Relationship between Calligraphy and Meteorology

Since ancient times,calligraphy and meteorology have had an inseparable relationship.Wang Xizhi s Prologue to the Collection of Poems Composed at the Orchid Pavilion records the beautiful scenery of mild wind and bright sun,as well as the relaxed and joyful mood of people in such weather.Su Shi s Cold Food Calligraphy Copybook records the scenery of solar terms and the author s psychological changes during these solar terms through calligraphy.The Quick Snow and Clear Time Calligraphy Copybook also reflects the grandeur of snowy days and the customs of literati recording weather and sharing it with friends.In Sun Guoting s Shupu,it is clearly stated that the third element of the"five harmony and five obedience"refers to the clear sky,humid air,and pleasant climate,and excellent climatic conditions are conducive to writing.

Response of warm season secondary pollutants to emissions and meteorology in the North China Plain region during 2018-2022

自2013年起中国空气质量虽改善,但华北平原(NCP)重污染仍存在且二次污染加剧,而人们对其成因和变化了解有限.本研究利用2018-2022年数据,借助CMAQ模型探讨此污染响应.结果显示,在2018-2022年间,PM_(2.5)浓度显著下降31%-37%,O_(3)和NO_(2)的年下降速率分别为1%和0.5%SIA和SOA也显著减少,每年分别减少9%和6%PM_(2.5)主要因排放减少而下降,而O_(3)则受气象影响而波动.硫酸盐和铵下降的主因是减排,而硝酸盐对气象变化敏感排放和气象变化对SOA的总体减少同样重要,但人为SOA对排放控制敏感生物SOA易受气象变化影响.研究强调了控制人为排放对缓解NCP地区夏季二次污染的重要性.

Design of Web System for Meso-scale Meteorological Observational Station Based on SVG

The web of meso-scale meteorological observational station based on WebGIS realized by SVG technology was briefly introduced.Through grasping and applying SVG technology,the high-density automatic observational station in Anhui Province was developed.The web of meso-scale meteorological observational stations constructed by SVG technique can display the network graphics of weather data and intuitionistic vector graphics interface.

Deep convolutional neural network for meteorology target detection in airborne weather radar images

Considering the problem that the scattering echo images of airborne Doppler weather radar are often reduced by ground clutters,the accuracy and confidence of meteorology target detection are reduced.In this paper,a deep convolutional neural network(DCNN)is proposed for meteorology target detection and ground clutter suppression with a large collection of airborne weather radar images as network input.For each weather radar image,the corresponding digital elevation model(DEM)image is extracted on basis of the radar antenna scan-ning parameters and plane position,and is further fed to the net-work as a supplement for ground clutter suppression.The fea-tures of actual meteorology targets are learned in each bottle-neck module of the proposed network and convolved into deeper iterations in the forward propagation process.Then the network parameters are updated by the back propagation itera-tion of the training error.Experimental results on the real mea-sured images show that our proposed DCNN outperforms the counterparts in terms of six evaluation factors.Meanwhile,the network outputs are in good agreement with the expected mete-orology detection results(labels).It is demonstrated that the pro-posed network would have a promising meteorology observa-tion application with minimal effort on network variables or parameter changes.

The 17th Workshop on Antarctic Meteorology and Climate and 7th Year of Polar Prediction in the Southern Hemisphere Meeting

1.Overview August 2022 marked the 17th Workshop on Antarctic Meteorology and Climate(WAMC)which was held in a hybrid format at the Pyle Center at the University of Wisconsin-Madison(UW-Madison)in Madison,WI,USA.The workshop is the first partial in-person gathering since the 14th WAMC(Lazzara et al.,2018)as the 15th WAMC was canceled due to the COVID-19 pandemic,and the 16th WAMC(Bromwich et al.,2022)was purely online.Global members of the Antarctic meteorological community gathered at this meeting to present and discuss weather-related topics encompassing scientific research and support operations within Antarctic meteorology and climate.These conversations aimed to share and discuss results,future developments,and build collaborative plans.

Research on Smart Meteorology Serving Agriculture under the Rural Revitalization Strategy—Taking Mingshan Tea as an Example

It is imperative to prioritize the development of agriculture and rural areas and improve the efficiency of smart meteorological services for agricultural products under the strategy of rural revitalization. In this article, we take Mingshan tea, one of the characteristic industries in Sichuan Province, as an example to explore the related issues of smart meteorology serving agriculture. The status, value, and demand of tea smart meteorological services have been analyzed in this article. In addition, in response to the increasing demand for meteorological services in agricultural production, we have proposed to solve problem of tea meteorological service by strengthening talent, technology, product refinement, and dissemination. We have also proposed specific measures for tea intelligent meteorology to serve agriculture, in order to provide reference for future service practices. We need to continuously improve the methods and content of meteorological services, and improve the level of meteorological services. At the same time, utilizing smart meteorological service methods provides strong support for rural revitalization. This not only increases the income of tea farmers, but also maximizes the technical support role of meteorology in disaster prevention and reduction.

Energy-Meteorology Synergy Development Thematic Forum of 2023 Global Energy Interconnection Conference Held in Beijing

On September 27th,the Energy-Meteorology Synergy Development Thematic Forum of the2023 Global Energy Interconnection Conference was held in Beijing.This forum,co-hosted by Global Energy Interconnection Development and Cooperation Organisation,World Meteorological Organisation and National Climate Centre.

The effects of cold region meteorology and specific environment on the number of hospital admissions for chronic kidney disease:An investigate with a distributed lag nonlinear model

Objective:To explore the effects of daily mean temperature(°C),average daily air pressure(hPa),humidity(%),wind speed(m/s),particulate matter(PM)2.5(μg/m3)and PM10(μg/m3)on the admission rate of chronic kidney disease(CKD)patients admitted to the Second Affiliated Hospital of Harbin Medical University in Harbin and to identify the indexes and lag days that impose the most critical influence.Methods:The R language Distributed Lag Nonlinear Model(DLNM),Excel,and SPSS were used to analyze the disease and meteorological data of Harbin from 01 January 2010 to 31 December 2019 according to the inclusion and exclusion criteria.Results:Meteorological factors and air pollution influence the number of hospitalizations of CKD to vary degrees in cold regions,and differ in persistence or delay.Non-optimal temperature increases the risk of admission of CKD,high temperature increases the risk of obstructive kidney disease,and low temperature increases the risk of other major types of chronic kidney disease.The greater the temperature difference is,the higher its contribution is to the risk.The non-optimal wind speed and non-optimal atmospheric pressure are associated with increased hospital admissions.PM2.5 concentrations above 40μg/m3 have a negative impact on the results.Conclusion:Cold region meteorology and specific environment do have an impact on the number of hospital admissions for chronic kidney disease,and we can apply DLMN to describe the analysis.

Surface ozone in global cities:A synthesis of basic features,exposure risk,and leading meteorological driving factors

Long-term exposure to high surface ozone(O_(3))concentrations,a complex oxidative atmospheric pollutant,can adversely impact human health.Based on O_(3)monitoring data from 261 cities worldwide in 2020,generalized additive model(GAM)and spatial data analysis(SDA)methods were applied in this study to quantitatively evaluate the spatiotemporal distribution of O_(3)concentration,exposure risk,and dominant meteorological factors.Results indicated that over 40%of the cities worldwide were exposed to harmful O_(3)concentration ranges(40-60μg/m^(3)),with most cities distributed in China and India.Moreover,significant seasonal variations in global O_(3)concentrations were observed,presenting as summer(45.6μg/m^(3))>spring(47.3μg/m^(3))>autumn(38.0μg/m^(3))>winter(33.6μg/m^(3)).Exposure analysis revealed that approximately 12.2%of the population in 261 cities were exposed to an environment with high O_(3)concentrations(80-160μg/m^(3)),with about 36.32 million people in major countries.Thus,the persistent increase in high O_(3)levels worldwide is a critical factor contributing to threats to human health.Furthermore,GAM results indicated temperature,relative humidity,and wind speed as primary determinants of O_(3)variability.The synergy of meteorological factors is critical for understanding O_(3)changes.Our findings are important for enforcing robust air quality policies and mitigating public risk.

Short-term effects of low-level PM2.5,PM10,O3,and tropical meteorological conditions on emergency department visits for respiratory diseases in Haikou,China

Objective:To assess the correlation between atmospheric pollutants,meteorological factors,and emergency department visits for respiratory diseases in Haikou City.Methods:Daily data on atmospheric pollutants,meteorological factors,and emergency department visits for respiratory diseases in Haikou City from 2018 to 2021 were collected.The Spearman rank correlation test was used to analyze the correlation,and a distributed lag non-linear model was employed to analyze the health effects and lag impacts of environmental factors.Subgroup analyses were conducted based on sex and age.Results:According to the criteria of International Classification of Diseases(ICD-10:J00-J99),a total of 221913 cases were included,accounting for 21.3%of the total emergency department visits in Haikou City.For every 1℃increase in temperature,the risk of emergency department visits increased by 1.029%(95%CI 1.016%-1.042%).Relative humidity greater than 80%reduced the risk of visits,while higher atmospheric pressure(>1010 hpa)also decreased the likelihood of daily emergency department visits.Higher concentrations of PM2.5(30-50μg/m^(3)),PM10(>60μg/m^(3)),and O_(3)(75-125μg/m^(3))were associated with increased visits.Higher temperatures(>25℃)have a greater impact on females and children aged 0-14 years,while males are more sensitive to low atmospheric pressure.Individuals aged 65 and above exhibited increased sensitivity to O_(3)concentration,and the effects of PM2.5,PM10,and O_(3)are more pronounced in individuals over 14 years old.Conclusions:Short-term exposure to high temperatures,particulate matter pollutants(PM_(2.5)and PM_(10)),and ozone(O_(3))is associated with increased emergency department visits for respiratory diseases.

Progress and Achievements of Fengyun Meteorological Satellite Program since 2022

Fengyun meteorological satellites have undergone a series of significant developments over the past 50 years.Two generations,four types,and 21 Fengyun satellites have been developed and launched,with 9 currently operational in orbit.The data obtained from Fengyun satellites is employed in a multitude of applications,including weather forecasting,meteorological disaster prevention and reduction,climate change,global environmental monitoring,and space weather.These data products and services are made available to the global community,resulting in tangible social and economic benefits.In 2023,two Fengyun meteorological satellites were successfully launched.This report presents an overview of the two recently launched Fengyun satellites and currently in orbit Fengyun satellites,including an evaluation of their remote sensing instruments since 2022.Additionally,it addresses the subject of Fengyun satellite data archiving,data services,application services,international cooperation,and supporting activities.Furthermore,the development prospects have been outlined.

Artificial Intelligence Based Meteorological Parameter Forecasting for Optimizing Response of Nuclear Emergency Decision Support System

This paper presents a novel artificial intelligence (AI) based approach to predict crucial meteorological parameters such as temperature,pressure,and wind speed,typically calculated from computationally intensive weather research and forecasting (WRF) model.Accurate meteorological data is indispensable for simulating the release of radioactive effluents,especially in dispersion modeling for nuclear emergency decision support systems.Simulation of meteorological conditions during nuclear emergencies using the conventional WRF model is very complex and time-consuming.Therefore,a new artificial neural network (ANN) based technique was proposed as a viable alternative for meteorological prediction.A multi-input multi-output neural network was trained using historical site-specific meteorological data to forecast the meteorological parameters.Comprehensive evaluation of this technique was conducted to test its performance in forecasting various parameters including atmospheric pressure,temperature,and wind speed components in both East-West and North-South directions.The performance of developed network was evaluated on an unknown dataset,and acquired results are within the acceptable range for all meteorological parameters.Results show that ANNs possess the capability to forecast meteorological parameters,such as temperature and pressure,at multiple spatial locations within a grid with high accuracy,utilizing input data from a single station.However,accuracy is slightly compromised when predicting wind speed components.Root mean square error (RMSE) was utilized to report the accuracy of predicted results,with values of 1.453℃for temperature,77 Pa for predicted pressure,1.058 m/s for the wind speed of U-component and 0.959 m/s for the wind speed of V-component.In conclusion,this approach offers a precise,efficient,and wellinformed method for administrative decision-making during nuclear emergencies.

Assessment of Meteorological Threats to the Coordinated Search and Rescue of Unmanned/Manned Aircraft

The architecture and working principle of coordinated search and rescue system of unmanned/manned aircraft,which is composed of manned/unmanned aircraft and manned aircraft,were first introduced,and they can cooperate with each other to complete a search and rescue task.Secondly,a threat assessment method based on meteorological data was proposed,and potential meteorological threats,such as storms and rainfall,can be predicted by collecting and analyzing meteorological data.Finally,an experiment was carried out to evaluate the performance of the proposed method in different scenarios.The experimental results show that the coordinated search and rescue system of unmanned/manned aircraft can be used to effectively assess meteorological threats and provide accurate search and rescue guidance.

Forecast Method of Ozone Concentration in Yulin City Based on Meteorological Conditions

Based on the monitoring data of ozone(O 3)concentration,conventional meteorological data and reanalysis products in Yulin City from 2018 to 2019,the weather situation of O 3 pollution was classified through case analysis and mathematical statistics.At 500 hPa,the weather situation was divided into continental high pressure type,subtropical high type and mixed type.At 850 hPa,it was divided into southwest air flow type,east air flow type and south air flow type.The correlation between meteorological element and O 3 concentration were analyzed,and factors with good correlation such as temperature,air pressure and wind speed were selected to establish regression equations.The fitting effect was good,and O 3 concentration could be objectively predicted.

Exploring the Relationship between Spatiotemporal Variations in Air Quality and Meteorological Parameters before and during the COVID-19 Pandemic in Xi’an

The COVID-19 pandemic has significantly changed the air pollution of the world. The present study investigated the temporal and spatial variability in air quality in Xi’an, China, and its relationship with meteorological parameters during and before the COVID-19 pandemic. The outcomes of this study indicated that air pollutants, PM2.5, NO2, PM10, CO, and SO2 are likely to decrease during winter (25%, 50%, 30%, 40%, and 35%) to spring (30%, 55%, 38%, 50%, and 40%) and summer (40%, 58%, 60%, 55%, and 47%), respectively. However, the concentration of O3-8h increased by 40%, 55%, and 65% during winter, spring, and summer, respectively. The values of the air quality index decreased during the COVID-19 period. Furthermore, significant positive trends were reported in PM2.5, NO2, PM10, O3, and SO2, and no notable trends in CO during the COVID-19 pandemic. Both during and before the COVID-19 period, PM10, NO2, PM2.5, CO, and SO2 showed a negative correlation with the temperature and a moderately positive significant correlation between O3-8h and temperature. The findings of this study would help understand the air pollution circumstances in Xi’an before and during the COVID-19 period and offer helpful information regarding the implications of different air pollution control strategies.

Analysis of Characteristics and Meteorological Influencing Factors of Air Pollution in Luojiang District,Deyang City

Based on the monitoring data of ambient air quality and meteorological observation data,the characteristics and meteorological influencing factors of air pollution in Luojiang District of Deyang City from 2018 to 2022 were analyzed.The results show that from 2018 to 2022,the main air pollutants affecting the air quality of Luojiang District of Deyang City were PM_(2.5) and PM_(10),and the primary pollutant on heavy pollution days was basically PM_(2.5).PM_(2.5) and PM_(10) pollution showed obvious seasonal differences,and PM_(2.5) concentration exceeded the limit mainly in spring and winter,among which it was the most serious in early spring,especially in January and February,followed by December.PM_(10) exceeding the standard had a high seasonal correlation with PM_(2.5) exceeding the standard,mainly in spring and winter,among which it was the most serious in winter,especially in December,followed by January.PM_(2.5) and PM_(10) pollution showed an overall weakening trend.PM_(2.5) and PM_(10) concentration were closely related to meteorological factors such as temperature,relative humidity,wind speed,precipitation and air pressure,and were mainly affected by rainfall.

Implications of Dynamic Interactions between Meteorological Patterns and Surface Water Quality on Environmental Health—A Case Study of the Nairobi River

Urban areas face significant challenges in maintaining water quality amidst increasing urbanization and changing climatic patterns. This study investigates the complex interplay between meteorological variables and water quality parameters in Nairobi City, focusing on the impacts of rainfall and temperature on surface water quality. Data from multiple sources, including the Water Resources Authority, Nairobi Water and Sewerage Company, and the World Bank’s Climate Change Knowledge Portal, were analyzed to assess the relationships between meteorological variables (rainfall and temperature) and water quality parameters (such as electroconductivity, biochemical oxygen demand, chloride, and pH). The analysis reveals varying impacts of rainfall and temperature on different water quality parameters. While parameters like iron and pH show strong relationships with both rainfall and temperature, others such as ammonia and nitrate exhibit moderate relationships. Additionally, the study highlights the influence of runoff, urbanization, and industrial activities on water quality, emphasizing the need for holistic management approaches. Recommendations encompass the establishment of annual publications on Nairobi River water quality, online accessibility of water quality data, development of hydrological models, spatial analysis, and fostering cross-disciplinary research collaborations. Implementing these recommendations can enhance water quality management practices, mitigate risks, and safeguard environmental integrity in Nairobi City.

Analysis of a Typical Case of Meteorological Service in Tangpu Reservoir

The continuous rainy precipitation process from February to March in 2019 was selected to analyze the effect of meteorological service in Tangpu Reservoir basin,so as to sum up service experience and then lay a better foundation for subsequent services.In response to the rainy weather from December 2018 to early 2019,three rounds of flood discharge were carried out in Tangpu Reservoir.During February-March in 2019,the hit rate of short-term area rainfall forecast for Tangpu Reservoir was 80.0%.Compared with the median of forecast interval,the average absolute error was 7.6 mm,and the relative error was 32.7%.The large deviation in the forecast from March 27 to 28 was deeply analyzed,and it is found that the main reasons were excessive reliance on and trust in a single model,insufficient correction of the actual situation,and insufficient judgment of the nature of precipitation.For the future reservoir meteorological service,three aspects of thinking were put forward,such as further strengthening the sharing of hydrological and meteorological information,improving the forecasting ability,and deepening the research of runoff forecast models.

Development and Application of the Edition System of Agricultural Meteorology Short Message in Liaoning Province

In order to meet the needs of Agricultural Meteorology business and research,an edition system of agricultural meteorology short message was established based on the Microsoft Access 2000 database and visualization developing software Visual Basic 6.0 in Liaoning Province.The basic principles of agro-meteorological text editing and system optimization ideas were pointed out.The meteorological conditions of the main crops growth needed in material library were introduced.

An Overview of Tropical Cyclone and Tropical Meteorology Research Progress

There has been much progress in the study of tropical cyclones and tropical meteorology in China in the past few years. A new atmospheric field experiment of tropical cyclone landfall with the acronym of CLATEX (China Landfalling Typhoon Experiment) was implemented in July-August 2002. The boundary layer characteristics of the target typhoon Vongfong and the mesoscale structural features of other land-falling typhoons were studied. In addition, typhoon track operational forecasting errors in the last decade have been reduced because the operational monitoring equipment and forecast techniques were improved. Some results from the research program on tropical cvclone landfall, structure and intensity change, inten-sification near coastal waters, interaction between tropical cyclone and mid-latitude circulation, and the interaction among different scales of motion are described in this paper. Four major meteorological scien-tific experiments in China with international cooperation were implemented in 1998: the South China Sea monsoon field experiment (SCSMEX), the Tibetan Plateau field experiment (TIPEX), the Huaihe River basin energy and water cycle experiment (HUBEX), and the South China heavy rain scientific experiment (HUAMEX). Although these field experiments have different scientific objectives, they commonly relate to monsoon activities and they interact with each other. The valuable intensive observation data that were obtained have already been shared internationally. Some new findings have been published recently. Other research work in China, such as the tropical air-sea interaction, tropical atmospheric circulation, and weather systems, are reviewed in this paper as well. Some research results have shown that the rainfall anomalies for different regions in China were closely related to the stages of El Nino events.