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Assessment of Meteorological Threats to the Coordinated Search and Rescue of Unmanned/Manned Aircraft
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作者 Fei YAN Chuan LI +2 位作者 Xiaoyi FU Kefeng WU Yuying LI 《Meteorological and Environmental Research》 2024年第1期27-29,37,共4页
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... 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. 展开更多
关键词 Unmanned/manned aircraft Coordinated search and rescue Assessment of meteorological threats meteorological data
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Surface ozone in global cities:A synthesis of basic features,exposure risk,and leading meteorological driving factors
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作者 Jinmian Ni Jiming Jin +6 位作者 Yanwen Wang Bin Li Qian Wu Yanfei Chen Shenwen Du Yilin Li Chao He 《Geography and Sustainability》 CSCD 2024年第1期64-76,共13页
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 add... 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. 展开更多
关键词 Ozone pollution Spatiotemporal variation Exposure risk GAM meteorological factors
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Artificial Intelligence Based Meteorological Parameter Forecasting for Optimizing Response of Nuclear Emergency Decision Support System
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作者 BILAL Ahmed Khan HASEEB ur Rehman +5 位作者 QAISAR Nadeem MUHAMMAD Ahmad Naveed Qureshi JAWARIA Ahad MUHAMMAD Naveed Akhtar AMJAD Farooq MASROOR Ahmad 《原子能科学技术》 EI CAS CSCD 北大核心 2024年第10期2068-2076,共9页
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 weat... 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. 展开更多
关键词 prediction of meteorological parameters weather research and forecasting model artificial neural networks nuclear emergency support system
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Progress and Achievements of Fengyun Meteorological Satellite Program since 2022
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作者 GUAN Min WANG Jingsong +4 位作者 ZHAO Xiangang QIN Danyu FAN Cunqun XIAN Di LIU Chang 《空间科学学报》 CAS CSCD 北大核心 2024年第4期712-721,共10页
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 opera... 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. 展开更多
关键词 Fengyun meteorological satellites Data services and application International cooperation and support
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Forecast Method of Ozone Concentration in Yulin City Based on Meteorological Conditions
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作者 Lidong MA Jiankang ZHANG Yanmei QU 《Meteorological and Environmental Research》 2024年第3期16-20,共5页
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 analy... 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. 展开更多
关键词 OZONE Weather situation meteorological factor Statistical forecast
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Analysis of a Typical Case of Meteorological Service in Tangpu Reservoir
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作者 Quan SHAN Yuxin DING +2 位作者 Tingting GU Jinxin WANG Kai TANG 《Meteorological and Environmental Research》 2024年第2期44-47,共4页
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... 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. 展开更多
关键词 Tangpu Reservoir meteorological service Continuous rain Analysis of a typical case
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Implications of Dynamic Interactions between Meteorological Patterns and Surface Water Quality on Environmental Health—A Case Study of the Nairobi River
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作者 Haron Safari Hongbin Chen +1 位作者 Edwin Kipkirui Duncan Mbuge 《Journal of Geoscience and Environment Protection》 2024年第5期113-146,共34页
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 wa... 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. 展开更多
关键词 Water Quality meteorological Conditions Urban Environment Environmental Health NAIROBI Water Quality Parameters
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Exploring the Relationship between Spatiotemporal Variations in Air Quality and Meteorological Parameters before and during the COVID-19 Pandemic in Xi’an
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作者 Muhammad Sajid Mehmood Shiyan Zhai +2 位作者 Gang Li Yaochen Qin Vithana Pathirannehelage Indika Sandamali Wijeratne 《Journal of Geoscience and Environment Protection》 2024年第8期115-148,共34页
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 meteorolog... 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. 展开更多
关键词 Spatiotemporal Analysis Air Quality Index meteorological Parameters COVID-19
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Analysis of Characteristics and Meteorological Influencing Factors of Air Pollution in Luojiang District,Deyang City
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作者 Zirui ZUO Hao XIANG +1 位作者 Huan YANG Yuxiang GAO 《Meteorological and Environmental Research》 2024年第4期24-28,共5页
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... 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. 展开更多
关键词 Luojiang District of Deyang City Air pollution METEOROLOGY CHARACTERISTICS
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Film Art:the Form of Audiovisual Aesthetics of Meteorological Communication
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作者 Zuixiong XIONGWEN 《Meteorological and Environmental Research》 CAS 2020年第4期43-48,共6页
Meteorological phenomenon widely exists in the film art as a subject,rhetoric,and culture.In theme creation,meteorological phenomenon is represented as fables of destiny and reality.In the broad view of rhetoric theor... Meteorological phenomenon widely exists in the film art as a subject,rhetoric,and culture.In theme creation,meteorological phenomenon is represented as fables of destiny and reality.In the broad view of rhetoric theory,meteorological phenomenon exists in the films as linguistic and formative rhetoric.Finally,the meteorological culture provides a wide range of contexts for film typing and stylization. 展开更多
关键词 meteorological communication meteorological film meteorological theme meteorological rhetoric meteorological culture
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Ensemble learning prediction of soybean yields in China based on meteorological data 被引量:1
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作者 LI Qian-chuan XU Shi-wei +3 位作者 ZHUANG Jia-yu LIU Jia-jia ZHOU Yi ZHANG Ze-xi 《Journal of Integrative Agriculture》 SCIE CAS CSCD 2023年第6期1909-1927,共19页
The accurate prediction of soybean yield is of great significance for agricultural production, monitoring and early warning.Although previous studies have used machine learning algorithms to predict soybean yield base... The accurate prediction of soybean yield is of great significance for agricultural production, monitoring and early warning.Although previous studies have used machine learning algorithms to predict soybean yield based on meteorological data,it is not clear how different models can be used to effectively separate soybean meteorological yield from soybean yield in various regions. In addition, comprehensively integrating the advantages of various machine learning algorithms to improve the prediction accuracy through ensemble learning algorithms has not been studied in depth. This study used and analyzed various daily meteorological data and soybean yield data from 173 county-level administrative regions and meteorological stations in two principal soybean planting areas in China(Northeast China and the Huang–Huai region), covering 34 years.Three effective machine learning algorithms(K-nearest neighbor, random forest, and support vector regression) were adopted as the base-models to establish a high-precision and highly-reliable soybean meteorological yield prediction model based on the stacking ensemble learning framework. The model's generalizability was further improved through 5-fold crossvalidation, and the model was optimized by principal component analysis and hyperparametric optimization. The accuracy of the model was evaluated by using the five-year sliding prediction and four regression indicators of the 173 counties, which showed that the stacking model has higher accuracy and stronger robustness. The 5-year sliding estimations of soybean yield based on the stacking model in 173 counties showed that the prediction effect can reflect the spatiotemporal distribution of soybean yield in detail, and the mean absolute percentage error(MAPE) was less than 5%. The stacking prediction model of soybean meteorological yield provides a new approach for accurately predicting soybean yield. 展开更多
关键词 meteorological factors ensemble learning crop yield prediction machine learning county-level
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Propagation characteristics from meteorological drought to agricultural drought over the Heihe River Basin, Northwest China 被引量:1
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作者 BAI Miao LI Zhanling +2 位作者 HUO Pengying WANG Jiawen LI Zhanjie 《Journal of Arid Land》 SCIE CSCD 2023年第5期523-544,共22页
In the context of global warming,drought events occur frequently.In order to better understanding the process and mechanism of drought occurrence and evolution,scholars have dedicated much attention on drought propaga... In the context of global warming,drought events occur frequently.In order to better understanding the process and mechanism of drought occurrence and evolution,scholars have dedicated much attention on drought propagation,mainly focusing on drought propagation time and propagation probability.However,there are relatively few studies on the sensitivities of drought propagation to seasons and drought levels.Therefore,we took the Heihe River Basin(HRB)of Northwest China as the case study area to quantify the propagation time and propagation probability from meteorological drought to agricultural drought during the period of 1981–2020,and subsequently explore their sensitivities to seasons(irrigation and non-irrigation seasons)and drought levels.The correlation coefficient method and Copula-based interval conditional probability model were employed to determine the drought propagation time and propagation probability.The results determined the average drought propagation time as 8 months in the whole basin,which was reduced by 2 months(i.e.,6 months)on average during the irrigation season and prolonged by 2 months(i.e.,10 months)during the non-irrigation season.Propagation probability was sensitive to both seasons and drought levels,and the sensitivities had noticeable spatial differences in the whole basin.The propagation probability of agricultural drought at different levels generally increased with the meteorological drought levels for the upstream,midstream,and southern downstream regions of the HRB.Lesser agricultural droughts were more likely to be triggered during the irrigation season,while severer agricultural droughts were occurred mostly during the non-irrigation season.The research results are helpful to understand the characteristics of drought propagation and provide a scientific basis for the prevention and control of droughts.This study is of great significance for the rational planning of local water resources and maintaining good ecological environment in the HRB. 展开更多
关键词 meteorological drought agricultural drought drought propagation time drought propagation probability Copula function interval conditional probability Heihe River Basin
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Meteorological factors, ambient air pollution, and daily hospital admissions for depressive disorder in Harbin: A time-series study 被引量:1
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作者 Ting Hu Zhao-Yuan Xu +2 位作者 Jian Wang Yao Su Bing-Bing Guo 《World Journal of Psychiatry》 SCIE 2023年第12期1061-1078,共18页
BACKGROUND The literature has discussed the relationship between environmental factors and depressive disorders;however,the results are inconsistent in different studies and regions,as are the interaction effects betw... BACKGROUND The literature has discussed the relationship between environmental factors and depressive disorders;however,the results are inconsistent in different studies and regions,as are the interaction effects between environmental factors.We hypo-thesized that meteorological factors and ambient air pollution individually affect and interact to affect depressive disorder morbidity.AIM To investigate the effects of meteorological factors and air pollution on depressive disorders,including their lagged effects and interactions.METHODS The samples were obtained from a class 3 hospital in Harbin,China.Daily hos-pital admission data for depressive disorders from January 1,2015 to December 31,2022 were obtained.Meteorological and air pollution data were also collected during the same period.Generalized additive models with quasi-Poisson regre-ssion were used for time-series modeling to measure the non-linear and delayed effects of environmental factors.We further incorporated each pair of environ-mental factors into a bivariate response surface model to examine the interaction effects on hospital admissions for depressive disorders.RESULTS Data for 2922 d were included in the study,with no missing values.The total number of depressive admissions was 83905.Medium to high correlations existed between environmental factors.Air temperature(AT)and wind speed(WS)significantly affected the number of admissions for depression.An extremely low temperature(-29.0℃)at lag 0 caused a 53%[relative risk(RR)=1.53,95%confidence interval(CI):1.23-1.89]increase in daily hospital admissions relative to the median temperature.Extremely low WSs(0.4 m/s)at lag 7 increased the number of admissions by 58%(RR=1.58,95%CI:1.07-2.31).In contrast,atmospheric pressure and relative humidity had smaller effects.Among the six air pollutants considered in the time-series model,nitrogen dioxide(NO_(2))was the only pollutant that showed significant effects over non-cumulative,cumulative,immediate,and lagged conditions.The cumulative effect of NO_(2) at lag 7 was 0.47%(RR=1.0047,95%CI:1.0024-1.0071).Interaction effects were found between AT and the five air pollutants,atmospheric temperature and the four air pollutants,WS and sulfur dioxide.CONCLUSION Meteorological factors and the air pollutant NO_(2) affect daily hospital admissions for depressive disorders,and interactions exist between meteorological factors and ambient air pollution. 展开更多
关键词 Mental health Depressive disorder Hospital admissions meteorological factors Air pollution Time-series
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Intensity Estimation of Extreme Meteorological and Hydrological Factors Induced by Tropical Cyclones Affecting Hong Kong
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作者 TAO Shanshan HUA Yunfei DONG Sheng 《Journal of Ocean University of China》 SCIE CAS CSCD 2023年第2期313-323,共11页
Hong Kong is often affected by tropical cyclones.The Hong Kong observatory issues warning signals based on the impact of tropical cyclones on the region.The joint frequency analysis of tropical cyclones in Hong Kong c... Hong Kong is often affected by tropical cyclones.The Hong Kong observatory issues warning signals based on the impact of tropical cyclones on the region.The joint frequency analysis of tropical cyclones in Hong Kong can provide a scientific basis for disaster reduction and prevention and post-disaster reconstruction of tropical cyclones.First,the maximum hourly mean wind speed(W),warning signal duration(D),maximum sea level(L),and total rainfall(R)of each tropical cyclone that affected Hong Kong from 1985 to 2019 are selected and fitted using the Gumbel,Weibull,Pearson type 3,and lognormal distributions.Then,bivariate copula functions,such as the Clayton,Frank,Gumbel-Hougaard,and Gaussian copulas,are applied to construct the joint probability models of W,D,L,and R,respectively.The joint return periods of W and D and those of L and R are defined as the meteorological and hydrological intensities of tropical cyclones,respectively.The results show that the joint return periods are good indicators of the comprehensive effect of the meteorological and hydrological intensities of tropical cyclones.No necessary correlation between meteorological and hydrological intensities of tropical cyclones exists.The meteorological and hydrological intensities of tropical cyclones show an upward trend in recent years. 展开更多
关键词 tropical cyclone warning signal meteorological intensity hydrological intensity copula
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Measuring moisture content of dead fine fuels based on the fusion of spectrum meteorological data
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作者 Bo Peng Jiawei Zhang +2 位作者 Jian Xing Jiuqing Liu Mingbao Li 《Journal of Forestry Research》 SCIE CAS CSCD 2023年第5期1333-1346,共14页
Dead fine fuel moisture content(DFFMC)is a key factor affecting the spread of forest fires,which plays an important role in evaluation of forest fire risk.In order to achieve high-precision real-time measurement of DF... Dead fine fuel moisture content(DFFMC)is a key factor affecting the spread of forest fires,which plays an important role in evaluation of forest fire risk.In order to achieve high-precision real-time measurement of DFFMC,this study established a long short-term memory(LSTM)network based on particle swarm optimization(PSO)algorithm as a measurement model.A multi-point surface monitoring scheme combining near-infrared measurement method and meteorological measurement method is proposed.The near-infrared spectral information of dead fine fuels and the meteorological factors in the region are processed by data fusion technology to construct a spectral-meteorological data set.The surface fine dead fuel of Mongolian oak(Quercus mongolica Fisch.ex Ledeb.),white birch(Betula platyphylla Suk.),larch(Larix gmelinii(Rupr.)Kuzen.),and Manchurian walnut(Juglans mandshurica Maxim.)in the maoershan experimental forest farm of the Northeast Forestry University were investigated.We used the PSO-LSTM model for moisture content to compare the near-infrared spectroscopy,meteorological,and spectral meteorological fusion methods.The results show that the mean absolute error of the DFFMC of the four stands by spectral meteorological fusion method were 1.1%for Mongolian oak,1.3%for white birch,1.4%for larch,and 1.8%for Manchurian walnut,and these values were lower than those of the near-infrared method and the meteorological method.The spectral meteorological fusion method provides a new way for high-precision measurement of moisture content of fine dead fuel. 展开更多
关键词 Near infrared spectroscopy meteorological factors Data fusion Long-term and short-term memory network Particle swarm optimization algorithm
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Future meteorological drought conditions in southwestern Iran based on the NEX-GDDP climate dataset
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作者 Sakine KOOHI Hadi RAMEZANI ETEDALI 《Journal of Arid Land》 SCIE CSCD 2023年第4期377-392,共16页
Investigation of the climate change effects on drought is required to develop management strategies for minimizing adverse social and economic impacts.Therefore,studying the future meteorological drought conditions at... Investigation of the climate change effects on drought is required to develop management strategies for minimizing adverse social and economic impacts.Therefore,studying the future meteorological drought conditions at a local scale is vital.In this study,we assessed the efficiency of seven downscaled Global Climate Models(GCMs)provided by the NASA Earth Exchange Global Daily Downscaled Projections(NEX-GDDP),and investigated the impacts of climate change on future meteorological drought using Standard Precipitation Index(SPI)in the Karoun River Basin(KRB)of southwestern Iran under two Representative Concentration Pathway(RCP)emission scenarios,i.e.,RCP4.5 and RCP8.5.The results demonstrated that SPI estimated based on the Meteorological Research Institute Coupled Global Climate Model version 3(MRI-CGCM3)is consistent with the one estimated by synoptic stations during the historical period(1990-2005).The root mean square error(RMSE)value is less than 0.75 in 77%of the synoptic stations.GCMs have high uncertainty in most synoptic stations except those located in the plain.Using the average of a few GCMs to improve performance and reduce uncertainty is suggested by the results.The results revealed that with the areas affected by wetness decreasing in the KRB,drought frequency in the North KRB is likely to increase at the end of the 21st century under RCP4.5 and RCP8.5 scenarios.At the seasonal scale,the decreasing trend for SPI in spring,summer,and winter shows a drought tendency in this region.The climate-induced drought hazard can have vast consequences,especially in agriculture and rural livelihoods.Accordingly,an increasing trend in drought during the growing seasons under RCP scenarios is vital for water managers and farmers to adopt strategies to reduce the damages.The results of this study are of great value for formulating sustainable water resources management plans affected by climate change. 展开更多
关键词 climate change meteorological drought Global Climate Models(GCMs) Standard Precipitation Index(SPI) Representative Concentration Pathway(RCP) NASA Earth Exchange Global Daily Downscaled Projections(NEX-GDDP) southwestern Iran
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Evaluation of meteorological predictions by the WRF model at Barrow, Alaska and Summit, Greenland in the Arctic in April 2019
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作者 ZHANG Tong CAO Le +1 位作者 LI Simeng WANG Jiandong 《Advances in Polar Science》 CSCD 2023年第4期352-367,共16页
Accurate meteorological predictions in the Arctic are important in response to the rapid climate change and insufficient meteorological observations in the Arctic.In this study,we adopted a high-resolution Weather Res... Accurate meteorological predictions in the Arctic are important in response to the rapid climate change and insufficient meteorological observations in the Arctic.In this study,we adopted a high-resolution Weather Research and Forecasting(WRF)model to simulate the meteorology at two Arctic stations(Barrow and Summit)in April 2019.Simulation results were also evaluated by using surface measurements and statistical parameters.In addition,weather charts during the studied time period were also used to assess the model performance.The results demonstrate that the WRF model is able to accurately capture the meteorological parameters for the two Arctic stations and the weather systems such as cyclones and anticyclones in the Arctic.Moreover,we found the model performance in predicting the surface pressure the best while the performance in predicting the wind the worst among these meteorological predictions.However,the wind predictions at these Arctic stations were found to be more accurate than those at urban stations in mid-latitude regions,due to the differences in land features and anthropogentic heat sources between these regions.In addition,a comparison of the simulation results showed that the prediction of meteorological conditions at Summit is superior to that at Barrow.Possible reasons for the deviations in temperature predictions between these two Arctic stations are uncertainties in the treatments of the sea ice and the cloud in the model.With respect to the wind,the deviations may source from the overestimation of the wind over the sea and at coastal stations. 展开更多
关键词 ARCTIC WRF meteorological parameters synoptic patterns model assessment
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Data-Driven Load Forecasting Using Machine Learning and Meteorological Data
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作者 Aishah Alrashidi Ali Mustafa Qamar 《Computer Systems Science & Engineering》 SCIE EI 2023年第3期1973-1988,共16页
Electrical load forecasting is very crucial for electrical power systems’planning and operation.Both electrical buildings’load demand and meteorological datasets may contain hidden patterns that are required to be i... Electrical load forecasting is very crucial for electrical power systems’planning and operation.Both electrical buildings’load demand and meteorological datasets may contain hidden patterns that are required to be investigated and studied to show their potential impact on load forecasting.The meteorological data are analyzed in this study through different data mining techniques aiming to predict the electrical load demand of a factory located in Riyadh,Saudi Arabia.The factory load and meteorological data used in this study are recorded hourly between 2016 and 2017.These data are provided by King Abdullah City for Atomic and Renewable Energy and Saudi Electricity Company at a site located in Riyadh.After applying the data pre-processing techniques to prepare the data,different machine learning algorithms,namely Artificial Neural Network and Support Vector Regression(SVR),are applied and compared to predict the factory load.In addition,for the sake of selecting the optimal set of features,13 different combinations of features are investigated in this study.The outcomes of this study emphasize selecting the optimal set of features as more features may add complexity to the learning process.Finally,the SVR algorithm with six features provides the most accurate prediction values to predict the factory load. 展开更多
关键词 Electricity load forecasting meteorological data machine learning feature selection modeling real-world problems predictive analytics
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Characterisation of Meteorological Drought in Northern Nigeria Using Comparative Rainfall-Based Drought Metrics
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作者 Onemayin David Jimoh Martins Yusuf Otache +2 位作者 Adeolu Richard Adesiji Rotimi Saka Olaleye James Agajo 《Journal of Water Resource and Protection》 CAS 2023年第2期51-70,共20页
Meteorological droughts occur when there is deficiency in rainfall;i.e. rainfall availability is below some acclaimed normal values. Hence, the greater challenge is to be able to obtain suitable methods for assessing ... Meteorological droughts occur when there is deficiency in rainfall;i.e. rainfall availability is below some acclaimed normal values. Hence, the greater challenge is to be able to obtain suitable methods for assessing drought occurrence, its onset or initiation and termination. Thus, an attempt was made in this paper to evaluate the performance of Standardised Precipitation Index (SPI) and Standardised Precipitation Anomaly Index (SPAI) to characterise drought in Northern Nigeria for purposes of comparison and eventual adoption of probable candidate index for the development of an Early Warning System. The findings indicated that despite the fact that the annual timescale may be long, it can be employed to obtain information on the temporal evolution of drought especially, regional behaviour. However, monthly timescale can be more appropriate if emphasis is on evaluating the effects of drought in situations relating to water supply, agriculture and groundwater abstractions. The SPAI can be employed for periodic rainfall time series though;it accentuates drought signatures and may not necessarily dampen high fluctuations due to implications of high climatic variability considering the stochastic nature and state transition of drought phenomena. On the other hand, the temporal evolution of SPI and SPAI were not coherent at different temporal accumulations with differences in fluctuations. However, despite the differences between the SPI and SPAI, generally at some timescales, for instance, 6-month accumulation, both spatial and temporal distributions of drought characteristics were seemingly consistent. In view of the observed shortcomings of both indices, especially the SPI, the Standardised Nonstationary Precipitation Index (SnsPI) should be looked into and too, other indexes that take into consideration the implications of global warming by incorporating potential evapotranspiration may be deemed more suitable for drought studies in Northern Nigeria. 展开更多
关键词 Characterisation TIMESCALE meteorological DROUGHT Metrics
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Comparisons of different statistical models for analyzing the effects of meteorological factors on COVID-19
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作者 Yulu Zheng Zheng Guo +2 位作者 Zhiyuan Wu Jun Wen Haifeng Hou 《Frigid Zone Medicine》 2023年第3期161-166,共6页
Objective:This general non-systematic review aimed to gather information on reported statistical models examing the effects of meteorological factors on coronavirus disease 2019(COVID-19)and compare these models.Metho... Objective:This general non-systematic review aimed to gather information on reported statistical models examing the effects of meteorological factors on coronavirus disease 2019(COVID-19)and compare these models.Methods:PubMed,Web of Science,and Google Scholar were searched for studies on"meteorological factors and COVID-19"published between January 1,2020,and October 1,2022.Results:The most commonly used approaches for analyzing the association between meteorological factors and COVID-19 were the linear regression model(LRM),generalized linear model(GLM),generalized additive model(GAM),and distributed lag non-linear model(DLNM).In addition to these classical models commonly applied in environmental epidemiology,machine learning techniques are increasingly being used to select risk factors for the outcome of interest and establishing robust prediction models.Conclusion:Selecting an appropriate model is essential before conducting research.To ensure the reliability of analysis results,it is important to consider including non-meteorological factors(e.g.,government policies on physical distancing,vaccination,and hygiene practices)along with meteorological factors in the model. 展开更多
关键词 coronavirus disease 2019 meteorological factors general coronavirus disease 2019 meteorological factors GENERAL
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