, with the daily peak at 16:00. The analysis of environmental conditions indicates that thermal environmental characteristics significantly indicate lightning occurrence, and thermal-related physical quantities have the best indicative significance for lightning occurrence, followed by water vapour physical quantities. The indicative role of dynamic-related characteristic quantities is not significant. Among them, the K index is the best index nationwide, with an optimal threshold of 37 ℃. For different regions, there are significant differences in the conditions of low-level water vapour, mid-level water vapour saturation, cold air intensity, and temperature difference between high and low levels. Comprehensive statistics show that regions with better low-level water vapour conditions are more sensitive to the K index and have relatively higher thresholds, such as northern China, the Yangtze River Basin, and southern China. For mid to high latitude regions, atmospheric instability is more sensitive to lightning occurrence, so indices such as BLI and LI perform better. The water vapour condition is a necessary factor for lightning occurrence, but its indicative significance for lightning cannot be used alone as a basis for lightning prediction. It should be determined by combining atmospheric circulation and other environmental field characteristics. Dynamic effects are deemed a necessary condition for the development of severe convective weather, although their ranking in the verification of dynamic indicators is relatively lower, failing to accurately reflect their importance for lightning occurrence. The lightning forecasting in China mainly relies on the determination of the location of lightning occurrence. It is necessary to combine the atmospheric circulation situation and environmental water vapour, dynamics, and thermal conditions to determine the area and possibility of thunderstorm occurrence, and then measure the accuracy of the forecast through weather verification indicators. These findings provide an objective reference for understanding and forecasting lightning activity in different regions in China.
    Identification of Dominant Impact Factors of Typhoon Disaster Economic Losses in China
    XU Jinqin, SHEN Danna, WANG Qian, MENG Mingming
    2024,52(6):869-878, DOI: 10.19517/j.1671-6345.20230370
    [Abstract] (18) [HTML] (0) [PDF 2.22 M] (20)
    Abstract:
    Based on comprehensive data spanning from 2004 to 2021, encompassing 125 typhoon disaster events within China, and in conjunction with wind and rain observation data collected from ground meteorological stations as well as synchronous social and economic statistical data, this study develops a robust model for assessing the direct economic losses of typhoon disasters. This model takes into account causative factors, receptor characteristics, and disaster prevention and reduction capacity. On the basis of this model, we design a quantitative analysis method to conduct an in-depth exploration and quantitative analysis of the dominant factors influencing the change in direct economic losses caused by typhoon disasters in China. The research findings indicate that during the observation period from 2004 to 2021, overall direct economic losses resulting from typhoon disasters in China exhibit a significant year-on-year decreasing trend. Simultaneously, there are discernible signs of weakening in the wind and rain intensity associated with these typhoons in China. Taking 2012 as the cut-off point (the year when real-time correction technology for ensemble forecast of typhoon paths is officially put into use), our study finds that prior to this year, the typhoon wind index is identified as the most significant factor contributing to economic losses from these disasters during the observation period from 2004 to 2021; however, its influence decreases significantly after 2012, becoming the smallest contributing factor to the direct economic losses of typhoon disasters during the observation period from 2012 to 2021. Compared with the observation period from 2004 to 2011, there is a notable increase in contributions to the direct economic losses of typhoon disasters in China from factors related to typhoons after 2012, such as the typhoon rain index, regional GDP, typhoon intensity forecast error, and drainage pipe density factor. Particularly noteworthy is our identification of improved accuracy in forecasting typhoon intensity along with substantial increases during the observation period from 2012 to 2021 regarding drainage pipe density being the dominant impact factor driving down direct economic losses resulting from typhoon-related disasters. This study not only reveals differences over different research periods regarding dominant influencing factors on direct economic losses caused by Chinese typhoon disasters but also emphasises strengthening development and application of technologies for forecasting typhoons alongside improving infrastructure like drainage systems can effectively reduce their impact on society’s economy. These findings provide crucial references for formulating more scientific and efficient strategies aimed at addressing typhoon-related disasters.
    One/Two-Dimensional Hydrodynamic-Pipe Network Coupled Flooding Model Construction Technology and Application
    CHEN Jianfei, XIN Jiacen, XUE Fengchang
    2024,52(6):879-889, DOI: 10.19517/j.1671-6345.20230282
    [Abstract] (14) [HTML] (0) [PDF 47.29 M] (17)
    Abstract:
    With the rapid and intensive development of high-tech industrial development zones, they become more sensitive to environmental factors, especially extreme climate events. Under the dual influences of global warming and urbanisation, extreme rainfall events occur frequently in cities, and urban inland inundation poses a significant threat to development zones. Using digital elevation model data, land use data, remote sensing image data, POI data, and measured precipitation data, a one-dimensional and two-dimensional hydrodynamic-pipe network coupling inland inundation model for Jianhu High-tech Zone is constructed. The one-dimensional hydrodynamic layer includes river centre lines, river sections, flow boundaries, and open boundaries, with a total of 68 river sections set up at an average interval of 260 metres. Through grid subdivision, the surface elevation data are assigned to grid nodes to build a gridded two-dimensional terrain model, simulating the evolution of two-dimensional hydrodynamic forces. The grid subdivision is based on research needs, with grid refinement in areas near the river channel and sparse grid in areas away from the river channel to improve model simulation accuracy and efficiency. A total of 8345 triangular grids are divided. After parameter calibration, the model achieves visual numerical simulation of inland inundation conditions. The model is tested using two measured rainfall processes. The model simulation results are consistent with the actual inland inundation conditions. Based on this, the evolution process and distribution characteristics of inland inundation under extreme rainstorm conditions are analysed. Based on the constructed urban inland inundation numerical simulation model, the surface water depth and spatial distribution characteristics of inland inundation under five-year, ten-year, twenty-year, thirty-year, fifty-year, and one-hundred-year return periods are simulated, with severe inland inundation, moderate inland inundation, and general inland inundation classified. The distribution map of inland inundation grades is drawn. The results show that under different return periods, the water depth in the high-tech zone mainly distributes between 0.1 and 0.25 metres, accounting for about 50% of the total inland inundation risk area. Under the scenario of a 100-year return period, commercial residential buildings are mostly affected by heavy rainfall, accounting for 38.4% of the affected area. Transportation facilities and public facilities for healthcare are the next, accounting for 28.5% of the affected area. Public facilities for science and education, culture, and companies are less affected, accounting for 14.2% and 19.8% of the affected area respectively. The evaluation results can provide a scientific reference for the construction and flood prevention planning of high-tech zones.
    Research on Evaluation Method of Climate Quality of Laoshan Spring Tea
    LIU Chuntao, XUE Xiaoping, ZHU Junhan, XIANG Yingshuo
    2024,52(6):890-897, DOI: 10.19517/j.1671-6345.20230410
    [Abstract] (29) [HTML] (0) [PDF 655.48 K] (23)
    Abstract:
    Based on the field experiment method of agricultural meteorology, two main cultivars: Laoshan Datian spring tea population and Longjing 43, are selected for research. Using two consecutive years of observations from 2022-2023, 17 test samples and 68 replicates are collected for Laoshan Datian spring tea population and Longjing 43 to detect their biochemical components such as caffeine, amino acids, tea polyphenols, and phenol ammonia ratio. We establish the climate evaluation indicators for Laoshan spring tea by conducting correlation analysis and regression analysis of each biochemical component with the daily average meteorological data of temperature, sunshine, and relative humidity of 1-20 days before tea picking. The results show that: (1) There is a significant correlation between caffeine, amino acids, tea polyphenols, and phenol ammonia ratio of the two varieties of Laoshan spring tea and meteorological factors of 1-20 days before tea picking. The correlations pass the 0.05 and 0.01 significance tests, respectively. The main meteorological factors affecting the different biochemical components are basically constant; however, different meteorological factors have different primary times of action. (2) We establish an optimal regression model for tea polyphenols, amino acids, phenol ammonia ratio, and meteorological factors. The results of the forecasting equations show that: the average prediction accuracies of polyphenols, amino acids, and phenol ammonia ratio of tea from Laoshan Datian spring tea population are 88.5%, 94.6% and 96.4%, respectively; and those of polyphenols, amino acids, and phenol ammonia ratio of Longjing 43 are 88.6%, 92.9% and 97.5%, respectively. (3) We further establish the climate evaluation indicators for Laoshan spring tea: by conducting the K-means clustering analysis on phenol ammonia ratio and amino acid samples, four grades of Laoshan spring tea have been classified. Climate quality evaluation indicators for Laoshan spring tea are established based on the corresponding phenol ammonia ratio meteorological indicators for each grade. Combined with the forecasting equation of Laoshan Datian spring tea population and Longjing 43, we can determine the different levels of climate quality of Laoshan tea by predicting the threshold of phenol ammonia ratio. The purpose of this study is to provide technical support for the evaluation of spring tea climate quality in Laoshan, which is very important and highly practical. At the same time, it is aimed at the Laoshan tea industry, which is conducive to improving the competitiveness and adding value of spring tea. This helps to contribute to rural revitalisation.
    Application of New Wave-Transparent Lightning Rod in Protection of X-band Weather Radar
    YANG Bixuan, MAO Feng, DENG Fengdong, BAI Shuicheng, HE Zheng, WANG Ce, HE Xiangyong
    2024,52(6):898-904, DOI: 10.19517/j.1671-6345.20230374
    [Abstract] (21) [HTML] (0) [PDF 16.93 M] (22)
    Abstract:
    To solve the deterioration problem of the reflectance, differential reflectance and other parameters when the X-band phased array weather radar is interfered with by metallic lightning rods and metallic down-conductor systems, the segmented metal foil array is used as the guiding structure of the down-conductor system, and a new type of wave-transmitting lightning rod is designed in combination with a high-performance composite rod, successfully solving the problem of wave transmittance and lightning current: a continuous plasma channel is formed by the lightning electric field, which can be used as a lightning flow path; the radar reflectivity is greatly reduced by the discontinuous special metal foil. In order to verify the protection and transmission capability of the wave-transparent lightning rod, tests are carried out: (1) the test of the high voltage attachment point and impulse discharge capacity, the average breakdown threshold of the wave-transparent lightning rod is 4.45 kV/cm, and the impulse discharge capacity is greater than 150 kA (±10%, 10/350 μs), which meets the requirements of the second level lightning protection stipulated in the GB50057 standard; (2) the field installation test, the test results show that the influence of the new type of beam on radar reflectance and differential reflectance is greatly reduced. The new wave-transparent lightning rod can greatly reduce the negative influences of the lightning protection system on radar detection performance and can be further applied and popularised in direct lightning protection of similar phased array radar.
    Article Search
    Search by issue
    Select AllDeselectExport
    Display Method:
    Article Search
    Search by issue
    Select AllDeselectExport
    Display Method:
    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] (909) [HTML] (0) [PDF 1.07 M] (64847)
    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] (842) [HTML] (0) [PDF 11.58 M] (63664)
    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] (1659) [HTML] (0) [PDF 2.17 M] (60902)
    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] (2023) [HTML] (0) [PDF 26.87 M] (59726)
    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] (1222) [HTML] (0) [PDF 2.65 M] (49377)
    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] (2526) [HTML] (0) [PDF 12.84 M] (30708)
    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] (2728) [HTML] (0) [PDF 63.01 M] (29585)
    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] (2263) [HTML] (0) [PDF 57.54 M] (28329)
    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] (2174) [HTML] (0) [PDF 13.24 M] (23791)
    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] (2700) [HTML] (0) [PDF 788.79 K] (22281)
    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] (174) [HTML] (0) [PDF 25.35 M] (18724)
    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.
    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] (203) [HTML] (0) [PDF 11.03 M] (18710)
    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.
    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] (155) [HTML] (0) [PDF 17.35 M] (18709)
    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.
    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] (123) [HTML] (0) [PDF 75.13 M] (18691)
    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.
    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] (149) [HTML] (0) [PDF 14.80 M] (18686)
    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.
    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] (301) [HTML] (0) [PDF 1.48 M] (18635)
    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] (261) [HTML] (0) [PDF 8.58 M] (18566)
    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] (137) [HTML] (0) [PDF 2.24 M] (18564)
    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] (190) [HTML] (0) [PDF 9.05 M] (18493)
    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] (107) [HTML] (0) [PDF 13.77 M] (18479)
    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.
    Article Search
    Search by issue
    Select AllDeselectExport
    Display Method:
    Design of RHI/PPI Scan Mode of CINRAD/SA Radar
    Meng Zhaolin Wang Ping Lu Yaping Wang Hongyan
    2004,32(4):251, DOI:
    [Abstract] (5845) [HTML] (0) [PDF 423.81 K] (5139)
    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] (5473) [HTML] (0) [PDF 464.40 K] (4992)
    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] (4416) [HTML] (0) [PDF 650.10 K] (4590)
    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] (4111) [HTML] (0) [PDF 146.22 K] (6761)
    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] (3823) [HTML] (0) [PDF 988.69 K] (7709)
    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.

WeChat

Mobile website

Most Read

More+

Most Cited

More+

Most Downloaded

More+
External LinksChina Meteorological AdministrationCMA Meteorological Observation CentreChinese Academy of Meteorological SciencesBeijing Meteorological ServiceNational Satellite Meteorological Center
You are thevisitors
Supported by:Beijing E-Tiller Technology Development Co., Ltd.