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主办单位:中国气象局沈阳大气环境研究所
国际刊号:ISSN 1673-503X
国内刊号:CN 21-1531/P

Table of Content

    28 October 2024, Volume 40 Issue 5 Previous Issue    Next Issue
    Articles
    The role of low-level jet and its cause of diurnal variation during the "6·13" heavy rainfall process in Guangxi
    Hao QIN,Le LIU,Mengsong NONG
    2024, 40 (5):  1-11.  doi: 10.3969/j.issn.1673-503X.2024.05.001
    Abstract ( 87 )   HTML ( 13 )   PDF (7310KB) ( 77 )   Save

    Based on observation data and ERA5 reanalysis data, an analysis and diagnosis of thes "6·13" heavy rainfall process in Guangxi in 2022 were conducted, with a focus on the role of diurnal variation and its cause of low-level jet. The results show that the heavy rainfall process is jointly influenced by the upper level trough, the low-level shear line and the southwest low-level jet. The low-level jet weakens during the day and significantly strengthens at night, with convective systems continuously developing at the top of the jet and the south of the shear line, resulting in heavy rainfall mainly concentrated at night. The extreme heavy rainfall appears during the merging stage of mesoscale convective cloud clusters, located in the large TBB (Top Blackbody Brightness temperature) gradient region. The convergence in the left front of the low-level jet at night and the obstruction of mountain topography together enhance the low-level convergence and promote the development of upward movement. The intensification of low-level jet at night causes the intense convergence of warm and cold air in the northeastern region of Guangxi, resulting in the enhancement of low-level horizontal frontogenesis forcing, which is conducive to the maintenance and intensification of precipitation. Under the continuous warm and humid transport of the low-level jet, the unstable structure in the lower atmosphere is significantly enhanced, which provides a favorable environment for the development and maintenance of convective systems and heavy rainfall. In addition, the low-level jet promotes the water vapor convergence and uplift in the northeastern region of Guangxi at night, which corresponds well with the heavy rainfall area. The diagnosis of momentum balance shows that inertial oscillation is the main mechanism causing the diurnal variation of low-level jet. The Coriolis force at night dominated the momentum change of the geostrophic wind, which rotates clockwise to form the southwest wind and superimposes with the background wind field to strengthen the low-level jet. The daytime turbulent friction is enhanced and the residual and advection terms jointly dissipate local momentum.

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    Quality control algorithm of S-band weather radar in Liaoning province based on three heavy precipitation processes
    Chang HOU,Liang WU,Chuanhai MIAO,Boshi KANG,Weiwei SHAN,Wen YAO,Zonghao LI,Lei YANG
    2024, 40 (5):  12-19.  doi: 10.3969/j.issn.1673-503X.2024.05.002
    Abstract ( 48 )   HTML ( 10 )   PDF (6167KB) ( 47 )   Save

    In this paper, a quality control algorithm of S-band dual polarization weather radar is proposed in order to solve the data quality problem of S-band weather radar in Liaoning province. The algorithm included five parts: initial azimuth consistency revision, non-standard blockage revision, ground clutter recognition, threshold control and clutter elimination. Based on the S-band dual polarization weather radar data under different weather processes in Yingkou region, the distribution characteristics of reflectivity level texture, correlation coefficient variance, differential reflectivity variance and differential propagation phase shift variance corresponding to feature clutter in Liaoning area were statistically characterized, the localization parameters corresponding to the fuzzy logic clutter recognition algorithm are established. The quality control algorithm was verified by using the radar base data during three severe convective weather events (August 19, 2021;June 9, 2019;June 25, 2022) in Liaoning province. The results show that the algorithm has less loss of meteorological echoes. It can improve the quality of S-band radar data, effectively revise the non-standard obscuration during the weather process, eliminate the non-meteorological echoes such as ground clutter and electromagnetic interference. The study can provide a reference for the monitoring of the S-band dual-polarization radar quality control technique in the strong convective weather.

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    Comparative analysis of extreme hourly precipitation characteristics in Henan province based on the observations from national and regional stations during the warm season
    Wei WU,Zhongxia DUAN,Qiongna XIE
    2024, 40 (5):  20-29.  doi: 10.3969/j.issn.1673-503X.2024.05.003
    Abstract ( 58 )   HTML ( 6 )   PDF (3247KB) ( 51 )   Save

    Based on the hourly precipitation data of national and regional stations from 2013 to 2022, the frequency, intensity and extreme value of extreme hourly heavy precipitation in Henan province during the warm season were studied by taking the 99.5% percentile as the threshold. The results show that the threshold of extreme hourly heavy precipitation in Henan province during the warm season is mainly concentrated in the range of 30~50 mm, while the threshold above 50 mm is mainly located in the northern and the middle eastern parts of Henan province. The intensity of extreme hourly precipitation is large in the east and north Henan province while small in the west, and the high value areas are mainly located in the eastern Taihang Mountain and the plains in east central Henan province. The frequency is more in the west and less in the east. Compared with national stations, regional stations can better show the extreme, discrete and localized nature of extreme hourly precipitation. In terms of annual variation trend, the frequency increases, the intensity decreases, while the change of extreme value is not obvious. In terms of monthly variation, the frequency, intensity and extreme value exhibit a single-peak distribution. National and regional stations are similar in frequency with peaks in July, while different in intensity and extreme value with peaks of national stations in June and July, with peaks of regional stations in July and August respectively. Moreover, the intensity and extreme value of regional stations are larger than those of national stations. The diurnal variation of frequency, intensity and extreme value shows a typical bimodal structure, with one peak located from afternoon to evening and another one located from night to early morning respectively, which is most obviously in July and August.

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    Analysis of variation characteristics and atmospheric circulation causes of cold and warm winter in Dalian from 1971 to 2021
    Xiuping WANG,Wei JIN,Yanze HOU,Kaiyu FAN,Xiaoxiao LI
    2024, 40 (5):  30-39.  doi: 10.3969/j.issn.1673-503X.2024.05.004
    Abstract ( 66 )   HTML ( 6 )   PDF (2512KB) ( 40 )   Save

    This study analyzes the daily temperature observation data from 6 national meteorological stations in Dalian, including the southern area (Dalian, Lvshun, Jinzhou) and northern area (Wafangdian, Pulandian, Zhuanghe) in winter from 1971 to 2021, as well as NCEP/NCAR monthly reanalysis data. Using methods such as linear tendency rate, Mann-Kendall abrupt test, extreme temperature thresholds defined by using percentiles and synthetic analysis, the cold and warm variation trends and unusual characteristics of winter over the past 51 years are analyzed. The atmospheric circulation causes of cold and warm winter in Dalian are further investigated. The results indicate that the winter temperature and monthly temperature have shown an increasing trend over the past 51 years, with a higher warming rate observed in the southern region compared to the north. The most significant rise in minimum temperatures occurs in south of Jinzhou and in Wafangdian, with notably impacting winter warming; Lvshun shows the highest increase in minimum temperatures, while Pulandian and Zhuanghe exhibit the most substantial rises in maximum temperatures; the increase in maximum temperatures has the most significant impact on winter warming, with Pulandian experiencing the highest rise in maximum temperatures. The temperature rise in February contributes the most to winter warming in Dalian. The period from the 1970s to 1980s was predominantly cold, while the 1990s were the warmest, but the warming slowed down in 2006. A significant transition from cold to warm around 1986 in winter mean temperature in Dalian. Over the past 51 years, there has been a significant decrease in the number of low-temperature days, although cold years still fluctuate within relatively warm periods, particularly in January when the highest number of low-temperature days occurs. Extreme cold days have significantly decreased, while extreme warm days have notably increased over the past 51 years, leading to greater interannual fluctuation and instability in climate anomalies. The winter temperature anomalies in Dalian are primarily attributed to anomalies of the Siberian high in surface, the East Asian trough at 500 hPa, Ural mountain high and Okhotsk sea high. When the Siberian high in surface is stronger (weaker) during winter, and the middle-high latitude of Eurasian continent experiences predominantly meridional (zonal) circulation, the Ural mountain high, Okhotsk Sea high and East Asian trough are stronger (weaker) than normal at 500 hPa. This results in a stronger (weaker) winter monsoon in East Asia, it is favorable (unfavorable) for polar cold air moving southward to affect Dalian area, and thereby contributing to cold (warm) winters in Dalian.

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    Characteristics of spatial-temporal distribution of holiday climate comfortable days over China from 1990 to 2019
    Rong WANG,Shanshan ZHAO,Dianxiu YE
    2024, 40 (5):  40-49.  doi: 10.3969/j.issn.1673-503X.2024.05.005
    Abstract ( 58 )   HTML ( 7 )   PDF (9214KB) ( 44 )   Save

    This study analyzed the spatio-temporal distribution pattern of the holiday climate comfort days in China from 1990 to 2019 in terms of annual, seasonal, monthly, and typical holiday periods using Holiday Climate Index (HCI), which incorporated five meteorological elements, temperature, precipitation, relative humidity, wind speed, and sunshine hours. The results show that the average annual number of comfortable days for holiday climates in China is 134.3, with the highest occurrence in autumn and the lowest in winter. The monthly and daily distribution of comfortable days exhibits a bimodal curve pattern, with secondary and primary peaks observed in early May to mid-June and early September to mid-October, respectively. The spatial distribution of holiday climate comfortable days is uneven; Yunnan and southern Sichuan exceed 200 days, while the majority of the Qinghai-Tibet Plateau and northern Northeast China have fewer than 100 days. Yunnan, Xinjiang, Guangdong, Shanxi, and He'nan are the top five provinces (autonomous regions) with the highest annual comfortable days for holiday climate, and Yunnan has the most with 207.7 days. The spring, autumn, and winter seasons in Yunnan rank among the top five for holiday climate comfortable days nationwide. May, September, and October show the broadest range of comfortable holiday climate. During the "May Day" and "National Day" holidays, the probability of comfortable weather exceeds 50% in most regions of China. However, during the "New Year's Day" holiday, the probability of comfortable weather exceeds 50% only occurred in South China and Yunnan.

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    Characteristics of pH value of precipitation in Liaoning province from 2021 to 2022
    Jiageng DAI,Hujia ZHAO,Jia XU,Yangfeng WANG,Peng WANG,Wenbo MA,Xiaolei SU,Lei XU
    2024, 40 (5):  50-56.  doi: 10.3969/j.issn.1673-503X.2024.05.006
    Abstract ( 43 )   HTML ( 7 )   PDF (1589KB) ( 28 )   Save

    This study analyzes the acid rain observation data from 14 cities in Liaoning province from 2021 to 2022, mapping the spatial distribution as well as the monthly and seasonal variations of precipitation pH values. It assesses that the frequency of acid precipitation and its correlation with acidic gaseous pollutants in different cities of Liaoning province. The results show that the average annual precipitation pH value across coastal areas is low. Dalian has the lowest average annual precipitation pH at 5.77, while Jinzhou has the highest at 6.74. The minimum annual pH value of 5.72 is recorded in December, the highest frequency of acid precipitation is 7.94%;while, the highest annual pH value is 6.25 in April, and the frequency of acid precipitation is 1.72%. Among the 14 cities, Anshan records the lowest occurrence of acid rain at 0.24%, while Huludao exhibits the highest frequency at 11.79%. Due to the washout effect of alkaline aerosol particles and the wet removal process during precipitation, the pH values in Liaoning province are higher in spring, decrease during summer and autumn, and reach their lowest in winter. Monthly variations of SO2 and NO2 concentrations in Benxi, Dandong, Dalian, and Huludao show lower levels in summer and higher levels in winter, which indicating a local emissions influence on acid precipitation in winter, while summer acid precipitation is significantly impacted by wet removal processes. Furthermore, the pH value decreases and the frequency of acid precipitation increase when precipitation is less than 50 mm. Conversely, the pH value rises and concentrates between 6 and 7 when precipitation exceeds 100 mm. Wind directions influence significantly the source and sink dynamics of key atmospheric pollutants affecting the pH value of precipitation. Dust storms driven by prevailing spring winds contribute to an increase in atmospheric alkaline aerosols, which in turn elevate precipitation pH levels. In summer, southward airflow brings in substantial moisture, leading to a rise in acid precipitation events.

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    Component characteristics and source apportionments of ambient PM2.5 during 2020 in Changsha
    Maoqing FAN,Qiao WU,Huiwen GU,Huimin HUANG,Ming ZENG
    2024, 40 (5):  57-64.  doi: 10.3969/j.issn.1673-503X.2024.05.007
    Abstract ( 49 )   HTML ( 9 )   PDF (3343KB) ( 38 )   Save

    Based on the online and offline daily monitoring data of seven sites in Changsha City in 2020, the chemical component pollution characteristics of PM2.5 were analyzed.The positive matrix factorization (PMF) model was used to analyze the source apportionments of PM2.5.The results show that the water-soluble ions in PM2.5 has the highest mass proportion, accounting for 64.3%, followed by organic matter (OM), accounting for 26.6%, SO42-, NO3- and NH4+ are the main components in water-soluble ions.The PMF model identified five sources of PM2.5, vehicle exhaust emission source (36%), secondary formation source (31%), industrial emission source (16%), biomass burning source (9%), and dust source (8%).The highest proportion at Changsha Environmental Protection College are secondary formation and motor vehicle emissions, reaching 38% and 37%; the contribution of motor vehicle emissions at Mapoling site is the highest, 42%; the sharing rates of secondary formation, motor vehicle emissions, and industrial emissions at Environmental Protection Bureau of the High-tech Zone are relatively similar, 28%, 26%, and 25%.In order to further control PM2.5 pollution, it is recommended that Changsha could focus on controlling vehicle exhaust emissions, accelerating the elimination of old motor vehicles, and promoting the electrification of fuel vehicles; meanwhile, differentiated control measures should be implemented for different seasons, with focus on controlling vehicle exhaust emissions in autumn and winter; in summer, it is recommended to prioritize controlling oxidants such as ozone to reduce the secondary formation rate of PM2.5.

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    Comparison and analysis of temperature measurement errors using three types of temperature sensing methods in micro-smart weather stations
    Tian CHU,Zhenchao WANG,Junming CHEN,Jiajia HUA,Wenzhong LIU
    2024, 40 (5):  65-72.  doi: 10.3969/j.issn.1673-503X.2024.05.008
    Abstract ( 33 )   HTML ( 9 )   PDF (2586KB) ( 19 )   Save

    To assess the temperature observation performance of different types of micro intelligent weather stations (micro smart stations), a comparative observational experiment was conducted from 08:00 on January 1 to 23:59 on December 31, 2023, at the Meteorological Service in Xiongan New Area, Hebei province.The stations employed differing temperature measurement principles (platinum resistance, thermistor, and diode). The results show that, on an annual time scale, the stations using platinum resistance closely matched the standard station temperatures, whereas the thermistor-based stations exhibited the largest deviations.In terms of data stability, platinum resistance stations outperformed those using diodes, with thermistor stations being the least stable.Stations with larger average annual temperature errors showed significant monthly fluctuations, which were not closely related to the seasons.It suggested that the primary source of overall temperature measurement errors in micro smart stations stems from the instruments themselves.Under extreme temperature conditions, the best-performing stations were again those using platinum resistance; overall, the temperature readings from all micro smart stations tended to be higher; thermistor stations performed the worst under extreme high temperatures; thermistor and diode stations had better temperature measurement performance under extreme low temperatures compared to high temperatures. The hourly average temperature error trends of each station nearly mirrored the trends in solar radiation, indicating that another major source of temperature measurement errors may be the radiation shielding hardware structure of the micro smart stations.Therefore, conducting field comparative experiments and optimizing the hardware structure based on the results is an effective way to enhance the temperature measurement performance of micro smart stations and can provide a reference for equipment selection in different scenarios and needs for refined thermal environment monitoring.

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    Study on scheme of snow enhancement by ground-based flare seeding system
    Yu FU,Wenyao PU,Hongbin LI,Diangang ZHANG,Fansheng ZHAO,Wei XIA,Jialiang WEN
    2024, 40 (5):  73-83.  doi: 10.3969/j.issn.1673-503X.2024.05.009
    Abstract ( 30 )   HTML ( 4 )   PDF (3542KB) ( 19 )   Save

    Using the WRF numerical model, the minimum height Hx required for the activation of the catalyst was calculated based on the forecast meteorological elements.The Gaussian plume model was employed to calculate the effective diffusion height Hkm of the catalyst concentration. A comparative analysis of the relationship between Hx and Hkm was conducted to explore and study the operational schemes of the ground-based broadcasting system.The results show that when using the WRF numerical model, the Lin-YSU-KF combination scheme has the best correlation with the observed precipitation, and the simulated cloud areas, temperature, and relative humidity are consistent with observational data.This scheme can be used to forecast the characteristic temperature layer height and cloud base height required for snow enhancement operations, and to determine the minimum height required for the catalyst to be effective. The study of the diffusion distribution using the Gaussian plume model indicates that burning multiple flares simultaneously can significantly increase the effective diffusion height within the same time period; when the total number of flares is the same, the diffusion center concentration and effective diffusion height are relatively similar. The more flares burned simultaneously, the higher the effective diffusion height.Comparing calculated Hx and Hkm can be used to determine the timing of snow enhancement operations and to choose appropriate operational schemes.

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    Validation and applicability assessment of multi-source integrated analysis products in Liaoning region
    Yang YU,Fanyue YU,Fangni WU,Dong SUI,Chen ZHU
    2024, 40 (5):  84-91.  doi: 10.3969/j.issn.1673-503X.2024.05.010
    Abstract ( 48 )   HTML ( 8 )   PDF (4576KB) ( 63 )   Save

    Using data from surface meteorological stations in Liaoning province from January to December of 2021, this study evaluates national multi-source integrated analysis products (resolution of 0.05°×0.05°) using various indices including mean error, mean absolute error, root mean square error, accuracy, correlation coefficient, and TS score.Additionally, two severe weather events involving heavy rain and strong winds in 2021 were selected to specifically assess the precipitation and wind speed products.The results show that, among the four products, the precipitation and temperature products generally perform better than the relative humidity and wind speed products, aligning more closely with observed values.The quality of the integrated analysis products is influenced by season and terrain, with larger errors observed in wind speed products in spring, precipitation products in summer, and temperature products in winter, especially in mountainous areas and near coastal regions.During extreme weather events, the precipitation and wind speed products demonstrate stability, with three-source integrated precipitation outperforming two-source integration.However, wind speed products generally underperform, with larger errors occurring at higher wind speeds.Multi-source integrated analysis products are already being applied in meteorological forecasting, early warning, services, and information operations within Liaoning province.

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    Bulletins
    Risk analysis of continuous rain disaster in ripening period of Dandong blueberry (Vaccinium) based on information diffusion theory
    Haitao DONG,Lulu SHAN,Xin MENG,Ru LI,Lijing TAN,Yihe FANG
    2024, 40 (5):  92-98.  doi: 10.3969/j.issn.1673-503X.2024.05.011
    Abstract ( 28 )   HTML ( 3 )   PDF (702KB) ( 25 )   Save

    Based on the meteorological data of blueberry ripening period at four stations in Dandong region from 1991 to 2020, the index of continuous rain disaster was taken as the daily precipitation greater than 0.1 mm for more than 3 days and greater than 25 mm for at least 1 day during blueberry ripening period.Considering the frequency and duration, the grades of light, moderate and severe continuous rain disaster were established.The characteristics of continuous rain disaster of blueberry were analyzed by the frequency and station ratios of this disaster, and the risk probability was evaluated based on information diffusion theory.The results show that during the past 30 years, the influence of continuous rain disaster was reduced in the whole blueberry ripening period in Dandong, and the frequency of continuous rain disaster showed a decreasing trend, especially in Zhen'an District, the frequency tendency rate of continuous rain disaster was 0.23 times per decade (p < 0.01).The risk of continuous rain disaster was low in the early maturing period of 30 years, the risk probabilities of mild and moderate continuous rain disasters were less than once in 20 years (≤5%), and no severe disaster occurred.Continuous rain disasters were mainly concentrated in the late maturing period, and the probability of light disaster was more than once in 10 years (≥10%).Zhen'an District is a high risk area of continuous rain disaster, with a wide range, high frequency and heavy degree.The probabilities of mild and moderate continuous rain disasters were more than once in 10 years (≥10%).

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    Calculation and classification of meteorological index for Marathon races
    Wenguang DUAN,Yiyang JIA,Yan LIU,Yongwei SHI,Lifu CHEN
    2024, 40 (5):  99-105.  doi: 10.3969/j.issn.1673-503X.2024.05.012
    Abstract ( 44 )   HTML ( 6 )   PDF (441KB) ( 30 )   Save

    Based on the research conclusions on the suitable meteorological conditions for Marathon races at home and abroad, the impact of weather factors on athletes' performance, and the meteorological disaster risk of sports events, the scoring method and calculation formula of meteorological index for marathon races were designed.Moreover, an index forecasting method was constructed by the characteristic element classification, interval threshold setting, and index level division.The results indicate that the main characteristic elements affecting Marathon races are temperature, precipitation, wind speed, humidity, air pressure, sunshine, ultraviolet radiation, air pollution, and severe convective weather.The calculated index level can reflect the impact of meteorological conditions on the races and the primary influencing meteorological conditions.When the meteorological index for Marathon races is level 1, the weather conditions are most suitable for the races; when the index is 2~3, there may be some adverse weather conditions that have a certain impact on the races; when the index is 4~5, there may be adverse weather conditions that have a high impact on the races; when the index is level 6, there may be disastrous weather conditions that have a serious impact on the races.The forecasting method of meteorological index for Marathon races can provide better meteorological service by "directly reflecting the suitability of meteorological conditions", thereby effectively improve the professionalism and pertinence of meteorological support services for the races.

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    Research on an improved NRCS model based on spaceborne SAR observation
    Zhenbin XU,Ya XIE,Rui WANG
    2024, 40 (5):  106-111.  doi: 10.3969/j.issn.1673-503X.2024.05.013
    Abstract ( 26 )   HTML ( 4 )   PDF (1107KB) ( 18 )   Save

    The Normalized Radar Cross Section (NRCS) calculation formula is derived by analyzing the echo paths of the scattering attenuation characteristics of rainfall particles in different phases.Using the vertical profiles of convective rainfall measured over low-latitude tropical land and ocean in 1998, the optimization of NRCS is validated based on the Model-Oriented Statistical (MOS) surface rainfall retrieval algorithm of Synthetic Aperture Radar (SAR). The results show that the optimized NRCS model can improve the echo attenuation by about 6.17%.The improvement of echo attenuation indicates that the optimized NRCS model can improve the surface rainfall retrieval accuracy of MOS algorithm in the range of surface rainfall underestimated by MOS algorithm, and the average retrieval error is reduced by about 1.56%.However, in the range of surface rainfall overestimated by MOS algorithm, the optimized NRCS model will increase the retrieval error of MOS algorithm.Therefore, the improved NRCS model is only applicable to the case where the MOS algorithm underestimates the surface rainfall.

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