Volume 51,Issue 5,2023 Table of Contents
WANG Qiyu
,
XU Weixin
,
ZHAXI Yangzong
,
HUANG Kunlin
,
DAI Na
,
XIAO Qiangzhi
,
DUAN Xuhui
,
LIANG Hao
2023, 51(5):613-628.
DOI: 10.19517/j.1671-6345.20220394
Abstract:
Monitoring the snow cover on the Qinghai Tibet Plateau holds great significance for climate prediction and snow disaster prediction, among other things. With its high temporal resolution and high spatial resolution, FY-4 data is providing a new field in snow monitoring service by geostationary satellite. Constructing snow monitoring methods and models based on FY-4A not only expands the application field of geostationary satellites but also enriches the means of snow monitoring application. The high temporal resolution of FY-4 provides minute-level data for research on snow monitoring, offering a more detailed understanding of changes in snow cover and clouds. To facilitate application for producers and reference for decision-makers, and to further improve the accuracy of snow depth inversion products, this paper is based on the hourly field snow depth observation data, daily FY-3D_SNC data, and the hourly FY-4A satellite data. A snow identification method based on NDSI (Normalized Difference Snow Index) is being constructed, as well as a snow depth monitoring model. In the end, referring to the existing snow depth classification standards on the Qinghai Tibet Plateau, a classification standard for snow depth levels in shallow snow areas using FY-4 satellite is proposed, based on NDSI and the linear estimation equation of snow depth. Mapping examples of different snow depth levels in plateau areas have been completed to better provide reference for practical business monitoring services and applications. The results show that NDSI≥0.20 is the reasonable threshold for FY-4A satellite snow detection in the Qinghai Tibet Plateau region, with a missing detection rate of less than 8.0% regardless of cloud conditions. The ground station verification results show that the accuracy of snow recognition is over 83.33%. After the cloud is directly removed in the spatial range, the accuracy of snow identification is more than 82.48%, verified by the confusion matrix. Therefore, the FY4 satellite has the ability to monitor snow cover in the Qinghai Tibet Plateau region. Although the FY-4A satellite does not have the ability to distinguish snow depths exceeding 10 cm, it can effectively identify shallow snow depths below 10 cm, with a correlation coefficient of 0.745, passing the 0.001 significance level. As a result, the FY-4A satellite snow depth level index of 0 to 10 cm has been established, with an overall classification accuracy of 87.50%. Hence, the FY-4A satellite snow depth inversion method has good estimation ability for 0 to 10 cm shallow snow depths in the Qinghai Tibet Plateau region.
Monitoring the snow cover on the Qinghai Tibet Plateau holds great significance for climate prediction and snow disaster prediction, among other things. With its high temporal resolution and high spatial resolution, FY-4 data is providing a new field in snow monitoring service by geostationary satellite. Constructing snow monitoring methods and models based on FY-4A not only expands the application field of geostationary satellites but also enriches the means of snow monitoring application. The high temporal resolution of FY-4 provides minute-level data for research on snow monitoring, offering a more detailed understanding of changes in snow cover and clouds. To facilitate application for producers and reference for decision-makers, and to further improve the accuracy of snow depth inversion products, this paper is based on the hourly field snow depth observation data, daily FY-3D_SNC data, and the hourly FY-4A satellite data. A snow identification method based on NDSI (Normalized Difference Snow Index) is being constructed, as well as a snow depth monitoring model. In the end, referring to the existing snow depth classification standards on the Qinghai Tibet Plateau, a classification standard for snow depth levels in shallow snow areas using FY-4 satellite is proposed, based on NDSI and the linear estimation equation of snow depth. Mapping examples of different snow depth levels in plateau areas have been completed to better provide reference for practical business monitoring services and applications. The results show that NDSI≥0.20 is the reasonable threshold for FY-4A satellite snow detection in the Qinghai Tibet Plateau region, with a missing detection rate of less than 8.0% regardless of cloud conditions. The ground station verification results show that the accuracy of snow recognition is over 83.33%. After the cloud is directly removed in the spatial range, the accuracy of snow identification is more than 82.48%, verified by the confusion matrix. Therefore, the FY4 satellite has the ability to monitor snow cover in the Qinghai Tibet Plateau region. Although the FY-4A satellite does not have the ability to distinguish snow depths exceeding 10 cm, it can effectively identify shallow snow depths below 10 cm, with a correlation coefficient of 0.745, passing the 0.001 significance level. As a result, the FY-4A satellite snow depth level index of 0 to 10 cm has been established, with an overall classification accuracy of 87.50%. Hence, the FY-4A satellite snow depth inversion method has good estimation ability for 0 to 10 cm shallow snow depths in the Qinghai Tibet Plateau region.
2023, 51(5):629-638.
DOI: 10.19517/j.1671-6345.20220199
Abstract:
Aiming at the problem of uncertainty regarding the threshold parameters in the quality control of radiosonde temperature using the bi-weight standard deviation method, an optimization algorithm for threshold Z parameters based on the skewness and normal waveform indicators is being proposed. By utilizing the temperature data from three radiosonde stations in Fujian in 2017 and the ERA5 model reanalysis temperature data, a comparative analysis of the different datasets of the sounding temperature increment data before and after quality control is conducted. The distribution curve of the kurtosis-skewness value CKS with threshold Z indicates that a higher threshold Z will result in incomplete quality control, while a lower threshold Z will result in excessive quality control. The optimal threshold Z of the bi-weight standard deviation method, as determined by the kurtosis-skewness value CKS, is more consistent with the normal distribution requirements of the model assimilation system than the fixed threshold of the bi-weight standard deviation method. This provides a better method for quality control of radiosonde temperature data in model assimilation. Regarding the distribution characteristics of temperature increment before and after quality control, the temperature observation increment consistently removes outliers from the entire pressure atmosphere using a fixed increment value. Around 57.15% of outliers are primarily distributed in the range of 0-100 hPa, while the remaining 42.85% of outliers are evenly distributed in the range of 100-1000 hPa. The abnormal points, where the absolute value of temperature increment within the range of 0-100 hPa is greater than 10 ℃, are caused by factors such as solar radiation affecting the temperature sensor, which exceed the normal detection error range. These abnormal points can be removed in advance before quality control, further improving the quality of radiosonde temperature data.
Aiming at the problem of uncertainty regarding the threshold parameters in the quality control of radiosonde temperature using the bi-weight standard deviation method, an optimization algorithm for threshold Z parameters based on the skewness and normal waveform indicators is being proposed. By utilizing the temperature data from three radiosonde stations in Fujian in 2017 and the ERA5 model reanalysis temperature data, a comparative analysis of the different datasets of the sounding temperature increment data before and after quality control is conducted. The distribution curve of the kurtosis-skewness value CKS with threshold Z indicates that a higher threshold Z will result in incomplete quality control, while a lower threshold Z will result in excessive quality control. The optimal threshold Z of the bi-weight standard deviation method, as determined by the kurtosis-skewness value CKS, is more consistent with the normal distribution requirements of the model assimilation system than the fixed threshold of the bi-weight standard deviation method. This provides a better method for quality control of radiosonde temperature data in model assimilation. Regarding the distribution characteristics of temperature increment before and after quality control, the temperature observation increment consistently removes outliers from the entire pressure atmosphere using a fixed increment value. Around 57.15% of outliers are primarily distributed in the range of 0-100 hPa, while the remaining 42.85% of outliers are evenly distributed in the range of 100-1000 hPa. The abnormal points, where the absolute value of temperature increment within the range of 0-100 hPa is greater than 10 ℃, are caused by factors such as solar radiation affecting the temperature sensor, which exceed the normal detection error range. These abnormal points can be removed in advance before quality control, further improving the quality of radiosonde temperature data.
2023, 51(5):639-647.
DOI: 10.19517/j.1671-6345.20220267
Abstract:
The layout quality of the meteorological station network directly affects the efficiency of observation data use. The existing surface precipitation station network in Sichuan Province is analyzed from the perspectives of the horizontal station spacing, vertical layer distribution, slope, river basin, risk zoning, station control range, and grid coverage, aiming to provide a scientific basis for the subsequent increase or decrease of stations and the optimisation of station network layout. The results show that: (1) The average horizontal station spacing of Sichuan precipitation stations is 9.04 km, which fully meets the requirements for climate monitoring by the World Meteorological Organisation OSCAR, and the “breakthrough” needs of global numerical weather forecasting, but there still exists a certain gap from the ideal “target”. (2) Over 80% of precipitation stations in Sichuan Province are located in low and medium-altitude areas, and 92.38% of precipitation stations are located in flat slopes, relatively flat slopes, gentle slopes, and relatively gentle slopes. (3) The area of the higher and highest-risk areas in Sichuan Province accounts for less than 40%, and the number of stations accounts for more than 50%. The density of the station network gradually increases with the risk area from low to high. (4) Stations with a control area of <100 km2 are primarily distributed in the Sichuan Basin. Stations in the Western Sichuan Plateau generally have a control area of more than 100 km2, and some stations have a control area of more than 1000 km2. (5) The grid coverage at different resolutions is highest in the Sichuan Basin, followed by the Panzhihua Xichang area, and the Western Sichuan Plateau is relatively low.
The layout quality of the meteorological station network directly affects the efficiency of observation data use. The existing surface precipitation station network in Sichuan Province is analyzed from the perspectives of the horizontal station spacing, vertical layer distribution, slope, river basin, risk zoning, station control range, and grid coverage, aiming to provide a scientific basis for the subsequent increase or decrease of stations and the optimisation of station network layout. The results show that: (1) The average horizontal station spacing of Sichuan precipitation stations is 9.04 km, which fully meets the requirements for climate monitoring by the World Meteorological Organisation OSCAR, and the “breakthrough” needs of global numerical weather forecasting, but there still exists a certain gap from the ideal “target”. (2) Over 80% of precipitation stations in Sichuan Province are located in low and medium-altitude areas, and 92.38% of precipitation stations are located in flat slopes, relatively flat slopes, gentle slopes, and relatively gentle slopes. (3) The area of the higher and highest-risk areas in Sichuan Province accounts for less than 40%, and the number of stations accounts for more than 50%. The density of the station network gradually increases with the risk area from low to high. (4) Stations with a control area of <100 km2 are primarily distributed in the Sichuan Basin. Stations in the Western Sichuan Plateau generally have a control area of more than 100 km2, and some stations have a control area of more than 1000 km2. (5) The grid coverage at different resolutions is highest in the Sichuan Basin, followed by the Panzhihua Xichang area, and the Western Sichuan Plateau is relatively low.
2023, 51(5):648-657.
DOI: 10.19517/j.1671-6345.20220277
Abstract:
Limited by the geographical environment, communication conditions, and personnel support capacity, the scientific investigation data of the Qinghai-Tibet Plateau cannot be collected and transmitted through the existing meteorological communication system. This has been a challenging problem for meteorological researchers. Relying on the public cloud resources of telecom operators, the author has established a scientific research data collection and transmission platform and is carrying out a significant amount of scientific research observation data collection and transmission work in Motuo, Tibet. The platform utilizes a high-concurrency data acquisition and distributed parallel processing framework to achieve continuous and orderly work of data collection, processing, distribution, monitoring, and other applications on a single server. It also provides targeted monitoring and archiving services for data in combination with the characteristics of scientific research instruments. Additionally, the author has designed and implemented a lightweight data upload client to address the data acquisition problem of scientific observation equipment deployed in the field. The platform’s design can be applied to the collection and transmission of scientific observation data in other regions.
Limited by the geographical environment, communication conditions, and personnel support capacity, the scientific investigation data of the Qinghai-Tibet Plateau cannot be collected and transmitted through the existing meteorological communication system. This has been a challenging problem for meteorological researchers. Relying on the public cloud resources of telecom operators, the author has established a scientific research data collection and transmission platform and is carrying out a significant amount of scientific research observation data collection and transmission work in Motuo, Tibet. The platform utilizes a high-concurrency data acquisition and distributed parallel processing framework to achieve continuous and orderly work of data collection, processing, distribution, monitoring, and other applications on a single server. It also provides targeted monitoring and archiving services for data in combination with the characteristics of scientific research instruments. Additionally, the author has designed and implemented a lightweight data upload client to address the data acquisition problem of scientific observation equipment deployed in the field. The platform’s design can be applied to the collection and transmission of scientific observation data in other regions.
2023, 51(5):658-667.
DOI: 10.19517/j.1671-6345.20220330
Abstract:
In order to achieve the goal of integrating provincial meteorological service data resources and unifying meteorological service export, promote the efficient application of meteorological data products in disaster prevention and public services, based on the Spring Cloud framework, the Hunan meteorological service platform is developed using Software Plugin, WebSerivce and other technologies. This paper introduces the layered model and functional structure of this platform and the key technologies such as multi-source meteorological data fusion processing, data parallel processing based on microservice, data vectorization based on SVG, and data secure interaction. The platform obtains meteorological data from CMADaas, packages them into the data plugin, graphic plugin and speciality plugin, provides meteorological products such as observation data, forecast, early warning, satellite cloud and Radar images through standard interfaces, and ensures the security of meteorological products service process based on MOID. The meteorological service plugin of this platform has been applied to the application systems of the Hunan Emergency Management Department, Natural Resources Department, Water Resources Department and other units. Application results indicate that the plugin service mode of this platform is suitable for different types of meteorological service needs, such as C/S clients, websites, and mobile apps. It realizes the unified management, efficient processing and standardized application of meteorological services and improves provincial meteorological service capabilities.
In order to achieve the goal of integrating provincial meteorological service data resources and unifying meteorological service export, promote the efficient application of meteorological data products in disaster prevention and public services, based on the Spring Cloud framework, the Hunan meteorological service platform is developed using Software Plugin, WebSerivce and other technologies. This paper introduces the layered model and functional structure of this platform and the key technologies such as multi-source meteorological data fusion processing, data parallel processing based on microservice, data vectorization based on SVG, and data secure interaction. The platform obtains meteorological data from CMADaas, packages them into the data plugin, graphic plugin and speciality plugin, provides meteorological products such as observation data, forecast, early warning, satellite cloud and Radar images through standard interfaces, and ensures the security of meteorological products service process based on MOID. The meteorological service plugin of this platform has been applied to the application systems of the Hunan Emergency Management Department, Natural Resources Department, Water Resources Department and other units. Application results indicate that the plugin service mode of this platform is suitable for different types of meteorological service needs, such as C/S clients, websites, and mobile apps. It realizes the unified management, efficient processing and standardized application of meteorological services and improves provincial meteorological service capabilities.
2023, 51(5):668-680.
DOI: 10.19517/j.1671-6345.20220379
Abstract:
The simulation of the extremely severe rainfall that occurred in Zhengzhou City, Henan Province, on 20 July 2021, is carried out to figure out the effects of topographic height and relief on water vapour transport and vertical conditions using the numerical model. The result shows that the CMA-MESO (GRAPES-MESO 3km) model’s simulation was satisfied with the actual situation for this process. However, the simulated precipitation centre was slightly to the west. The terrain had a significant impact on precipitation. The precipitation centre weakened when the terrain height decreased, and its position leaned toward the north. The precipitation centre strengthened when the terrain height increased, and its position leaned toward the south. The main influence mechanisms are as follows: (1) The upward effect of the Taihang Mountain and the mountain on the west side of Zhengzhou City resulted in a strong vertical ascending movement in the west of Zhengzhou City, and there was a deep convective system. The blocking effect of Funiu Mountain terrain had a significant effect on the north-south position of the vertical movement centre. Under the influence of the two typhoons, the warm and wet air coming from the southeast was formed, and the blocking effect of the southern part of Taihang Mountain caused part of the air in the north branch to deflect to the west and produced a southward component. That conjoined with the southerly airflow over Funiu Mountain and the southern branch of the southeast airflow, transported water vapour to the northwest under the blocking mountains such as Taihang Mountain and Songshan Mountain so that large-scale water vapour convergence was maintained over Zhengzhou City, and extremely heavy rain was generated. (2) With the increase of local height, part of the airflow from the north branch of the southeast airflow was blocked and turned into the northeast airflow, the intensity of the convergence zone of the airflow increased, the vertical velocity centre shifted to the south, and the water vapour content over Zhengzhou increased obviously. The southern branch of the southeast airflow also produced a strong updraft in the southwest of Zhengzhou under the effect of Funiu Mountain and formed two heavy precipitation centres near Zhengzhou, corresponding to Funiu Mountain and Songshan Mountain in the southwest and Taihang Mountain in the northwest, respectively. Under the uniform terrain condition, without the lifting and blocking effect of Taihang Mountain and Songshan Mountain, the water vapour accumulation over Zhengzhou decreased, the vertical movement centre moved northward, and the simulated precipitation centre was weaker than the real terrain condition, and the location was northward.
The simulation of the extremely severe rainfall that occurred in Zhengzhou City, Henan Province, on 20 July 2021, is carried out to figure out the effects of topographic height and relief on water vapour transport and vertical conditions using the numerical model. The result shows that the CMA-MESO (GRAPES-MESO 3km) model’s simulation was satisfied with the actual situation for this process. However, the simulated precipitation centre was slightly to the west. The terrain had a significant impact on precipitation. The precipitation centre weakened when the terrain height decreased, and its position leaned toward the north. The precipitation centre strengthened when the terrain height increased, and its position leaned toward the south. The main influence mechanisms are as follows: (1) The upward effect of the Taihang Mountain and the mountain on the west side of Zhengzhou City resulted in a strong vertical ascending movement in the west of Zhengzhou City, and there was a deep convective system. The blocking effect of Funiu Mountain terrain had a significant effect on the north-south position of the vertical movement centre. Under the influence of the two typhoons, the warm and wet air coming from the southeast was formed, and the blocking effect of the southern part of Taihang Mountain caused part of the air in the north branch to deflect to the west and produced a southward component. That conjoined with the southerly airflow over Funiu Mountain and the southern branch of the southeast airflow, transported water vapour to the northwest under the blocking mountains such as Taihang Mountain and Songshan Mountain so that large-scale water vapour convergence was maintained over Zhengzhou City, and extremely heavy rain was generated. (2) With the increase of local height, part of the airflow from the north branch of the southeast airflow was blocked and turned into the northeast airflow, the intensity of the convergence zone of the airflow increased, the vertical velocity centre shifted to the south, and the water vapour content over Zhengzhou increased obviously. The southern branch of the southeast airflow also produced a strong updraft in the southwest of Zhengzhou under the effect of Funiu Mountain and formed two heavy precipitation centres near Zhengzhou, corresponding to Funiu Mountain and Songshan Mountain in the southwest and Taihang Mountain in the northwest, respectively. Under the uniform terrain condition, without the lifting and blocking effect of Taihang Mountain and Songshan Mountain, the water vapour accumulation over Zhengzhou decreased, the vertical movement centre moved northward, and the simulated precipitation centre was weaker than the real terrain condition, and the location was northward.
2023, 51(5):681-692.
DOI: 10.19517/j.1671-6345.20220356
Abstract:
Typhoon Hagupit (No.04,2020) caused torrential rainfall in the mountain region as it passed over North Yandang Mountain after making landfall in the south coastal areas of Zhejiang Province. Based on the Weather Research and Forecast (WRF) version 4.0.2 mesoscale numerical model, a high-resolution numerical simulation is conducted on typhoon Hagupit to analyse the effect of North Yandang Mountain on the occurrence of this heavy rainstorm caused by the typhoon. Sensitivity experiments, which involve adjusting the terrain height by lifting or reducing it, are carried out to investigate the role of terrain. The results are as follows: The track and intensity of the typhoon were well simulated by the numerical experiment over time. The simulated torrential rain triggered by the typhoon was consistent with the observation, including the rainfall area and intensity. The distribution of the strong wind centre caused by typhoon Hagupit was noticeably asymmetric. The first and fourth quadrants of typhoon Hagupit successively passed over the mountain region after the typhoon made landfall, which transported sufficient water vapour to the mountain region through a strong southerly jet on the east side of the typhoon. A long and narrow spiralling convergence band was observed at low altitudes above the mountain region, which was brought from the inner core of typhoon Hagupit before the landfall. The location and distribution of the water vapour flux convergence band were consistent with the wind convergence band. Strong upward motion occurred on the windward slope along the heavy rain centres when the eyewall of the typhoon passed over, indicating favourable dynamic conditions for the formation of torrential rain. The water vapour transport band extended upward from the near surface into the lower atmosphere, and scattered convective cells started to be triggered and enhance in the mountain region simultaneously. As the back of typhoon Hagupit passed over, the winds weakened in the high altitude area of the mountain region, resulting in flow around and the formation of mesoscale vortices, which contributed to the heavy rainstorm. The primary reason for the appearance of torrential rainfall was the presence of a strong, persistent, and fixed positive vorticity centre on the windward slope of the heavy rain centre. In sensitive experiments involving the terrain height, it was observed that the accumulated precipitation decreased by 40% to 50% when the terrain height in North Yandang Mountain was set to zero, while it increased by over 60% when the terrain height was doubled in the mountain region.
Typhoon Hagupit (No.04,2020) caused torrential rainfall in the mountain region as it passed over North Yandang Mountain after making landfall in the south coastal areas of Zhejiang Province. Based on the Weather Research and Forecast (WRF) version 4.0.2 mesoscale numerical model, a high-resolution numerical simulation is conducted on typhoon Hagupit to analyse the effect of North Yandang Mountain on the occurrence of this heavy rainstorm caused by the typhoon. Sensitivity experiments, which involve adjusting the terrain height by lifting or reducing it, are carried out to investigate the role of terrain. The results are as follows: The track and intensity of the typhoon were well simulated by the numerical experiment over time. The simulated torrential rain triggered by the typhoon was consistent with the observation, including the rainfall area and intensity. The distribution of the strong wind centre caused by typhoon Hagupit was noticeably asymmetric. The first and fourth quadrants of typhoon Hagupit successively passed over the mountain region after the typhoon made landfall, which transported sufficient water vapour to the mountain region through a strong southerly jet on the east side of the typhoon. A long and narrow spiralling convergence band was observed at low altitudes above the mountain region, which was brought from the inner core of typhoon Hagupit before the landfall. The location and distribution of the water vapour flux convergence band were consistent with the wind convergence band. Strong upward motion occurred on the windward slope along the heavy rain centres when the eyewall of the typhoon passed over, indicating favourable dynamic conditions for the formation of torrential rain. The water vapour transport band extended upward from the near surface into the lower atmosphere, and scattered convective cells started to be triggered and enhance in the mountain region simultaneously. As the back of typhoon Hagupit passed over, the winds weakened in the high altitude area of the mountain region, resulting in flow around and the formation of mesoscale vortices, which contributed to the heavy rainstorm. The primary reason for the appearance of torrential rainfall was the presence of a strong, persistent, and fixed positive vorticity centre on the windward slope of the heavy rain centre. In sensitive experiments involving the terrain height, it was observed that the accumulated precipitation decreased by 40% to 50% when the terrain height in North Yandang Mountain was set to zero, while it increased by over 60% when the terrain height was doubled in the mountain region.
2023, 51(5):693-703.
DOI: 10.19517/j.1671-6345.20220354
Abstract:
The weather system on 600 hPa can analyse the main characteristics of the variation of low vortex over the western Sichuan Plateau and identify the relationship between the development and movement of low vortex and the heavy precipitation area over the western Sichuan Plateau. Therefore, we are currently analyzing the spatiotemporal distribution of the vortex on 600 hPa, the relationship between low vortex and precipitation, and dynamic and thermal characteristics of vortex causing rainfall in the western Sichuan Plateau in the summer half of the year by using the 3-hour ERA5 reanalysis data (0.25°×0.25°) and the hourly precipitation data from 2011 to 2020. The results show that there are 80 low vortices per year in 42 years, and the duration of less than one day accounts for 95.7% of the total. The formation and extinction of the low vortices are affected by the topography on the east side of the plateau and the obvious diurnal variation of surface temperature. The annual average number of the low vortices generated in the western Sichuan Plateau is 61.5. The annual average number of the low vortices which move in the western Sichuan Plateau is 18. And the annual average number of the low vortices which move out of the western Sichuan Plateau is 5.3. The source area of the low vortex is located in Baiyu County in Ganzi Prefecture. And the dissipation area of the low vortex is located in Litang County in Ganzi Prefecture. The low vortices with a life history longer than 12 h account for 36.4%，which will bring precipitation. And more than 83.7% of them will cause moderate rainfall or above. The central position of the maximum daily precipitation intensity associated with the low vortex moves from the eastern and southern parts of the western Sichuan Plateau to the central part each month, and then gradually moves back to the eastern and southern parts. Correspondingly, in July and August, majority low vortices move from the north and south to the centre and wobble away. In other months, majority low vortices formed in the centre will affect the east and south areas, or generated in the south and then stagnate or wobble in situ. Strong vertical upward motion, the coupling development of positive vorticity region and the formation and maintenance of the deep unstable stratification are the dynamic characteristics and thermodynamic stratification conditions of the generation and development of vortex, causing heavy precipitation.
The weather system on 600 hPa can analyse the main characteristics of the variation of low vortex over the western Sichuan Plateau and identify the relationship between the development and movement of low vortex and the heavy precipitation area over the western Sichuan Plateau. Therefore, we are currently analyzing the spatiotemporal distribution of the vortex on 600 hPa, the relationship between low vortex and precipitation, and dynamic and thermal characteristics of vortex causing rainfall in the western Sichuan Plateau in the summer half of the year by using the 3-hour ERA5 reanalysis data (0.25°×0.25°) and the hourly precipitation data from 2011 to 2020. The results show that there are 80 low vortices per year in 42 years, and the duration of less than one day accounts for 95.7% of the total. The formation and extinction of the low vortices are affected by the topography on the east side of the plateau and the obvious diurnal variation of surface temperature. The annual average number of the low vortices generated in the western Sichuan Plateau is 61.5. The annual average number of the low vortices which move in the western Sichuan Plateau is 18. And the annual average number of the low vortices which move out of the western Sichuan Plateau is 5.3. The source area of the low vortex is located in Baiyu County in Ganzi Prefecture. And the dissipation area of the low vortex is located in Litang County in Ganzi Prefecture. The low vortices with a life history longer than 12 h account for 36.4%，which will bring precipitation. And more than 83.7% of them will cause moderate rainfall or above. The central position of the maximum daily precipitation intensity associated with the low vortex moves from the eastern and southern parts of the western Sichuan Plateau to the central part each month, and then gradually moves back to the eastern and southern parts. Correspondingly, in July and August, majority low vortices move from the north and south to the centre and wobble away. In other months, majority low vortices formed in the centre will affect the east and south areas, or generated in the south and then stagnate or wobble in situ. Strong vertical upward motion, the coupling development of positive vorticity region and the formation and maintenance of the deep unstable stratification are the dynamic characteristics and thermodynamic stratification conditions of the generation and development of vortex, causing heavy precipitation.
2023, 51(5):704-714.
DOI: 10.19517/j.1671-6345.20220229
Abstract:
Based on conventional observation data, dual-polarisation radar data, and raindrop spectrometer data, different phases of rain, sleet, and pure snow caused by a rare cold wave that occurred in Changzhou on 28 March 2020 are analyzed. The results show that: (1) The impact of this intense cold wave weather happened in the winter and spring alternating season at the end of March. There was a severe drop in cooling weather in Changzhou (the temperate drop in early spring ranked second in history), and light rain, light sleet, or light snow occurred successively. During the cold wave, the temperature fell sharply twice. The first drop (8.7 ℃ in 6 h) was caused by the weak cold air at the surface. The second cooling period (2 h drop of 5.0 ℃ during this time) occurred primarily due to a combination of high altitude trough, mid to low-level shear, and surface cold high pressure, as well as strong cold advection intrusion and the absorption of evaporative (or sublimative) heat by an apparent dry layer at 850 hPa. This triggered a sharp decrease in temperature at the mid and low levels during precipitation, causing the entire layer to become a cold layer and remained low. This provided favourable conditions for the rain to turn into snow, resulting in rapid changes in the precipitation phase. (2) The dual-polarisation radar determined that the three precipitation phases displayed different polarisation variable characteristics. When the precipitation phase changed to sleet, Z increased, Z DR increased significantly, C C showed an evident low-value zonal distribution, and KDP increased slightly. During the transition from sleet to pure snow, the mixed region of rain and snow phase composed of Z>30 dBz, Z DR >1 dB, C C <0.95 was gradually pressured south, and then became Z>22 dBz, Z DR <1 dB,C C >0.98 pure snow, and K DP decreased slightly. It was also observed that dual-polarisation radar had more reference significance for monitoring precipitation in different phase states than single polarisation radar. (3) The rain phase consisted of high-concentration small particles and low-concentration large particles. The raindrop speed-scale spectrum presented a slanted band, which conformed to the Brandes experience curve, characterised by a large falling velocity and small particle diameter. In the stage of sleet, the number concentration decreased, the particle size range broadened, Dm increased significantly, and the maximum diameter approached 6 mm. The range of raindrop velocity and particle size fell between rain and pure snow. In the pure snow stage, at the beginning of the snow, the snow intensity was small, and the number concentration decreased significantly. As the snow intensity increased, the number concentration increased, nearing 2.2 m-3mm-1. The spectral width of particles widened rapidly, and there were more large particles. The concentration of small particles was larger, whilst the concentration of large particles was smaller.
Based on conventional observation data, dual-polarisation radar data, and raindrop spectrometer data, different phases of rain, sleet, and pure snow caused by a rare cold wave that occurred in Changzhou on 28 March 2020 are analyzed. The results show that: (1) The impact of this intense cold wave weather happened in the winter and spring alternating season at the end of March. There was a severe drop in cooling weather in Changzhou (the temperate drop in early spring ranked second in history), and light rain, light sleet, or light snow occurred successively. During the cold wave, the temperature fell sharply twice. The first drop (8.7 ℃ in 6 h) was caused by the weak cold air at the surface. The second cooling period (2 h drop of 5.0 ℃ during this time) occurred primarily due to a combination of high altitude trough, mid to low-level shear, and surface cold high pressure, as well as strong cold advection intrusion and the absorption of evaporative (or sublimative) heat by an apparent dry layer at 850 hPa. This triggered a sharp decrease in temperature at the mid and low levels during precipitation, causing the entire layer to become a cold layer and remained low. This provided favourable conditions for the rain to turn into snow, resulting in rapid changes in the precipitation phase. (2) The dual-polarisation radar determined that the three precipitation phases displayed different polarisation variable characteristics. When the precipitation phase changed to sleet, Z increased, Z DR increased significantly, C C showed an evident low-value zonal distribution, and KDP increased slightly. During the transition from sleet to pure snow, the mixed region of rain and snow phase composed of Z>30 dBz, Z DR >1 dB, C C <0.95 was gradually pressured south, and then became Z>22 dBz, Z DR <1 dB,C C >0.98 pure snow, and K DP decreased slightly. It was also observed that dual-polarisation radar had more reference significance for monitoring precipitation in different phase states than single polarisation radar. (3) The rain phase consisted of high-concentration small particles and low-concentration large particles. The raindrop speed-scale spectrum presented a slanted band, which conformed to the Brandes experience curve, characterised by a large falling velocity and small particle diameter. In the stage of sleet, the number concentration decreased, the particle size range broadened, Dm increased significantly, and the maximum diameter approached 6 mm. The range of raindrop velocity and particle size fell between rain and pure snow. In the pure snow stage, at the beginning of the snow, the snow intensity was small, and the number concentration decreased significantly. As the snow intensity increased, the number concentration increased, nearing 2.2 m-3mm-1. The spectral width of particles widened rapidly, and there were more large particles. The concentration of small particles was larger, whilst the concentration of large particles was smaller.
2023, 51(5):715-727.
DOI: 10.19517/j.1671-6345.20220367
Abstract:
The urban heat island effect is one of the primary manifestations of the impact of human activities on the atmospheric system. In this paper, the Space and Time Multiscale Analysis System (STMAS) is used to fuse multi-source high spatial and temporal resolution observations from automatic ground stations, radars, satellites and other sources, and establish a three-dimensional data set of urban heat island. Moreover, on this basis, the characteristics of the intensity change of Beijing urban heat island are statistically analyzed, and a case of an ultrastrong urban heat island (June 11-12, 2021) is selected to analyze its three-dimensional fine structure characteristics in detail. The results show that: (1) In the case of the heat island, the suburban near-surfaces cooled rapidly at night, forming an inversion layer, while the temperature of the urban near-surface decreased slowly, which made the temperature difference between suburban and urban near-surface increased continuously. (2) The warm core structure of the three-dimensional temperature field of this ultrastrong urban heat island was clearly visible in the isobaric surface on the ground and near ground isobaric surfaces below 990 hPa. The wind field anomaly showed the characteristics of cyclonic circulation. It converged from suburb to urban area at low height, causing upward movement that could reach middle and high heights, indicating that the urban heat island effect could enhance the vertical circulation.
The urban heat island effect is one of the primary manifestations of the impact of human activities on the atmospheric system. In this paper, the Space and Time Multiscale Analysis System (STMAS) is used to fuse multi-source high spatial and temporal resolution observations from automatic ground stations, radars, satellites and other sources, and establish a three-dimensional data set of urban heat island. Moreover, on this basis, the characteristics of the intensity change of Beijing urban heat island are statistically analyzed, and a case of an ultrastrong urban heat island (June 11-12, 2021) is selected to analyze its three-dimensional fine structure characteristics in detail. The results show that: (1) In the case of the heat island, the suburban near-surfaces cooled rapidly at night, forming an inversion layer, while the temperature of the urban near-surface decreased slowly, which made the temperature difference between suburban and urban near-surface increased continuously. (2) The warm core structure of the three-dimensional temperature field of this ultrastrong urban heat island was clearly visible in the isobaric surface on the ground and near ground isobaric surfaces below 990 hPa. The wind field anomaly showed the characteristics of cyclonic circulation. It converged from suburb to urban area at low height, causing upward movement that could reach middle and high heights, indicating that the urban heat island effect could enhance the vertical circulation.
2023, 51(5):728-737.
DOI: 10.19517/j.1671-6345.20220313
Abstract:
With the economic and social development of Shihezi, especially the continuous advancement of industrialization, the pollution weather caused by the haze weather in Shihezi occurs frequently in winter. The heavy pollution weather caused by the haze in winter in 2019 has exceeded 50 days, and the ambient air quality has been deteriorating. In this paper, an analysis is made to investigate the impact of artificial smog dispersal in Shihezi, north of Tianshan Mountain, using the data of extinction coefficient observed by the aerosol lidar in Shihezi in December 2019. The methods mainly adopt the physical statistical test method of weather modification, such as the sign test, pairwise rank sum test of inspection, nonparametric tests, and parametric t-test. The smog reduction effect is obtained based on the extinction coefficient of aerosol lidar. In addition, the ground station monitoring cannot obtain the vertical distribution characteristics and evolution law of pollution. At present, most scholars use aerosol lidar to fill this monitoring gap and realize three-dimensional monitoring of the pollution process. The results are as follows: 20 minutes after the artificial smog dispersal operation, the reliability of the reduction of the average extinction coefficient at different heights below 400 m is 99.5%. Further, according to the 95% confidence threshold, the reduction value is 0.05, and the reduction rate is 9.8%. The reliability of the positive effect obtained by the pairwise rank sum test is 97.5%, which is very significant. However, the reliability of the positive effect obtained by the parametric t-test is only 90% to 80%, which does not reach the threshold of 99.5%, indicating a general significance. This is related to the fact that different types of catalysts are used in operation, such as only hygroscopic dry powder catalyst, and that the variation effect of extinction coefficient as samples cannot meet the test efficiency due to the high seeding height. Further analysis shows that the response effect of reducing the extinction coefficient at different heights below 400 meters decreases from top to bottom 20 minutes after the aircraft’s manual haze reduction operation, which is consistent with the gradual response process of the physical mechanism of the catalyst effect that artificially affects the operation seeding from top to bottom. In China, meteorologists have used weather modification to improve the quality of ambient air. In terms of this paper, the weather modification technology is used to carry out the winter haze reduction test in Shihezi. In the course of the test, the extinction coefficient detected by aerosol lidar is utilized to preliminarily analyze the test effect, which is the first time in China.
With the economic and social development of Shihezi, especially the continuous advancement of industrialization, the pollution weather caused by the haze weather in Shihezi occurs frequently in winter. The heavy pollution weather caused by the haze in winter in 2019 has exceeded 50 days, and the ambient air quality has been deteriorating. In this paper, an analysis is made to investigate the impact of artificial smog dispersal in Shihezi, north of Tianshan Mountain, using the data of extinction coefficient observed by the aerosol lidar in Shihezi in December 2019. The methods mainly adopt the physical statistical test method of weather modification, such as the sign test, pairwise rank sum test of inspection, nonparametric tests, and parametric t-test. The smog reduction effect is obtained based on the extinction coefficient of aerosol lidar. In addition, the ground station monitoring cannot obtain the vertical distribution characteristics and evolution law of pollution. At present, most scholars use aerosol lidar to fill this monitoring gap and realize three-dimensional monitoring of the pollution process. The results are as follows: 20 minutes after the artificial smog dispersal operation, the reliability of the reduction of the average extinction coefficient at different heights below 400 m is 99.5%. Further, according to the 95% confidence threshold, the reduction value is 0.05, and the reduction rate is 9.8%. The reliability of the positive effect obtained by the pairwise rank sum test is 97.5%, which is very significant. However, the reliability of the positive effect obtained by the parametric t-test is only 90% to 80%, which does not reach the threshold of 99.5%, indicating a general significance. This is related to the fact that different types of catalysts are used in operation, such as only hygroscopic dry powder catalyst, and that the variation effect of extinction coefficient as samples cannot meet the test efficiency due to the high seeding height. Further analysis shows that the response effect of reducing the extinction coefficient at different heights below 400 meters decreases from top to bottom 20 minutes after the aircraft’s manual haze reduction operation, which is consistent with the gradual response process of the physical mechanism of the catalyst effect that artificially affects the operation seeding from top to bottom. In China, meteorologists have used weather modification to improve the quality of ambient air. In terms of this paper, the weather modification technology is used to carry out the winter haze reduction test in Shihezi. In the course of the test, the extinction coefficient detected by aerosol lidar is utilized to preliminarily analyze the test effect, which is the first time in China.
2023, 51(5):738-746.
DOI: 10.19517/j.1671-6345.2022.372
Abstract:
The occurrence process of flood disasters has a certain degree of predictability. Predictive analysis of flood risk can mitigate or reduce the impact of disasters and improve disaster prevention and reduction capabilities. The analysis of flood hazard warning is an important foundation for disaster prevention and reduction. Early warning before the occurrence of disasters can effectively reduce the impact of disasters. The research is focused on flood disasters in the Yangtze River-Huaihe River basin during June to August 2020. This paper aims to develop an improved flood hazard risk warning analysis model using the Analytic Hierarchy Process (AHP) and multiple triggering and predisposing factors. Triggering factors, including cumulative precipitation in the previous three days, current soil moisture, and forecasted precipitation, are crucial in assessing the immediate risks of flood disasters. Predisposing factors, such as river network density, terrain elevation, terrain amplitude, and land use data, provide insights into the vulnerability of the region to flood disasters. By combining these factors, we can effectively evaluate the flood risk and issue timely warnings to mitigate the impact of disasters. To validate the effectiveness of the proposed model, we compare the evaluation results with the flood disaster information reported in the “Meteorological Disaster Management System” of the China Meteorological Administration. The evaluation accuracy rate, which measures the agreement between the risk assessment and the actual occurrence of disasters, reaches 74.46%. This indicates that the model has a relatively high accuracy in predicting flood risks. Additionally, the missing rate, which measures the proportion of missed warnings, is only 5.59%, demonstrating the model’s ability to effectively capture potential flood disasters. Furthermore, the evaluation results show a good correlation between the risk assessment and the actual occurrence of disasters. The warning rate of the maximum disaster unit index, which represents the highest risk within a county, reaches 81.6%. Moreover, for “extreme” heavy rain and flood disasters, the warning rate exceeds 77.3%. This suggests that the proposed model is particularly effective in predicting and warning against severe flood disasters. In terms of temporal consistency evaluation, the risk index consistently increases 3-5 days before the occurrence of “extreme” heavy rain and flood disasters. In conclusion, the model’s high accuracy and reliability make it a valuable tool for decision-making in disaster prevention and reduction efforts. By providing timely and accurate warnings, the model can significantly mitigate the impact of flood disasters and improve the region’s resilience to such events. Future research can focus on further refining the model and incorporating additional factors to enhance its predictive capabilities.
The occurrence process of flood disasters has a certain degree of predictability. Predictive analysis of flood risk can mitigate or reduce the impact of disasters and improve disaster prevention and reduction capabilities. The analysis of flood hazard warning is an important foundation for disaster prevention and reduction. Early warning before the occurrence of disasters can effectively reduce the impact of disasters. The research is focused on flood disasters in the Yangtze River-Huaihe River basin during June to August 2020. This paper aims to develop an improved flood hazard risk warning analysis model using the Analytic Hierarchy Process (AHP) and multiple triggering and predisposing factors. Triggering factors, including cumulative precipitation in the previous three days, current soil moisture, and forecasted precipitation, are crucial in assessing the immediate risks of flood disasters. Predisposing factors, such as river network density, terrain elevation, terrain amplitude, and land use data, provide insights into the vulnerability of the region to flood disasters. By combining these factors, we can effectively evaluate the flood risk and issue timely warnings to mitigate the impact of disasters. To validate the effectiveness of the proposed model, we compare the evaluation results with the flood disaster information reported in the “Meteorological Disaster Management System” of the China Meteorological Administration. The evaluation accuracy rate, which measures the agreement between the risk assessment and the actual occurrence of disasters, reaches 74.46%. This indicates that the model has a relatively high accuracy in predicting flood risks. Additionally, the missing rate, which measures the proportion of missed warnings, is only 5.59%, demonstrating the model’s ability to effectively capture potential flood disasters. Furthermore, the evaluation results show a good correlation between the risk assessment and the actual occurrence of disasters. The warning rate of the maximum disaster unit index, which represents the highest risk within a county, reaches 81.6%. Moreover, for “extreme” heavy rain and flood disasters, the warning rate exceeds 77.3%. This suggests that the proposed model is particularly effective in predicting and warning against severe flood disasters. In terms of temporal consistency evaluation, the risk index consistently increases 3-5 days before the occurrence of “extreme” heavy rain and flood disasters. In conclusion, the model’s high accuracy and reliability make it a valuable tool for decision-making in disaster prevention and reduction efforts. By providing timely and accurate warnings, the model can significantly mitigate the impact of flood disasters and improve the region’s resilience to such events. Future research can focus on further refining the model and incorporating additional factors to enhance its predictive capabilities.
2023, 51(5):747-754.
DOI: 10.19517/j.1671-6345.20220347
Abstract:
Lightning disasters are now recognised as one of the top ten most severe natural calamities, being particularly frequent in mountainous areas. The continuous growth of tourism has led to significant impacts on tourists and cable cars, especially in mountainous scenic areas, where equipment like cable cars are highly sensitive to lightning. To investigate the key factors influencing lightning development in these regions and to promptly understand the trends in lightning activity in and around the Huangshan Scenic Area, we are leveraging multiple monitoring data, such as Doppler weather radar, meteorological soundings, and lightning detection. In this study, we are building and evaluating multiple lightning nowcasting models using different machine learning algorithms. The models are based on the non-inductive charging mechanism in the thunderstorm and the characteristics of Doppler weather radar echo. We are extracting echo characteristics of the Doppler weather radar as key forecasting factors, focusing on the intensity, vigour, and movement trends of the thunderstorm system. By comparing false alarm rates, missed alarm rates, and TS scores of various machine learning algorithms, we are selecting the most suitable forecast method for mountainous scenic areas. Our evaluation results reveal that the Random Forest (RF), Logistic Regression (LR), K-Nearest Neighbour (KNN), Gaussian Naive Bayes (GNB), and Support Vector Machine (SVM) algorithms all have certain nowcasting capabilities for lightning. The RF algorithm scores highest in TS scoring, the SVM has the lowest missed alarm rate, and LR has the lowest false alarm rate. Among these, the intensity and vigorous development of the thunderstorm system play a pivotal role in the RF algorithm, with the radar base reflectivity at the -20 ℃ layer height in the thunderstorm system intensity having the most influence, followed by the radar echo thickness above the 0 ℃ layer. Taking an example on 29 August 2021, when a large-scale intense thunderstorm occurred in and around the Huangshan Scenic Area in the afternoon. Employing the RF method resulted in a false alarm rate of 0.425, a missed alarm rate of 0.378, and a TS score of 0.426, indicating good forecasting performance in the area.
Lightning disasters are now recognised as one of the top ten most severe natural calamities, being particularly frequent in mountainous areas. The continuous growth of tourism has led to significant impacts on tourists and cable cars, especially in mountainous scenic areas, where equipment like cable cars are highly sensitive to lightning. To investigate the key factors influencing lightning development in these regions and to promptly understand the trends in lightning activity in and around the Huangshan Scenic Area, we are leveraging multiple monitoring data, such as Doppler weather radar, meteorological soundings, and lightning detection. In this study, we are building and evaluating multiple lightning nowcasting models using different machine learning algorithms. The models are based on the non-inductive charging mechanism in the thunderstorm and the characteristics of Doppler weather radar echo. We are extracting echo characteristics of the Doppler weather radar as key forecasting factors, focusing on the intensity, vigour, and movement trends of the thunderstorm system. By comparing false alarm rates, missed alarm rates, and TS scores of various machine learning algorithms, we are selecting the most suitable forecast method for mountainous scenic areas. Our evaluation results reveal that the Random Forest (RF), Logistic Regression (LR), K-Nearest Neighbour (KNN), Gaussian Naive Bayes (GNB), and Support Vector Machine (SVM) algorithms all have certain nowcasting capabilities for lightning. The RF algorithm scores highest in TS scoring, the SVM has the lowest missed alarm rate, and LR has the lowest false alarm rate. Among these, the intensity and vigorous development of the thunderstorm system play a pivotal role in the RF algorithm, with the radar base reflectivity at the -20 ℃ layer height in the thunderstorm system intensity having the most influence, followed by the radar echo thickness above the 0 ℃ layer. Taking an example on 29 August 2021, when a large-scale intense thunderstorm occurred in and around the Huangshan Scenic Area in the afternoon. Employing the RF method resulted in a false alarm rate of 0.425, a missed alarm rate of 0.378, and a TS score of 0.426, indicating good forecasting performance in the area.
2023, 51(5):755-763.
DOI: 10.19517/j.1671-6345.20220319
Abstract:
Lightning protection is a measure taken to prevent and reduce material losses and loss of life or personal injury caused by lightning strikes. Lightning protection facilities are easily affected by the external environment and their decreasing performance. Therefore, it is of great significance to evaluate the protection ability of lightning protection measures scientifically to ensure and improve the protection effect. The advantages and disadvantages of fault tree analysis, Bayesian network evaluation, neural network, failure mode analysis, Kent score, and principal component analysis are discussed. Based on the characteristics of coupling and fuzziness of lightning protection measures and the requirement of reasonably determining evaluation index weight, the fuzzy comprehensive evaluation based on improved analytic hierarchy process is proposed. According to the relevant technical standards and norms of lightning protection, considering the impact of the lightning environment, carrier characteristics, and natural factors, an evaluation index system of lightning protection capability with 6 primary indexes and 17 secondary indexes is established. The weights of each index are calculated by establishing a comparison matrix, calculating importance ranking index, constructing a judgment matrix, calculating a transfer matrix, constructing an optimal transfer matrix, calculating a quasi-optimal consistent matrix, solving the feature vector, and so on. The evaluation set and membership matrix of fuzzy comprehensive evaluation are established, and the single index fuzzy evaluation is carried out by using the weight vector and membership matrix corresponding to the evaluation level. The multi-index fuzzy comprehensive evaluation is carried out by using a new matrix composed of a single index evaluation vector and an index weight vector. The evaluation grade of lightning protection capability is determined by the principle of maximum membership degree. This method is used to evaluate the lightning protection ability of the oil and gas gathering station library containing an inflammable and explosive production area, information control function area, and power system function area. The evaluation level is consistent with the actual situation and related literature cases, indicating the applicability and correctness of the method, and providing guidance for the improvement of lightning protection measures and lightning protection ability.
Lightning protection is a measure taken to prevent and reduce material losses and loss of life or personal injury caused by lightning strikes. Lightning protection facilities are easily affected by the external environment and their decreasing performance. Therefore, it is of great significance to evaluate the protection ability of lightning protection measures scientifically to ensure and improve the protection effect. The advantages and disadvantages of fault tree analysis, Bayesian network evaluation, neural network, failure mode analysis, Kent score, and principal component analysis are discussed. Based on the characteristics of coupling and fuzziness of lightning protection measures and the requirement of reasonably determining evaluation index weight, the fuzzy comprehensive evaluation based on improved analytic hierarchy process is proposed. According to the relevant technical standards and norms of lightning protection, considering the impact of the lightning environment, carrier characteristics, and natural factors, an evaluation index system of lightning protection capability with 6 primary indexes and 17 secondary indexes is established. The weights of each index are calculated by establishing a comparison matrix, calculating importance ranking index, constructing a judgment matrix, calculating a transfer matrix, constructing an optimal transfer matrix, calculating a quasi-optimal consistent matrix, solving the feature vector, and so on. The evaluation set and membership matrix of fuzzy comprehensive evaluation are established, and the single index fuzzy evaluation is carried out by using the weight vector and membership matrix corresponding to the evaluation level. The multi-index fuzzy comprehensive evaluation is carried out by using a new matrix composed of a single index evaluation vector and an index weight vector. The evaluation grade of lightning protection capability is determined by the principle of maximum membership degree. This method is used to evaluate the lightning protection ability of the oil and gas gathering station library containing an inflammable and explosive production area, information control function area, and power system function area. The evaluation level is consistent with the actual situation and related literature cases, indicating the applicability and correctness of the method, and providing guidance for the improvement of lightning protection measures and lightning protection ability.
LI Xiali
,
DUAN Chunfeng
,
FENG Ying
,
PAN Xianjie
,
WANG Yazheng
,
SHAO Chenli
,
YAN Shaowei
,
ZHANG Guoling
2023, 51(5):764-770.
DOI: 10.19517/j.1671-6345.20220213
Abstract:
Based on the observation data of the open-circuit CH4 gas analyzer at Shouxian National Climatological Observatory, we analyze the variation characteristics and influencing factors of CH4 flux in different growth periods of rice-wheat rotation farmland in the Huaihe River Basin. The results show that CH4 flux in the Huaihe River Basin has a single peak distribution throughout the year, with the peak occurring in summer. The diurnal variation of CH4 flux shows a single peak during the day, and the peaks mostly appear in the afternoon. CH4 flux during the day is higher than at night. CH4 flux in the rice growth period is significantly higher than that in the wheat growth period. During the wheat growth period, CH4 flux is the smallest during the seedling period but the largest during the mature period, reaching 0.14 μg ·m-2·s-1. During the rice growth period, the maximum CH4 flux during the jointing period is 3.02 μg ·m-2·s-1, and the minimum during the maturity stage is 0.12 μg ·m-2·s-1. CH4 flux decreases by 50% and 30% before and after the harvest of rice and wheat. This study shows that crop biomass has a significant impact on CH4 flux. CH4 flux is positively correlated with precipitation, relative humidity, water vapour pressure, soil temperature, and air temperature. When precipitation, humidity, or air temperature is higher, the CH4 flux will be greater.
Based on the observation data of the open-circuit CH4 gas analyzer at Shouxian National Climatological Observatory, we analyze the variation characteristics and influencing factors of CH4 flux in different growth periods of rice-wheat rotation farmland in the Huaihe River Basin. The results show that CH4 flux in the Huaihe River Basin has a single peak distribution throughout the year, with the peak occurring in summer. The diurnal variation of CH4 flux shows a single peak during the day, and the peaks mostly appear in the afternoon. CH4 flux during the day is higher than at night. CH4 flux in the rice growth period is significantly higher than that in the wheat growth period. During the wheat growth period, CH4 flux is the smallest during the seedling period but the largest during the mature period, reaching 0.14 μg ·m-2·s-1. During the rice growth period, the maximum CH4 flux during the jointing period is 3.02 μg ·m-2·s-1, and the minimum during the maturity stage is 0.12 μg ·m-2·s-1. CH4 flux decreases by 50% and 30% before and after the harvest of rice and wheat. This study shows that crop biomass has a significant impact on CH4 flux. CH4 flux is positively correlated with precipitation, relative humidity, water vapour pressure, soil temperature, and air temperature. When precipitation, humidity, or air temperature is higher, the CH4 flux will be greater.
External LinksChina Meteorological AdministrationCMA Meteorological Observation CentreChinese Academy of Meteorological SciencesBeijing Meteorological ServiceNational Satellite Meteorological Center
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Supported by:Beijing E-Tiller Technology Development Co., Ltd.
Supported by:Beijing E-Tiller Technology Development Co., Ltd.