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Abstract: To harness the benefits derived from the high spatial and temporal resolution of vertically continuous wind profile radar observations and exploit its capacity for monitoring atmospheric diffusion conditions during pollution events, this paper calculates parameters such as vertical wind shear, divergence, vorticity, and boundary layer ventilation by utilising 13 sets of wind profile radar data in Hebei Province. The computations are based on the principles of atmospheric dynamics and the dynamic conditions inversion algorithm. By comparing the results with sounding data and analysing them in conjunction with near-surface PM2.5 concentration, the four parameter algorithms are examined. The results show that the variations and characteristics of the inversion products are reasonably represented, effectively reflecting the evolution of atmospheric pollution conditions. However, due to disparities in resolution and detection methods among different observational datasets, substantial discrepancies exist in the results derived from various datasets. Therefore, it is imperative to maintain data consistency when conducting analyses. Taking the regional PM2.5 pollution event in Hebei from 9 to 11 November 2022 as an example, through multi-site joint application, the evolution characteristics of the four products in this process indicate the following: during the pollution accumulation process, vertical wind shear below 3 km decreased from the diagonal to the lower right corner, with most values below 5 m/(s·km). Vorticity and divergence values were mostly within 20×10-5s-1, and less than 15×10-5 s-1 for distances below the 950 hPa isobaric surface, indicating a stable meteorological situation. Boundary layer ventilation was less than 3000 m2/s. Before the pollutant dispersal, vertical wind shear increased to above 10 m/(s·km) throughout the entire layer. The region with wind shear greater than 10 m/(s·km) between 2-3 km height and 0-1 km above the ground showed the strongest sensitivity to pollutant dispersion. Vorticity and divergence above the 850 hPa isobaric surface first increased to above 30×10-5s-1, and when vorticity and divergence above 20×10-5 s-1 extended within the boundary layer, the near-surface PM2.5 concentration rapidly decreased. When boundary layer ventilation reached 4000 m2/s, pollutant concentrations met the standards. The values at downstream stations increased significantly with a noticeable delay along the cold air transmission path, thus multi-station joint analysis could be used for pollution dispersion forecasts at downstream sites. By comparing with the data of airborne sounding and near-surface wind field, the wind profile data had obvious advantages of high temporal and spatial resolution. However, these parameters exclusively responded to atmospheric dynamic conditions and did not account for the evolving principles governing the weather system. The application was most effective when used in conjunction with the prevailing circulation patterns and the diagnostic analysis of the weather system.
Abstract: The standard deviation analysis method is crucial for effectively evaluating radar data quality. This study applies the standard deviation analysis to analyse the polarisation parameters of C-band dual-polarisation radar, identifying the main influencing factors and optimising parameter configurations. The improvement effects on the standard deviation of polarisation parameters across typical weather processes are examined through observational experiments. The findings indicate that the accuracy of existing observational modes for C-band polarisation parameters is relatively low, with significant discrepancies in accuracy across different elevation angles. Specifically, the accuracy of polarisation parameter data at 1.5° elevation is higher than that at 0.5°. The dwell time, pulse repetition frequency, and number of pulses directly impact the standard deviation of C-band dual-linear polarisation radar’s polarisation parameters. By optimising the pulse repetition frequency and number of pulses, the accuracy of polarisation standard deviation is enhanced without altering the observational mode within the same dwell time. An analysis of the standard deviation of polarisation parameters during two typical weather processes reveals that, before parameter optimisation, the accuracy of polarisation standard deviation is generally higher during hail processes than in heavy precipitation events. However, post-improvement, the enhancement in the accuracy of polarisation standard deviation for heavy precipitation events is usually superior to that for hail events. The modified observational mode thus improves the accuracy of polarisation parameter data for C-band dual-polarisation radar to a certain extent.
Abstract: As the main equipment for atmospheric detection, weather radar plays an important role in meteorological operations, weather early warning, and atmospheric science research. With the upgrading of the S-band dual-polarisation radar, it is very important to improve the precision of radar quantitative precipitation estimation. In this paper, three southwest monsoon and three typhoon precipitation processes over the Shantou region from 2018 to 2022 are selected as the research objects. Hourly rainfall data from the S-band dual-linear polarisation weather radar and 43 automatic weather gauges in Shantou are used to analyse the effectiveness of radar precipitation estimation. To improve the reliability and accuracy of data, the data quality control of radar and rain gauge data is carried out by various means. The data of 92,880 polarisation samples are obtained by matching the station coordinates of the rain gauge with the multi-polarisation parameters of the radar from the time dimension and the space dimension. By means of five error indexes: mean error (ME), relative error (RE), root mean square error (RMSE), standard deviation (STD) and correlation coefficient (ρ), the total samples, sub-rainfall intensity samples and sub-precipitation type samples of PPS, Ryzhkov, CSU-HIDRO and HCA-LIQ radar precipitation estimation algorithms in six precipitation processes are evaluated respectively. By comparing and analysing the error indexes and the stability of the algorithm between the estimated value of radar precipitation and the measured value of rain gauge, the following conclusions are drawn: (1) in the total sample, CSU-HIDRO algorithm and HCA-LIQ algorithm outperform PPS algorithm and Ryzhkov algorithm, with CSU-HIDRO algorithm being the best; (2) CSU-HIDRO algorithm and HCA-LIQ algorithm perform better than PPS algorithm and Ryzhkov algorithm in the samples of southwest monsoon precipitation and typhoon precipitation, with CSU-HIDRO algorithm performing best in the samples of southwest monsoon precipitation, and HCA-LIQ algorithm performing best in typhoon precipitation samples; (3) Ryzhkov algorithm performs best in light rain samples, CSU-HIDRO algorithm outperforms other algorithms in medium rain samples and heavy rain samples, with HCA-LIQ algorithm being next. In a word, both CSU-HIDRO algorithm and HCA-LIQ algorithm adopt the data of raindrop spectrum in South China to improve the fitting of formula parameters, and the effect of quantitative precipitation estimation is better than the other two algorithms in the United States. In practical application, the rainfall intensity and precipitation type can be considered synthetically, and the corresponding precipitation estimation algorithm can be adopted to improve the accuracy of radar quantitative precipitation estimation. At the same time, it also provides reference for the secondary development of radar products and short-term forecast and early warning.
Abstract: The International Joint Committee for Guides in Metrology (JCGM) puts forward “Evaluation of measurement data-propagation of distributions using the Monte Carlo method” (MCM) in ISO/IEC Guide 98-3:2008 supplement 1. MCM is a method based on the law of propagation of distribution (LPD). Therefore, compared with the GUM (Guide to the Expression Uncertainty in Measurement) evaluation method, MCM has higher accuracy and reliability when applied to the evaluation of measurement uncertainty. There are two schemes of MCM: one is single batch MCM and the other is adaptive MCM. Since adaptive MCM can effectively save computer resources and is more efficient in evaluation, it is widely used in the evaluation of measurement uncertainty in various fields. To ensure the accuracy of the detection data of the digital barometer, it needs to be calibrated periodically, and to characterise the reliability of the calibration results, and needs to be analysed and evaluated in terms of the measurement uncertainty (referred to as “uncertainty”) of the calibration results. To effectively improve the accuracy of the calibration results of the digital barometer and provide technical support for the credibility and reliability of meteorological observation data, taking the calibration results of PTB220 digital barometer as the research object, the adaptive MCM method is used to evaluate the uncertainty of the measurement results of the digital barometer. The adaptive MCM method is used to compare and verify the GUM method in accordance with the validation scheme given in the ISO/IEC Guide 98-3: 2008 supplement 1. The results show that the deviation of GUM in the uncertainty of the digital barometer exceeds the specified range, i.e., the absolute deviation of the left and right endpoints of the 95% inclusion interval between GUM and MCM uncertainty exceeds the numerical tolerance of 0.005 hPa, which is determined by the effective number of digits of the standard uncertainty, so the GUM method fails to pass the validation. Through the above results, it is indicated that the GUM method may be unsuitable for the verification of the uncertainty of this instrument. The above results indicate that the GUM method may not be suitable for the evaluation of the uncertainty of this instrument.
Abstract: Building an open real-time monitoring system for integrated meteorological services and comprehensively improving the operational quality and efficiency of meteorological services is an important task for the development of meteorological informatization. The scope of meteorological integrated business monitoring includes multiple business fields such as forecast, prediction, observation, information, and public services. The monitoring function covers multiple aspects such as meteorological data, meteorological business applications, and infrastructure resources. The monitoring data have a wide range, diverse content, and intensive transmission, with a massive expansion in quantity and capacity. Establishing a standardised access mechanism for monitoring data has become a key factor in ensuring that complex and diverse monitoring data can be efficiently, completely, and accurately collected into the real-time monitoring system, and achieving integrated monitoring for meteorological comprehensive service. Upon the CIMISS-MCP monitoring data framework, this article designs a scalable monitoring data content model based on standardised data classification. Firstly, based on the content and application characteristics of the monitoring data, the meteorological business integrated monitoring data is divided into three categories: event information, status information, and indicator data, and their meanings are defined separately. Secondly, for each category of monitoring data, by analysing and summarising the business connotation of massive monitoring information, the necessary attribute items are extracted, forming a universal model composed of data identification domain and data attribute domain. Thirdly, considering the significant specificity of data attribute domain content due to the differences in monitoring objects and monitoring requirements, attribute items are defined for typical data domain content of event information required for core monitoring functions such as meteorological data full process monitoring, meteorological business application task monitoring, and centralised alarm monitoring. This model adopts various scalability elements in the design of general and typical attributes, which has good universality and scalability characteristics. It is widely applied in the construction of the “Meteorological Integrated Real-time Monitoring System” of the China Meteorological Administration, achieving the generation, collection, storage, calculation, service, and publication display of massive monitoring data, and well supporting various functions of the meteorological integrated monitoring business. At the same time, it is widely applied in the localisation and functional expansion of business monitoring systems in various provincial meteorological data centres and shows positive benefits. The design and application of this model effectively ensure the efficient and stable operation of meteorological information business, laying a solid data foundation for service-oriented and intelligent operation and maintenance of meteorological big data centres in the era of intelligent meteorology.
Abstract: In order to meet the requirements of meteorological departments for efficient management and sharing of meteorological government administration data, solve the problems of difficult communication, sharing and collaboration of data, and promote the integration of meteorological government administration data into the national integrated government big data system, China Meteorological Administration designs and builds the meteorological department’s first centralised and unified government administration data centre, which is “one level of concentration and four levels of application,” relying on the national-level meteorological proprietary cloud platform, and directly supporting meteorological government administration and business applications. This article analyses the current status, existing problems and construction needs of meteorological department government administration data, introduces the core architecture design, main business functions, the key information flow, the government administration data classification and hierarchical data system based on the characteristics of meteorological government administration data, key implementation technologies, and application effectiveness of the system. The implementation of the system adopts a series of advanced information technologies, including support for multi-source heterogeneous data aggregation, policy-based data cleansing and integration governance, globally unified data service and interface management, full-text search based on the open-source ElasticSearch engine, message-driven management application collaboration, data synchronisation in the master and standby centres, etc. The system started construction in 2019, and after more than two years of research and development, it completes the development of system software functions, establishes a data collection, data storage and data update mechanism, provides unified data sharing services, and continues to carry out the aggregation and governance of government administration data resources. It builds data applications such as office management, forecasting, human resources management, technology management, forecaster team portraits, full-text retrieval, business collaboration, comprehensive management decision-making analysis, etc. As the system is put into business applications, government administration data of the meteorological department are standardised, managed and effectively utilised, establishing a data resource directory of 12 first-level categories, 72 second-level categories, and 357 types of government administration data, completing the collection and storage of 237 types of data, releasing a total of 30 data interfaces in 20 categories, implementing 72 types of government administration data sharing applications within the meteorological department. Master data such as personnel, institutions, administrative divisions, seasonal holidays, and public roles provide real-time data services for more than 200 applications of the meteorological department. As a digital base for the digital transformation and upgrading of government administration of the meteorological department, the system provides “one-stop” government data management and sharing application services for the four-level meteorological departments at the national, provincial, city and county levels after its completion, and plays an essential role in effectively supporting China Meteorological Administration’s office management, scientific decision-making and performing public functions.
Abstract: Using data from 373 meteorological stations in the Western China region and ERA5 reanalysis data from 1981 to 2022, this study employs methods such as Mann-Kendall, correlation, and composites to analyse the characteristics of autumn rainfall changes in Western China after entering a new climatic phase, and explores the atmospheric circulation and sea temperature anomaly characteristics. The results indicate that over the past 32 years, the overall trend of Western China autumn rain significantly increases, with an increase in precipitation of approximately 30.4 mm, at a rate of about 9.5 mm per decade. Spatially, most areas show an increase post-shift, with significant increases primarily located in most of the Sichuan Basin, western Hunan, southern Shanxi, and southern Ningxia regions. Circulation field analysis reveals that since 2011, the blocking high near the western coast of Europe to the Ural Mountains and the Sea of Okhotsk area (hereafter referred to as the Okhotsk high) strengthens. The Western Pacific Subtropical High (hereafter referred to as the West Pacific Sub-high) also intensifies and extends westward. The southwesterly winds turning through the South China Sea from the subtropical region of the Western Pacific, the easterlies from the Northwest Pacific region, and the southwesterly winds from the Indian Ocean through the Bay of Bengal all strengthen. These factors collectively contribute to an increasing trend in water vapour transported to Southwestern, providing favourable conditions for the transition from lesser to greater autumn rainfall. Sea surface field analysis indicates that during the earlier spring and summer, as well as the concurrent autumn seasons, sea temperatures in the Indian Ocean transition from cold to warm, while sea temperatures in the central Pacific shift from warm to cold. These shifts prompt adjustments in convective activity and meridional circulation across the mid-low latitudes. These also lead to a shift in the West Pacific Sub-high from weak to strong, markedly extending westward, enhancing the intensity of water vapour transported from its western side and the Bay of Bengal to Southwestern. Anomalous warming in the Northwest Pacific Ocean, by stimulating meridional teleconnection wave trains, strengthens the Okhotsk high. Elevated sea temperatures in the western Atlantic increase convective activity from the Arabian Sea to the Bay of Bengal, which, through downstream propagation of teleconnection wave trains, facilitates the transport of water vapour from the Bay of Bengal to Southwestern. The combined sea temperature changes in these regions thus intensify the water vapour transport from the western side of the West Pacific Sub-high and the Bay of Bengal to Southwestern, consequently leading to an increase in autumn rainfall from lesser to greater amounts.
Abstract: In order to improve the understanding of the characteristics and mechanisms of typhoon remote rainstorms within the subtropical high, a remote rainstorm process triggered by Typhoon Mangosteen in 2018 is analysed using multi-source observation and ERA5 reanalysis data. The results show that: (1) The rainstorm occurred within a strong convective and unstable environment characterised by high temperature, high humidity, and high energy within the 500 hPa subtropical high. The rainstorm area was located at the north end of the typhoon trough at the lower level, within the southerly wind speed convergence area, and to the right side of the upper jet stream inlet area. (2) The lower-level warm and humid advection provided sufficient water vapour and energy, promoting the development and maintenance of convective unstable stratification. Strong upper-level divergence coupled with lower-level convergence induced a strong upward motion, which provided favourable dynamic conditions for the rainstorm. (3) The mesoscale convective system exhibited three evolution stages: the organisation and establishment of banded convection, the development and movement of supercells in the south, the weakening of convection in the north, and the development of new convection in the south, resulting in extreme short-term heavy precipitation (exceeding 100 mm/h) during two stages. (4) The low-level North China high combined with the typhoon trough and the offshore high successively enhanced the low-level convergence and maintained the shear line (surface convergence line), which was conducive to the development and maintenance of convection. The typhoon trough acted as the trigger and organiser of the initial convective zone, and the outflow of the thunderstorm cold pool played a pivotal role in the development and movement of supercells. (5) The divergence and suction force of the upper jet stream in the mid-level convergence, the development of positive vorticity and low trough, and the enhancement of vertical wind shear in the rainstorm area were conducive to the development of the southern convective zone. During typhoon activity at the low latitudes, there was a typhoon trough at the lower level of the 500 hPa subtropical high, and the convergence area at the northern end of the typhoon trough was the focus of long-range rainstorm forecasts.
Abstract: Using the data from conventional meteorological observation stations, sounding data, and S-band Doppler and dual-polarization radar data from Qingdao, the weather background and radar echo characteristics of a convective hail event at Qingdao Airport on the afternoon of July 8, 2023 are analyzed. The results show that the hail event occurred under the combined action of a strong westerly wind belt at 500 hPa and a cold vortex trough, with strong local characteristics. The entire atmosphere had strong instability, with obvious characteristics of dryness in the upper layer and wetness in the lower layer. The vertical wind shear intensity in the lower layer was moderate, while the vertical wind shear intensity in the deep layer was strong. The wind vector difference between 0 and 6 km reached 21 m/s, and the temperature difference between high and low altitudes was large. The height at wet bulb temperature 0 ℃ was 4 km. The radar echoes had high-rise strong echoes, bounded weak echo areas, echo hangings, and three-body scattering structures. At the same time, there was a clear mesocyclone structure at an altitude of 4-8 km in the middle layer, with a diameter of about 4 km and a thickness of about 3.2 km in the convergence layer. There was a velocity divergence in the upper layer. These were all typical radar characteristics of hailstorms. The large values of C-VIL and VIL density could well correspond to hail particles, and the C-VIL mutation could also be used as a reference index for forecasting hail and strong winds. The C-VIL jump occurred 30 minutes before the hail at Qingdao Airport, and the sudden drop occurred 7 minutes before the strong wind at Qingdao Airport. During this hail process, the dual-polarisation radar parameters ZDR and ρhv could effectively distinguish hail and strong precipitation, while the KDP large value area corresponded to heavy rain or melted hail. It was necessary to combine other parameters to further determine the particle morphology. This hail process showed obvious ZDR and KDP column structures, with the ZDR column higher than the KDP column. The ZDR column corresponded to strong upward motion, which corresponded to the location of the mesocyclone on the velocity diagram, while the KDP column corresponded to a more obvious downdraft. The analysis results can provide some reference for short-term and imminent forecasts of hail at Qingdao Airport, and also have some instructive significance for the practical application of dual-polarisation radar products.
Abstract: In order to thoroughly comprehend the types, characteristics, and patterns of weather systems leading to maize lodging disasters in Jilin Province, an analytical approach employing historical disaster data, maize development period data, and ERA5 reanalysis data is adopted. Utilising typical case analysis methods, we seek to scrutinise and summarise the weather systems associated with maize lodging disasters in Jilin Province. The outcomes indicate that four predominant types of weather systems contribute significantly to maize lodging in the region: typhoon, northeast cold vortex, low-level shear line, and upper trough. During the jointing tasselling period, maize lodging is predominantly influenced by the northeast cold vortex, while during the tasselling milking period, the primary influencing factors are the low-level shear line and upper trough. The milking ripening period is chiefly affected by the northward movement of typhoons. Typhoons emerge as the most severe weather system causing maize lodging in Jilin Province, exhibiting extensive impacts, with the trajectory of their movement playing a pivotal role in determining the extent of crop lodging disasters. Typically, maize lodging disasters triggered by typhoons occur predominantly on the western or northern peripheries of their paths and on the northern flank of the associated surface low-pressure system. The second most influential weather system is the northeast cold vortex. Maize lodging disasters instigated by the cold vortex primarily manifest in the southeast quadrant of its influence, where conditions such as water vapour, dynamics, heat, and convective instability are most pronounced. The low-level shear line and upper trough exhibit a limited influence range. The occurrence site of maize lodging induced by the low-level shear line is contingent upon the positioning of the low-level shear line or convergence line. Maize lodging disasters attributed to upper-level troughs typically manifest in the frontal region of the upper-level trough, proximal to the ground cold front.
Abstract: This article introduces a novel method that draws on big data thinking, treating the weather system as a comprehensive entity in which the interactions of the high, middle, and low-level atmospheres, as well as the influences of static, thermal, and dynamic conditions, are considered. It utilises a novel approach to comprehensive similarity assessment through situation field analysis, using derived data from numerical weather models and reanalysed grid data of various meteorological elements as its fundamental characteristics. The approach begins by employing the machine learning Principal Component Analysis (PCA) method to condense the features of the original grid field data, making it adaptable to the resource processing capabilities of conventional business platforms. Subsequently, the derived dimensional feature data of different meteorological elements at various spatial levels are normalised to ensure a balanced effect when participating in similarity calculations. The constructed sample-derived feature factor matrix, suitable for comprehensive weather similarity analysis, undergoes calculation of the similarity distance for each feature dimension among the samples. Based on the variance contribution rates of the initial field information contained in the data from different “principal component” dimensions, different weights are assigned to the similarity distance results of each dimension, yielding a comprehensive similarity distance. Finally, using the K-Nearest Neighbours (KNN) algorithm, the method provides the most comprehensive similar sequence in the historical weather situation database for the target sample, thus upgrading and improving traditional methods of similar weather forecasting. This method provides a multi-element and multi-level “stereoscopic” comprehensive similarity, aiding forecasters in better understanding the structure and evolution of weather systems and, consequently, more accurately assessing the possible occurrence of related weather phenomena. Comparative analysis and testing applications indicate that the results of comprehensive similarity analysis are superior to traditional “sliced” similarity analysis, which only targets single meteorological elements or altitude levels, particularly in terms of matching critical weather system positions and strength features. It resolves issues such as inconsistent results of similar weather situation analysis for different “slices” and poor forecast stability. This method provides more direct and efficient assistance in weather analysis and forecasting and holds promising prospects for refined meteorological forecasting services. In several instances of extreme precipitation meteorological forecasting services in the Guangxi region since 2023, this method achieves significant application effectiveness.
Abstract: With global warming, the occurrence of extreme weather and climate events, coupled with the rapid development of the economy and society, the problem of water resource shortages in Erhai Lake is becoming increasingly serious. To increase precipitation in the Erhai Lake basin, the meteorological department often carries out artificial rainfall enhancement operations and establishes artificial rainfall enhancement test areas in the Erhai Lake basin to conduct artificial rainfall enhancement effect evaluation research, so as to improve the ability of artificial rainfall enhancement operations. According to the weather situation of the rainfall enhancement operation day, this paper selects 819 daily precipitation data points of the test area and the contrast area in the Erhai Lake basin from 2005 to 2014 (November to February in winter and June to September in summer), and 79 rainfall enhancement operation data points from 2015 to 2020. The artificial rainfall enhancement operations in the Erhai Lake basin are subject to statistical and physical tests, and the following conclusions are drawn. (1) The statistical effect test of the artificial rainfall enhancement operations in the Erhai Lake basin is carried out by using the regional regression numerical simulation evaluation programme. The rainfall enhancement efficiency of stratus and mixed cloud is 16.57% and 20.09% respectively, and passes the significance test at the significance level α≤0.05. (2) The physical examination of the rainfall enhancement effect of the stratus cloud precipitation on 31 January 2020 and the mixed cloud precipitation on 13 August 2020 is conducted by using the new generation of weather radar. The results show that the maximum echo intensity and the average vertical integral liquid water content (VIL) of the stratus cloud target cloud body in the experimental area decreases slightly after the operation, and the echo top height changes little. The maximum echo intensity, the average VIL and the echo top height of the mixed cloud target cloud body increase rapidly. The ground rainfall intensity is significantly enhanced after the two types of rainfall enhancement operations. (3) The physical examination of the above two processes is conducted by using the laser raindrop spectrometer. The results show that the rainfall intensity and the number concentration of the stratus cloud and the mixed cloud rainfall enhancement operations in the experimental area begin to increase about 10-15 minutes after the operation. The diameter of the maximum number concentration changes from 0.437 mm to 0.562 mm, the spectral width increases, and the peak type changes from single peak to bimodal structure. The characteristics of the raindrop spectrum in the contrast area do not change obviously during the same period, indicating that the rainfall enhancement operation intensifies the condensation of water vapour in the cloud and produces more raindrops, and at the same time, it touches and produces larger scale raindrops.
Abstract: Gale is one of the main meteorological disasters affecting the safety of heavy haul railway transportation. Therefore, carrying out a risk assessment of gale disasters has certain guiding significance for preventing disasters and reducing damages in railway departments. This paper takes Shuozhou-Huanghua railway as a typical section of the heavy haul railway. First, the risk assessment system of gale disasters in typical sections along the heavy haul railways is constructed based on the four criteria levels such as the disaster-inducing factors of gale, environmental sensitivity of gale disasters, vulnerability of gale disaster-bearing bodies, and the capability of disaster prevention and mitigation, as well as the 17 indicator layers such as the number of blue level alarms for gale, the number of yellow level alarms for gale, the number of orange level alarms for gale, the number of red level alarms for gale, frequency of strong crosswind, altitude, terrain, the number of tracks, the number of trains, station level, allowable speed of lines, bridges, tunnels, presence of wind barriers, strong wind warning capabilities, the number of emergency personnel, and emergency rescue equipment and materials. Then, the analytic hierarchy process and entropy weight method are used to determine the weight coefficients of the above four criteria levels and the above 17 indicator layers of emergency, and finally, the comprehensive risk zoning of wind disasters in typical sections of heavy-duty railways is obtained. The results show that the railway sections from Shenchi South station to Ningwu West station, from Huanghua South station to Huanghua Port station, from Beigang station to Dagang station, and Shengang station are the highest risk sections of gale disasters along the Shuozhou-Huanghua railway. The railway sections from Longgong station to Diliudeng station, and from Huanghua East station to Yangsanmu station are the second highest risk sections of gale disasters along Shuozhou-Huanghua railway. The railway sections from Houwen station to Sanji station, from Xingtang station to Quyang station, from Dingzhou West station to Dingzhou East station, from Anguo station to Boye station, from Lixian station to Litianmu station, and from Douzhuangzi station to Guozhuangzi station are medium high risk sections of gale disasters along Shuozhou-Huanghua railway. To sum up, it can be seen that the comprehensive risk level of gale disasters along Shuozhou-Huanghua railway sections in the western mountainous, hilly areas and eastern coastal areas is the highest.
Abstract: In order to better consolidate the results of the creation of “China’s Natural Oxygen Bar” in Yichun, promote the green and healthy development of Yichun’s forest recreation and tourism industry, and help transform the value of ecological resources in the Lesser Khingan Mountains region, this paper formulates a data quality control method to analyse and evaluate the characteristics of the daily changes of anion concentration in the hinterland of Yichun based on the monitoring data on the anion concentration in the air at 13 stations in Yichun. The annual, seasonal, monthly and diurnal variation of anion concentration in Yichun, the hinterland of the Lesser Khingan Mountains, are analysed and evaluated. The results show that the annual average negative oxygen ion concentration in Yichun is generally higher than that in most areas in China, showing a spatial distribution of high in the mountains and low in the plains, and increasing with the latitude and longitude and the forest cover, showing a growing trend from the south to the north. Seasonal change characteristics are not significant; the overall trend is the highest in summer, followed by winter and spring, and the lowest in autumn, while the counties and districts show obvious local characteristics. Negative oxygen ion concentration has a daily change pattern, showing U-shaped bimodal characteristics, with nighttime significantly higher than daytime. Monthly changes are not significant, with the peak occurring in July-August and the lowest values in January and April. Negative oxygen ion concentrations in 90 percent of the county-level administrative areas reach the level of Class I, and the negative oxygen ion concentrations at the three types of monitoring stations basically reach the level of freshness and above.
Abstract: The single-factor analysis and multi-factor comprehensive evaluation delineation method are used to evaluate the geo-disaster prone area, and the rainfall distribution characteristics and the frequency of geo-disasters are combined to determine the geo-disaster meteorological early warning area. Taking the towns and streets as early warning units, and the effective rainfall and activated rain intensity of geological disasters as the disaster-causing factors, the box plot analysis method is used to determine the rainfall threshold index value of all levels of landslide geological hazard. The method of typical heavy rainfall process combined with disaster reverse check and historical typical case back is used to test the rainfall threshold of geological disaster warning. From the statistical analysis of geological disaster census cases in Zhuzhou from 2011 to 2021, it is found that the geological disasters in Zhuzhou are mainly landslide disasters, followed by collapse, and small-scale geological disasters account for 98% of the total. The occurrence period of geological disasters in Zhuzhou is consistent with the rainy season, and landslide geological disasters are mainly distributed in Youxian County and Chaling County, and collapse disasters are mainly distributed in Lusong District and Hetang District. More than 80% of towns and streets in the city have experienced geological disasters. Geological disasters in Zhuzhou are closely related to rainfall, and heavy rain or more is the main factor for the formation of geological disasters in Zhuzhou. When the rain intensity is more than 20 mm/h, the risk of geological disasters in Zhuzhou is relatively high, and the risk of geological disasters induced by heavy rain intensity more than 50 mm/h is great. The critical value of effective rainfall for geological disasters in Liling is 61.9 mm, and the critical rainfall in other counties (cities, districts) is less than 50 mm, and the effective rainfall is more than 80 mm when more than 80% of geological disasters occur. The geological disaster meteorological early warning area of Zhuzhou can be divided into key early warning area A, sub-key early warning area B and general early warning area C. Each early warning area contains N early warning units of towns or streets. The effective rainfall and activated rain intensity are taken as the disaster factors. Using the box plot analysis method, it is clear that the disaster probability of 25% is the yellow warning rainfall threshold, the disaster probability of 50% is the orange warning rainfall threshold, and the disaster probability of 75% is the red warning rainfall threshold. The blue, yellow, orange and red warning rainfall thresholds of landslide-type geological disasters in different meteorological warning zones of Zhuzhou are determined. It is proved that the threshold index of early warning rainfall with effective rainfall as the disaster factor has a good application effect in practical early warning, while the threshold index of early warning rainfall with activated rainfall intensity as the disaster factor is lower and has a larger false alarm rate, so it should not be used alone in practical early warning.
Abstract: Using the meteorological observation data of Yuepuhu in Xinjiang from 1981 to 2019, combined with the growth and development of Flos Lonicerae, the relationship between the climatic conditions and the growth of Flos Lonicerae in Yuepuhu are analyzed. According to the ecological characteristics of Flos Lonicerae, the meteorological conditions of Flos Lonicerae cultivation in Yuepuhu are systematically analyzed, and the results show that the average temperature of each phenological stage of Flos Lonicerae in Yuepuhu show an obvious increasing trend; the number of sunshine hours has an obvious increasing trend; and the water source is sufficient. These are conducive to the normal growth and development of Flos Lonicerae. As the temperature rises and the number of sunshine hours increases, the planting time has been advanced from the previous mid March to early March; the planting area has expanded year by year, from tens of hectares in 2016 to 345 hm2 in 2019; and the planting mode has been adjusted from the plain cropping to inter cropping method. In the inter planting mode, the varieties are unified with Beihua No.1. The number of consecutive high temperature days of ≥38 ℃ during the growth and development of Flos Lonicerae, especially in ≥40 ℃ high temperature weather, the short term heavy precipitation weather, windy and sandy weather and other meteorological conditions have certain influence on the quality and yield of Flos Lonicerae. Exploration of the favorable climatic conditions for the development of the Flos Lonicerae planting industry in Yuepuhu provides a scientific basis for the construction of the Yuepuhu Flos Lonicerae industrial base, as well as the meteorological guarantee for the increase of income of flower farmers.
Abstract: Clouds are an important part of the earth system, which can affect the radiation balance of the earth atmosphere system by affecting atmospheric radiation transmission. At present, the information obtained from three dimensional cloud observation has certain limitations, so it is necessary to obtain more accurate three dimensional cloud information by using multi source observation data merging analysis. Based on the successive correction method, 〖JP2〗the Three Dimensional Cloud Merge Analysis Operation System (3DCloudA V1.0) integrates multi source data such as numerical forecast products, geostationary meteorological satellite observation, meteorological radar observation to produce the real time 0.05°/h three dimensional cloud merging analysis product covering China and its surrounding areas (0°-60°N, 70°-140°E), which is distributed to the national and provincial meteorological departments through the China Telecommunication System. The modular system framework is considered in the operation system design and construction process, and the fault tolerant functions such as EC Flow scheduling process real time monitoring and automatic restarting are developed, which effectively improves the stability and reliability of the operation system. Evaluations show that through merging multi source observation data, the three dimensional cloud merge analysis product can describe cloud the top, inside and bottom information more accurately.〖JP〗
Abstract: In order to improve the weather forecast quality over the low latitude plateau regions, the wind data retrieved with VAD (Velocity Azimuth Display) method are assimilated to the WRF (Weather Research and Forecasting) model by WRF 3DVar (3 Dimensional Variational Data Assimilation System). With different assimilation schemes, a torrential rain event occurred in Yunnan Province from 00:00UTC 30 June 2009 to 00:00UTC 1 July 2009 is numerically simulated and comparatively analyzed. The results indicate that the initial wind fields of the WRF model are markedly improved by assimilating the retrieved wind data. The WRF 3DVar can availably introduce the information of the retrieved wind to the initial conditions of the regional numerical model. The assimilation of the retrieved wind data helps enhance the wind convergence and vapor transportation over the rainy area. Furthermore, the assimilation help improve quantitative precipitation forecasts. The quantitative test of the 18 hour rainfall forecast shows that forecasts are more accurate, less pretermissions, and more rational pertinence for over 250 mm precipitation in the assimilation experimentations. The higher the assimilation frequency and the longer the assimilation time is, the more obvious the influence of data assimilation on the initial fields and forecast fields of the regional model is. But long assimilation time may increase the speed of synoptic systems and the overestimate rainfall, and so the suitable selection of frequency and time is crucial in numerical experimentations.
Abstract: Through investigating the lightning disasters of ancient buildings, the distribution of ancient buildings being stricken by lightning are analyzed. It is found that animal finials and prominent parts of the like, old trees, towers and kiosks, service facilities and other parts of ancient buildings are vulnerable to lightning strikes. It is found that once an ancient building is stricken by lightning, it is probable to be stricken again by lightning. The reasons for that ancient buildings are stricken and caught fire by lightning are analyzed, and the proportions of casualties caused by ancient building lightning disasters are calculated. It is concluded that the reasons for ancient buildings stricken by lightning includes the appropriate location and structure of ancient buildings, tree triggering, internal environment changes, and water infiltration because of disrepair and other factors vulnerable to lightning.
Abstract: Data quality assessment is an important part in model operation application. In this paper, the soil moisture observation data and China Meteorological Administration Land Data Assimilation System (CLDAS) data are used to establish the online CLDAS data quality assessment system through the MySQL database and the Web technology like html, JavaScript, HighChart， etc. The assessment analysis between the simulated soil moisture and the observed soil moisture at any of stations and provinces, times and different soil layers is implemented in the form of correlation coefficient, root mean square error, relative deviation, and mean deviation. Diagrams such as time series and scatter are visually displayed to compare the observation and simulated data in the system. The statistical indexes can be calculated immediately using JavaScript language in the Web platform. The assessment results and the comparison diagrams can be showed through the internet Web page, and the real time monitoring of the model product data quality can be achieved.
Abstract: Due to the influence of the curve Earth, the fixed detection mode of the CINRAD/SA weather radar uses the minimum elevation angle of 0.5 °, so the blind area is relatively big, and the detection capability for low level precipitation echoes is limited. On the basis of experiments, the calculation formulas of the minimum height applicable when CINRAD/SA detects with positive and negative elevation angles are devised. Then the minimum detecting heights of CINRAD/SA at different distances with different elevation angles (0.5°, 0°, -0.3°,-0.5°) are calculated. Through analyzing characteristics of radar products detected under different elevation angles, some suggestions on CINRAD/SA about using negative elevation angles are presented.
Abstract: With the intensive observation data and NCEP/NCAR reanalyzed data, an unusual heavy fog process occurred over the east central China from 25 to 27 December in 2006 is analyzed in aspects of the large scale synoptic condition and dynamic and thermodynamic mechanisms. It was shown that the fog occurred while the near ground wind velocity varied from 0.3 to 2.9 m/s and the dense fog occurred while the wind velocity varied from 0.3 to 2.4 m/s and the visibility was within 15 meters when velocity was from 0.8 to 1.1 m/s. Although vapor condition was bad and rainfall didn’t occur within a few days before the heavy fog, the continuous vapor transportation of the southwestern air current before a trough offered plentiful vapor for the fog. The results also show that the stable stratification gradually established before the fog.At first, the instable stratification built at higher levels after sunrise, subsequently passed downward to lower levels, and then the inversion layer destroyed and the fog dispersed and cleared off. The results indicate that the visibility changed rapidly and violently before the first stage of the severe heavy fog but it did not before the second stage.
Abstract: In order to reveal the development mechanisms of heavy snowfall in Hebei Province,two heave snow processes on 14 to 16 March 2003 and 20 to 21 February 2004 are selected. A contrast analysis of their meteorological characteristics is made from aspect of synoptic situation and physical mechanism by means of numerical diagnosis with the NCEP reanalysis data and conventional observation data. The results show that the combination of south and north troughs with identical phase around 110°E at 500 hPa, the allocation of the surface pressure field with high in north and low in south, and the appearance of the ground inverted trough in the Hetao area of NW China, as well as the thermodynamic conditions with warm temperature tongue and warm advection in the lower troposphere, are the favorable large scale background for the formation of heavy snowfall. There are three important paths of water vapor in the two snow events: from southwest in front of the 500 hPa trough, from east at low level, and from low level jet. From the cross sections of vorticity, divergence, vertical velocity and vertical helicity, it is found that the vertical distribution of convergence at low level but divergence at upper level and ascending motion in the whole troposphere benefit the forming and maintaining of heavy snowfall, and the distribution of positive vorticity (vertical helicity) in the whole troposphere is most favorable. It is also suggested the temperature descending to below 0 ℃ at both 850 hPa and 925 hPa, meanwhile below 1 ℃ in the surface, is favorable to snowing. The results can be used as reference in the forecasting heavy snowfall.
Abstract: A whole province range thunderstorm occurred in Zhejiang Province on 26 June 2009, and the occurrence frequency of cloud to ground lightning in this thunderstorm is the highest since the establishment of the lightning position system in 2006. By means of the observation data from the lightning position system, the intensive rainfall observation system, and Doppler radar, the characteristics of the cloud to ground lightning process are analyzed. The results indicate that lightning strokes were mainly negative; in the lightning echo image, negative strokes were mostly distributed in the area of 25 dBz to 55 dBz, and positive strokes were usually in the area of 25 dBz to 35 dBz; lightning strokes occurred mostly on the side of echo development or advancement, distributed around the area with maximum gradients, and there seldom appeared lightning strokes around a strong echo center; the frequency of cloud to ground lightning was correlated closely with the accumulated precipitation of the whole province during the thunderstorm. The peak value of precipitation lagged more than 0.5 hour behind the peak value of the frequency of cloud to ground lightning, and the accumulated precipitation of the whole province occurred 1 to 2 hours behind the peak value of the frequency of cloud to ground lightning. Therefore, the cloud to ground lightning data can be used as a basis in short range severe precipitation forecasting.
Abstract: Soil moisture is a key variable in water and energy exchanges in land atmosphere interface. The passive microwave remote sensing is the most potent technology to retrieve soil moisture. A brief introduction is made to microwave theory, and a general review of soil moisture retrieval algorithms is given. Three typical cases are illustrated based on the different microwave sensors by comparing various algorithms, which correspond to the three parameter AMSR based retrieval developed by Njoku and Li, the two parameter SMMR based retrieval developed by Owe et al. and the two parameter SSM/I based retrieval developed by Wen et al. The insufficiency and potentials in the researches on soil moisture are discussed.
Abstract: In order to expand the space of meteorological business, integrate multiple fields of monitoring, and promote the development of the meteorological industry towards efficiency, convenience, and intensification, the Guizhou Province Meteorological Comprehensive Monitoring System APP is developed using mainstream mobile apps as carriers, based on the Springboot+Vue+Mybatis Plus development framework, and using multi-platform compatible development (uni-app), real-time capture of change data (FlinkCDC), and an efficient packaging framework (Mybatis-Plus) among other technical means. The article provides a detailed introduction to the framework structure and functional design adopted by the APP as an independent monitoring system, as well as the big data development technology and its business advantages involved. At the technical level, the system utilises uni-app development technology to make the APP client more compatible and can simultaneously adapt to various application platforms such as iOS, Android, Web, and various mini-programs; using Mybatis-Plus as the database driver framework to improve code reusability and reduce database performance overhead; by using FlinkCDC as a data processing and incremental synchronisation tool, resource waste caused by full data synchronisation can be avoided, simultaneously serving as a one-way synchronisation tool to enhance the security of meteorological data. At the framework level, in order to avoid security risks caused by network mixing, the system introduces a Demilitarised Zone (DMZ) to isolate the internal and external network data environments. The internal network department is responsible for collecting and storing meteorological data from various formats such as databases, static files, API interfaces, logs, etc. Then, it will be synchronised unidirectionally with the external network environment through FlinkCDC. The external network interacts with the mobile APP by receiving data pushed by FlinkCDC. The software is aimed at meteorological users at all levels of province, city, county, and station. Through preliminary research and analysis, four functional modules have been developed for different users, including regional automatic stations, weather radar stations, network connectivity, and interface service status. This provides convenience for meteorological data monitoring and equipment maintenance, and improves the timeliness of response. The system has been put into use throughout the province since 2022. The application results show that the APP adapts to multiple mobile system platforms such as Android and iOS, and has a friendly interface, simple operation, and stable operation. Since its application, the timeliness of meteorological data has improved, enriching the monitoring business methods of Guizhou Province, meeting the user needs at all levels, and playing a positive role in the development of the meteorological industry.
Abstract: Under the common influence of factors including complex terrain, subtropical high pressure, and monsoon weather, the wind field in the alpine canyon areas of is complex and changeable, and it is easy to form the “narrow pipe effect”, which leads to disastrous gales that have a great impact on the construction and operation of large-scale projects. In this paper, based on Fluent, a fluid dynamics computing software, a standard turbulence model and PISO algorithm are used to study the variation of wind velocity field near the dam during dam construction and the influence of dam construction on the wind velocity field, taking the level 7 north wind in Baihetan Hydropower Station as a typical calculation condition. The research results show that the blocking effect of the dam body makes the wind velocity field at the top of the dam generate flow separation and wind field uplift, and a low wind velocity zone forms below the dam elevation. When the dam elevation is 650 m and 750 m, the wind speed within the cable platform is about 15 m/s to 16 m/s, and the channel length of the significant influence area by the wind speed vertical distribution downstream of the dam is 4.4 Ht and 4.5 Ht (Ht being the dam height). The significant influence heights of the wind velocity field at the top of the dam are 2.0 Ht and 3.0 Ht respectively. When the dam is filled to the normal water level of 825 m, the channel length of the significant influence area by the wind field downstream of the dam is 8.0 times the dam height (2.3 km), and the maximum influence channel length is 30.4 times the dam height (8.8 km). The influence height of the dam top reaches about 1500 m height, which is 3.5 times the dam height.
Abstract: Aiming at the problems of data quality degradation caused by multi-channel scanning-type loads on geostationary orbit remote sensing satellites in the process of imaging, transmission and storage, i.e., the influence of texture distortion and edge blurring in the meteorological remote sensing feature recognition images on the analysis of meteorological remote sensing images, this study proposes an improved BM3D noise reduction algorithm. The algorithm combines Morlet wavelet decomposition theory (with good symmetry and its decay characteristics follow the exponential law, it is able to match the mutation signals in the meteorological remote sensing images, thus realising signal denoising) and BM3D denoising principle (a non-local filtering algorithm that includes two parts: block matching and 3D collaborative filtering. Block matching involves grouping image blocks similar to a given reference block and composing them into a 3D array). Firstly, the image decomposes using wavelet transform to get four components. Secondly, the meteorological remote sensing image decomposes into three levels with a total of ten components. Finally, each component denoises using a separate BM3D filter, and the output image of the 10 components reconstructs. The output reconstructed image views as an estimate of the desired image, capable of suppressing meteorological remote sensing image noise and preserving edge detail. Compared with the traditional BM3D denoising algorithm, the improved BM3D algorithm is able to reduce the computation by about one-fifth. The eight meteorological remote sensing images process by equalising the grayscale and adding additive Gaussian white noise with mean 0 and standard deviation σ and random impulse noise. The median filter (suitable for removing isolated noise such as pepper noise), mean filter (suitable for removing noise from images), NL-Bayes (suitable for smoothing images and preserving image details), BM3D algorithm and the improved BM3D algorithm also compare to process the images respectively, and based on the results of peak signal-to-noise ratio (according to the definition of peak signal-to-noise ratio, it considers as the main metric to evaluate the quality of an image and utilises to measure the degree of realism of an image, with higher values indicating better denoising effects) of the meteorological remote sensing images, it finds that the average PSNR gain of the algorithms proposed in this study is in the range of 0.39 dB to 4.45 dB. The above experimental results of meteorological remote sensing images indicate that the improved BM3D algorithm works better, especially in the mixed noise denoising of Gaussian white noise and impulse noise.
Abstract: Based on the hourly and daily precipitation data of 61 national meteorological stations from 1961 to 2020 and 998 regional automatic meteorological observation stations from the beginning of the establishment to 2020 in Liaoning Province, we analyse the main causing factors of rainstorm and flood disaster, calculate the environmental indicators of rainstorm and flood disaster, and complete the hazard assessment of rainstorm and flood disaster in Liaoning Province. The results show that the high-risk area of rainstorms and floods is mainly located in Dandong. The high population risk areas of rainstorm and flood disaster are mainly located in Shenyang and Dalian urban areas. The high economic risk areas of rainstorm and flood disaster are mainly located in Dalian and Panjin urban areas. The high-risk areas of rice and maize are mainly located in Jinzhou, Panjin, and Dandong. The disaster risk of the rainstorm process on 28-29 July 2022 is pre-assessed using the intelligent grid forecast data of Liaoning Province. It is found that the high hazardous areas are mainly distributed in Chaoyang, Huludao, and the central part of Liaoning. The population and economic high-risk areas caused by the rainstorm disaster are mainly located in the western and central areas. The high-risk areas of rice and maize caused by rainstorm disaster are mainly located in Shenyang, Tieling, and the north of Chaoyang. It is estimated that the population affected in the high-risk area is about 4.49 million, the economic loss is about 14.32 million yuan. The affected rice area is about 10,280 hectares, the maize area is about 17,798 hectares. Through the post-disaster effect test, it is found that the pre-assessment model is effective and can be used in the actual rainstorm and flood disaster risk assessment business.
Abstract: In order to apply the Hail Detection Algorithm (HDA) related products more extensively and correctly, for the 22 hail cases monitored in Pu’er area from 2015 to 2020, the new Radar Operational Software Engineering (ROSE2.0) is used to replay radar-based data and analyse the relevant products. The recognition effect of the HDA algorithm in the Pu’er area is evaluated with the probability of detection (POD), false alarm rate (FAR), and critical success index (CSI), and a localised parameter configuration scheme is provided after that, which is useful to improve the local hail warning ability. The results show that although the POD of the HDA algorithm in Pu’er area is close to 100%, there are also many ordinary storm cells that are identified as hail cells mistakenly. The number of false alarms is very huge, and the low CSI cannot meet the requirement of the weather forecasting operation. The warning effect of using Probability of Severe Hail (POSH) is better than that of Probability of Hail (POH) for any size of hail, and the larger the size of hail, the lower the probability of false alarm of POSH. Further analysis of the adaptation parameters of the POSH algorithm by a simulation test method shows that the height of the 0 ℃ and -20 ℃ layers has a significant impact on the recognition ability of POSH, the original default value is significantly lower in Pu’er area, correctly inputting the height of 0 ℃ and -20 ℃ layers on the day of hail can effectively reduce the FAR and improve the CSI of POSH; at the same time, it can control the situation that the maximum hail diameter predicted by the algorithm is generally too large, and the maximum expected hail size (MEHS) is closer to the observation value; the deviation percentage of small and medium-sized hail diameter decreases by 76.07%, with a significantly higher improvement effect than large hail, but the diameter prediction error of MEHS for large hail is smaller. In addition, increasing the reflectivity factor and POSH threshold can effectively control FAR, but it also leads to a rapid increase in the number of missed alarms. When the threshold is too large, the POD significantly decreases. In order to achieve a higher POD and CSI, selecting Z=50 dBz or POSH=70% as the threshold can improve the recognition effect of the HDA algorithm. Setting the optimal threshold of multiple parameters at the same time can effectively improve the recognition ability of the HDA algorithm in Pu’er.
Abstract: By introducing the relief shading method, which is often used in making the topographic maps, into the visualisation of numerical weather forecast data, this article presents the achievement in three-dimensional drawing of meteorological variables, such as air pressure and geopotential height. Based on the principle and implementation of hill shading, which uses the relationship between the illumination angle, the direction, the slope, and the orientation of the terrain to calculate the brightness value of luminous flux, the relief shading method makes use of the brightness value to display the three-dimensional sense of meteorological model data. At the same height, the steeper the terrain, the darker (brighter) the shaded (sunny) side; under the same slope, the higher the terrain, the darker (brighter) the shaded (sunny) side, which is consistent with the real-life visual effect. The colouring method of the shaded relief map is to use the brightness value (V) in the HSV colour space which is calculated on each grid point, combined with hue (H) and saturation (S) to obtain a complete HSV colour scheme. Through the conversion from the HSV colour space to the RGB colour space, the latter colour space is used for drawing a coloured shaded relief map for meteorological model data. In the shaded relief map, the high-pressure centre in the weather system is often shown as a raised peak, and the low pressure is shown as a depressed valley; a large pressure gradient can be seen as a steep slope, while a small pressure gradient can be seen as a gentle slope. Compared with the traditional isoline and colour filling analysis, it is found that the shaded relief map can help to identify high-low weather systems by concave-convex shapes and reflects the gradient changes of weather systems through the steepness of slope, thus intuitively representing the three-dimensional distribution of atmospheric circulation. In addition, the shaded relief map has the ability to visualise model data in pixel level details, identify early eddy current disturbances in small gradients, and reveal equivalent terrain effects, which helps the meteorologists better interpret the model data and provides the references for the improvements of data process functions in numerical models. Furthermore, the relief shading method is suitable for using the synthetic animations to showcase the fluid characteristics of atmospheric motion, which is conducive to popularising the concept of various weather systems, such as the high, the low, the trough and ridge, and their evolution to the public.
Abstract: Flash heavy rain and the resulting low visibility make it difficult for pilots to visually assess the runway clearly, severely impacting the take-off and landing of aircraft, thereby posing a threat to aviation operational safety. Moreover, the flight delays and diversions caused by this also result in significant losses for airlines and negatively affect socioeconomic benefits. Therefore, conducting comprehensive studies on flash heavy rain is crucial for ensuring aviation safety and enhancing flight punctuality. A thorough analysis of sufficiently detailed observational data is beneficial for clarifying the dynamic mechanisms of convective organisation and enhancement. On July 15, 2022, Xiamen Airport experienced a rare flash heavy rain event triggered by a weak background gust front. During this period, the precipitation intensity peaked at 2.5 mm per minute, and runway visibility rapidly decreased to 600 m, which is relatively uncommon at Xiamen Airport. To analyse this flash heavy rain event, this study utilises minute rainfall data from both ends of the runway, conventional observational data, densified automatic weather station data, ERA5 reanalysis, and S-band dual-polarisation and X-band dual-polarisation phased array radar data of Xiamen. The results of the study indicate that this event occurred under weak weather-scale forcing, where the gust front triggered uplift by intersecting and merging with the surface convergence line during propagation. In an environment characterised by negative large values of pseudo-equivalent potential temperature (θse500-850 hPa) and a warm and humid lower atmosphere, new convection was stimulated, resulting in the rare flash heavy rain at Xiamen Airport. During heavy rain, strong water vapour convergence appeared in the boundary layer at 1000 hPa. Minute rainfall on the runway showed an inverse correlation with visibility, but this correlation weakened when the minute rainfall exceeded 1.6 mm, and the visibility minimum lagged behind the rainfall peak by 7 minutes. Observational analysis reveals that the cyclonic shear of radial velocity was consistent with the trend of minute rainfall change. The peak minute rainfall at both ends of the runway corresponded to the peak cyclonic shear at a certain height layer, indicating a good correspondence between the two. When there was cyclonic shear in the radial velocity at heights of 2-5 km, rainfall significantly intensified. When the shear intensity at two height layers exceeded 2×10-3s-1, minute rainfall could reach approximately 2 mm (equivalent to an hourly rainfall of 120 mm), which emerged as a characteristic feature of this flash heavy rain event.
Abstract: In order to achieve the goal of independent and controllable key core technologies for Meteo by 2025, the Meteo Big Data Cloud Platform (referred to as Tianqing) establishes a simulation environment based on Hygon X86 CPU and Kylin OS. However, in the operation of simulation platforms, it finds that the docker scheduling performance of data processing and assembly line subsystems based on Kubernetes is poor, which cannot meet the timeliness requirements of user integration algorithms. In response to this issue, this article adopts a comparative analysis method, selecting servers based on three types of CPU and three types of operating systems from the simulation environment and business environment for Tianqing as the research objects. A series of combined comparative test cases are designed. It finds that the kernel is the key factor affecting docker scheduling performance. Further analysis is conducted on the impact of operating system kernel settings on real-time and throughput, as well as the suitable business scenarios. Finally, a method for adjusting the Kylin OS kernel is provided. By adjusting the kernel settings, the docker scheduling performance significantly improves, meeting the timeliness requirements of the data processing system and laying the foundation for achieving self-supporting of the key core technology of Tianqing.
Abstract: In order to further strengthen the application of satellite-to-ground lightning, the spatial-temporal distribution characteristics and spatial-temporal matching features are comparatively analysed in Zhejiang Province based on lightning data from FengYun (FY)-4A Lightning Mapping Imager (LMI) and Advanced Direction and Time-of-arrival Detecting (ADTD)-2C three-dimensional lightning location system from June to August in 2020. In addition, by combining reflectivity of Doppler radar mosaics and cloud top brightness temperature from FY-4A Advanced Geosynchronous Radiation Imager (AGRI), the spatial and temporal evolution patterns of lightning data from two observation systems are analysed during a thunderstorm process in Zhejiang Province on 15 July 2020. The results show that from June to August in 2020, the number of LMIG detected by LMI was 8483, while the number of lightning detected by the ADTD-2C three-dimensional lightning location system was 376932. The ratio of the two sets of data was approximately 1∶44.43. The monthly and spatial distributions of lightning detected by these two systems were generally consistent, while diurnal variation of which were different. Specifically, diurnal variation of LMIG presented two peaks, and diurnal variation of three-dimensional lightning showed only one peak. Besides, when the time matching window was larger than 1.8 seconds, and the latitude and longitude matching window was larger than 0.5°, the matching rate gradually tended to be stable. Furthermore, the height of three-dimensional lightning matched with LMIG was mainly concentrated below 16 km, and the lightning intensity of which was mainly concentrated below 50 kA. During the thunderstorm weather in Zhejiang Province in the afternoon on 15 July 2020, the ratio of LMIG to three-dimensional lightning was approximately 1∶25.44. The time of the first LMIG and its peak time were both later than the time of the first three-dimensional lightning and its peak time. What’s more, the lightning data observed by the two systems corresponded well with the development process of the thunderstorm. When the thunderstorm was at the developing stage, the number of lightning data detected by the two systems was both gradually increasing, and when the thunderstorm was at the mature stage, the number of lightning data detected by the two systems was both maintaining a relatively high value, and when the thunderstorms were at the dissipation stage, the number of lightning data detected by the two systems was both decreasing rapidly. When it came to the spatial distribution of the lightning, both of the two datasets corresponded well with the spatial distribution of low cloud top brightness temperature.
Abstract: Based on the ensemble forecast data derived from European Centre for Medium-range Weather Forecasts (ECMWF) ensemble forecast system and observation data derived from automatic observation stations in Zhejiang region, the Bayesian Model Averaging (BMA) method is used to calibrate the probabilistic forecasts of precipitation during the super long Meiyu season in 2020. In this paper, we verify the raw ensemble probabilistic forecast and BMA calibrated probabilistic forecast from 1 June to 15 July, 2020, by Mean Absolute Error (MAE), Continuous Ranked Probability Score (CRPS), Brier Score (BS), Talagrand, Probability Integral Transform (PIT) histogram, and attribute diagram. The verification results before and after calibration are compared. The analysis results are listed as follows. (1) In 8 different training periods (10 days to 80 days), 50 days correspond to smaller MAE and CRPS score values. So we set 50 days as the optimal BMA training period for ECMWF ensemble forecast calibration in the Meiyu season in Zhejiang Province. After BMA calibration in the optimal training period, the spread of ensemble forecast increases and the forecast error decreases. Analysing from the quantitative verification indicators, BMA can effectively calibrate the overall precipitation in the test stage, but it cannot calibrate the daily precipitation in the test stage. (2) For forecasting of different threshold precipitation, BMA has different calibration performance. For the thresholds of 0.1 mm, 10.0 mm, and 25.0 mm, BMA has a significant calibration effect. After BMA calibration, the CRPS of precipitation probabilistic forecast for these three thresholds (0.1 mm, 10.0 mm, and 25.0 mm) decreases by 25.92%, 19.29%, and 4.76%, respectively. However, the calibration effect of BMA weakens with the increase of precipitation threshold. For the events with total precipitation exceeding 50.0 mm, the BMA calibration effect is not as significant as that of the smaller threshold. In addition, BMA can effectively improve the forecast skills of 0.1 mm, 10.0 mm and 25.0 mm threshold precipitation and make the forecast probability more closely match the observation. (3) In the case of heavy rain, the high probability range of the raw ensemble probabilistic forecast is always wider than that of the observation. BMA has the ability to slightly calibrate the raw ensemble forecast probability. After BMA calibration, the high probability range of precipitation forecast at each threshold effectively reduces the deviation. The empty message information and the probability of empty message events also reduce after calibration. So BMA can make the calibrated high probability range of precipitation forecast more consistent with the observed range. But unfortunately, BMA cannot adjust the spatial distribution of precipitation forecast probability.
Abstract: CINRAD/SA, China Next Generation Weather Radar,was produced by the Beijing METSATAR Radar Co., Ltd, based on the NEXRAD WSR-88D technology.Its software system was modified to provide the new RHI/PPI scan mode because NEXRAD WSR-88D provides only the volume scan mode. The design and realization of the RHI/PPI scan mode on the CINRAD/SA are described.
Abstract: An analysis is made of the annual, seasonal, and monthly variation characteristics of sunshine duration in recent 50 years and its relationship with total cloudiness, trying to detect the variation of sunshine duration in Chengdu by the abrupt climate change theory. The results indicate that in recent 50 years, the sunshine duration decreased with a tendency of 69.41 hours per ten years; the interannual variation amplitude was obviously greater; and the difference between the sunshine durations in 1963 and in 1989 is up to 662.8 hours. There is obvious seasonal difference in sunshine duration, with bigger decreasing amplitude in summer and winter than those in spring and autumn and a tendency of -29.77 and -20.17, -9.91 and -9.56 hours per ten years, respectively. The decreasing tendency is obviously greater in August and less in April. The annual variation of sunshine duration is consistent with sunshine percentage. The sudden change occurred around 1978, with the annual sunshine duration decreased rapidly.
Abstract: An observational experiment was conducted on the impact of air temperature and humidity variation on soil resistivity and earthing resistance with different structures by selecting three typical soil conditions to set three vari structure lightning protecting earthing bodies in Ningxia for one year. By means of comparative and regression analysis, the impacts of different soil conditions on soil resistivity at different temperatures and humidity in different seasons, and the variation characteristics and regularities of the lightning protecting earthing bodies with different structures are studied, and accordingly the optimal requirements for the layout and structure of lightning protecting earthing bodies are presented.
Abstract: In order to develop and utilize reasonably climate resources and offer a scientific basis for the sub-area management of livestock production over grasslands, an analysis was made of the Inner Mongolia grassland climate characteristics and effects of climate on the growth of pasture grass, the distribution of domestic animal breeds and the soil environment. It is found that some isolines of climatic moisture are almost superposed with the boundaries of soil, which indicates that the formation of soil zones is closely related to climatic conditions, and climate and soil environment are main influence factors for pasture types and the ecosystem. Based on the climatic moisture, in combination with the distribution characteristics of soil over Inner Mongolia, a regionalization was carried out of grassland ecological types, which is not only rational, but also stable. It is pointed out that the climatic warming and the resulting changes in recent years improved, to some extent, the productivity of the grasslands, but not changed the ecotype in Inner Mongolia.
Abstract: An introduction of the main reanalysis data of NCEP, ECMWF, JMA and the preliminary comparison among them are given from the following aspects: (1) assimilation systems, including the assimilation module and method; (2) the data used in the reanalysis; and (3) the methods of quality control and bias correction. The main assimilation methods of all reanalysis datasets include the 3D variational method, 4D variational method, and optimum interpolation. The dominating differences of these reanalysis datasets are data types and the resolution of modules. In addition, the advantages and deficiencies of these reanalysis datasets are given by empirical analysis. It is helpful for selecting the correct reanalysis dataset. The advances in reanalysis in China ars introduced simply and some problems on the improvement of the reanalysis in China are discussed.
