The diurnal variation characteristics of raindrop size distribution (RSD) in the Ili River Valley are investigated in this study, using the RSD data from May to September during 2020-2021 collected by a Parsivel2 disdrometer in Zhaosu. Significant diurnal variations (02–07, 08–13, 14–19, and 20-01 local standard time (LST)) of precipitation and RSD in Zhaosu are revealed during the rainy seasons. Precipitation mainly occurs in the late afternoon and early evening. A higher concentration of small raindrops is observed in the morning, whereas more mid-size and large raindrops are observed in the afternoon. The RSD exhibits diurnal differences between different rainfall rate classes; the diurnal difference of RSD is more pronounced in the case of high rainfall rates. Stratiform precipitation can occur at any time of the day, yet convective precipitation mainly occurs during the late afternoon and early evening. The RSD of stratiform rainfall shows a similar distribution over the four time periods. For convective rainfall, the concentration of small raindrops is the highest (lowest) over 02–07 (14–19) LST, while the highest (lowest) concentration of medium and large drops is observed over 14–19 (02–07) LST. Convective rain in the Ili River Valley over 14–19 LST can be characterized as the continental convective cluster, while in the rest time of the day, it is neither in the maritime cluster nor in the continental cluster. The empirical relationships between the radar reflectivity factor and rainfall rate (Z-R) for stratiform and convective rain types are also derived. The purpose of this study is to advance our understanding of precipitation microphysics in arid mountainous region.
{"title":"Diurnal Variation Characteristics of Raindrop Size Distribution Observed by a Parsivel2 Disdrometer in the Ili River Valley","authors":"Yufei Jiang, Lianmei Yang, Jiangang Li, Yong Zeng, Zepeng Tong, Xiaomeng Li, Haoyang Li","doi":"10.1155/2024/1481661","DOIUrl":"https://doi.org/10.1155/2024/1481661","url":null,"abstract":"The diurnal variation characteristics of raindrop size distribution (RSD) in the Ili River Valley are investigated in this study, using the RSD data from May to September during 2020-2021 collected by a Parsivel<sup>2</sup> disdrometer in Zhaosu. Significant diurnal variations (02–07, 08–13, 14–19, and 20-01 local standard time (LST)) of precipitation and RSD in Zhaosu are revealed during the rainy seasons. Precipitation mainly occurs in the late afternoon and early evening. A higher concentration of small raindrops is observed in the morning, whereas more mid-size and large raindrops are observed in the afternoon. The RSD exhibits diurnal differences between different rainfall rate classes; the diurnal difference of RSD is more pronounced in the case of high rainfall rates. Stratiform precipitation can occur at any time of the day, yet convective precipitation mainly occurs during the late afternoon and early evening. The RSD of stratiform rainfall shows a similar distribution over the four time periods. For convective rainfall, the concentration of small raindrops is the highest (lowest) over 02–07 (14–19) LST, while the highest (lowest) concentration of medium and large drops is observed over 14–19 (02–07) LST. Convective rain in the Ili River Valley over 14–19 LST can be characterized as the continental convective cluster, while in the rest time of the day, it is neither in the maritime cluster nor in the continental cluster. The empirical relationships between the radar reflectivity factor and rainfall rate (<i>Z</i>-<i>R</i>) for stratiform and convective rain types are also derived. The purpose of this study is to advance our understanding of precipitation microphysics in arid mountainous region.","PeriodicalId":7353,"journal":{"name":"Advances in Meteorology","volume":"9 1","pages":""},"PeriodicalIF":2.9,"publicationDate":"2024-01-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139475176","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Israel Gebresilasie Kimo, Bisrat Elias Cholo, Tarun Kumar Lohani
Understanding the sources of precipitation and their impacts is crucial for basin-wide water balance research. Previous research concentrated on the sources of moisture in Ethiopia. The southern part’s moisture sources, however, were not investigated. The primary objective of this study is to trace the source of atmospheric moisture in the Abaya-Chamo sub-basin of southern Ethiopia using numerical water vapor tracers like Hybrid Single Particle Lagrangian Integrated Trajectory (HYSPLIT) model. Exploring the possible regions of atmospheric vapor roots and the path of moist air initiating rainfall that reaches the basin was feasible for the year 2018–2020. The anticyclone from the Arabian High, which is positioned in the Arabian and Mediterranean seas, was the primary source of moisture supply in the study area during the Belg (March to May) season, according to the back trajectory cluster analysis results. Additionally, the Indian Ocean adds moisture resulting from Mascarene highs brought by equatorial easterlies. Furthermore, during Kiremt (June to September), air masses from the Congo basin were the potential moisture source region for the study areas in combination with air masses originating from the Mascarene highs, located in the South Indian Ocean, and the St. Helena high, centered in the subtropical southern Atlantic Ocean. This study primarily focuses on the complex dynamics of atmospheric moisture sources around Abaya-Chamo sub-basin of southern Ethiopia, offering insight into seasonal fluctuations and contributing various components. These findings contribute to basin-specific water balance research by filling gaps in the previous studies.
{"title":"Identifying the Moisture Sources in Different Seasons for Abaya-Chamo Basin of Southern Ethiopia Using Lagrangian Particle Dispersion Model","authors":"Israel Gebresilasie Kimo, Bisrat Elias Cholo, Tarun Kumar Lohani","doi":"10.1155/2024/4421766","DOIUrl":"https://doi.org/10.1155/2024/4421766","url":null,"abstract":"Understanding the sources of precipitation and their impacts is crucial for basin-wide water balance research. Previous research concentrated on the sources of moisture in Ethiopia. The southern part’s moisture sources, however, were not investigated. The primary objective of this study is to trace the source of atmospheric moisture in the Abaya-Chamo sub-basin of southern Ethiopia using numerical water vapor tracers like Hybrid Single Particle Lagrangian Integrated Trajectory (HYSPLIT) model. Exploring the possible regions of atmospheric vapor roots and the path of moist air initiating rainfall that reaches the basin was feasible for the year 2018–2020. The anticyclone from the Arabian High, which is positioned in the Arabian and Mediterranean seas, was the primary source of moisture supply in the study area during the Belg (March to May) season, according to the back trajectory cluster analysis results. Additionally, the Indian Ocean adds moisture resulting from Mascarene highs brought by equatorial easterlies. Furthermore, during Kiremt (June to September), air masses from the Congo basin were the potential moisture source region for the study areas in combination with air masses originating from the Mascarene highs, located in the South Indian Ocean, and the St. Helena high, centered in the subtropical southern Atlantic Ocean. This study primarily focuses on the complex dynamics of atmospheric moisture sources around Abaya-Chamo sub-basin of southern Ethiopia, offering insight into seasonal fluctuations and contributing various components. These findings contribute to basin-specific water balance research by filling gaps in the previous studies.","PeriodicalId":7353,"journal":{"name":"Advances in Meteorology","volume":"35 1","pages":""},"PeriodicalIF":2.9,"publicationDate":"2024-01-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139412505","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Farhad Zolfaghari, Hasan Khosravi, Shahram Khalighi Sigaroudi
The drying up of Hamoun International Wetland (HIW) and the loss of vegetation in this area have led to an increase in ambient temperature. This research examines the changes in the surface of HIW and its role in air temperature (Tair) using data on land surface temperature (LST), vegetation, wind speed, and relative humidity. The Cubist regression model (CRM) is used to simulate the effects of land surface factors (LSFs) on Tair. Four microsites with different plant cover percentages were selected for this purpose. After data collection, 75% of the data were used for modeling and 25% of the data were used for model testing. The results showed that CRM has adequate performance for estimating Tair. The assessment of the relationship between land surface temperature (LST) and Tair at 2 meter height showed that there was a high correlation coefficient between 0.86 and 0.91 in the different microsites. The results of using CRM for estimating Tair showed that this model can estimate air temperature from independent parameters of LST, wind speed, vegetation percentage, and relative humidity with a correlation coefficient of 0.98. In this model, the LST, relative humidity, and vegetation percentage were entered with values of 100%, 93%, and 83% respectively. Wind speed was not included in the model because the measurements were constant and less than 4 m/s throughout the period (no changes).
哈蒙国际湿地（HIW）的干涸和植被的减少导致了环境温度的升高。本研究利用地表温度 (LST)、植被、风速和相对湿度数据，研究了哈蒙国际湿地表面的变化及其对气温 (Tair) 的作用。采用立体回归模型（CRM）模拟地表因子（LSF）对气温的影响。为此选择了四个不同植物覆盖率的微观站点。数据收集后，75% 的数据用于建模，25% 的数据用于模型测试。结果表明，CRM 在估算 Tair 方面具有足够的性能。对 2 米高处的地表温度（LST）与 Tair 之间关系的评估表明，不同微观站点的相关系数在 0.86 至 0.91 之间。使用 CRM 估算 Tair 的结果表明，该模型可根据独立参数 LST、风速、植被百分比和相对湿度估算气温，相关系数为 0.98。在该模型中，低温层、相对湿度和植被率的输入值分别为 100%、93% 和 83%。风速未被纳入模型，因为测量值在整个期间都是恒定的，且小于 4 米/秒（无变化）。
{"title":"Air Temperature Modeling Based on Land Surface Factors by the Cubist Method (Case Study of Hamoun International Wetland)","authors":"Farhad Zolfaghari, Hasan Khosravi, Shahram Khalighi Sigaroudi","doi":"10.1155/2024/6466936","DOIUrl":"https://doi.org/10.1155/2024/6466936","url":null,"abstract":"The drying up of Hamoun International Wetland (HIW) and the loss of vegetation in this area have led to an increase in ambient temperature. This research examines the changes in the surface of HIW and its role in air temperature (Tair) using data on land surface temperature (LST), vegetation, wind speed, and relative humidity. The Cubist regression model (CRM) is used to simulate the effects of land surface factors (LSFs) on Tair. Four microsites with different plant cover percentages were selected for this purpose. After data collection, 75% of the data were used for modeling and 25% of the data were used for model testing. The results showed that CRM has adequate performance for estimating Tair. The assessment of the relationship between land surface temperature (LST) and Tair at 2 meter height showed that there was a high correlation coefficient between 0.86 and 0.91 in the different microsites. The results of using CRM for estimating Tair showed that this model can estimate air temperature from independent parameters of LST, wind speed, vegetation percentage, and relative humidity with a correlation coefficient of 0.98. In this model, the LST, relative humidity, and vegetation percentage were entered with values of 100%, 93%, and 83% respectively. Wind speed was not included in the model because the measurements were constant and less than 4 m/s throughout the period (no changes).","PeriodicalId":7353,"journal":{"name":"Advances in Meteorology","volume":"3 1","pages":""},"PeriodicalIF":2.9,"publicationDate":"2024-01-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139397652","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Liang Zhang, Zeming Zhou, Qian Li, Xiao Feng, Kangquan Yang
Sichuan is a high-incidence area of thunderstorm activity in China. Based on the data of the total lightning location system from 2018 to 2022, the total lightning, cloud-to-ground (CG) lightning, and intracloud (IC) lightning activity regularity for the Sichuan province (SC) and its three climate subregions: Sichuan Basin (SB), Panxi district (PD), and West Sichuan Plateau (WSP) are analyzed, and the influences of different climate and topography conditions on lightning activities are also discussed. The results show that (1) for the whole province, the annual mean value of total lightning is about 850 thousand. The SB has the most lightning occurrences, and the WSP has the largest IC and +CG proportion. The southwest of PD, the north-center of PD, and the southeast of SB are the three high-value centers of lightning density. (2) For SB, the better thermodynamic and moisture conditions account for the most lightning occurrences. For PD, the lightning distribution is attributed to the joint effect of specific meteorological conditions and mountainous topography. For WSP, the convections are weak and shallow, which lead to high IC and +CG proportion. (3) The IC lightning mainly occurs below 12 km, and the IC height is much lower on WSP. The spatial and seasonal variation of IC height corresponds well to the cloud base height (CBH) and cloud top height (CTH). (4) The seasonal lightning frequency distribution in the three regions is similar, but the diurnal variation is quite different. The lightning activity mainly occurs between 1400 and 2200 LT on WSP but shows obvious nocturnal in SB. (5) Most CG intensity concentrates in the range below 50 kA, and IC concentrates in the range below 75 kA.
四川是中国雷暴活动的高发区。基于2018-2022年总雷电定位系统数据，分析了四川省及其三个气候分区的总雷电、云到地（CG）雷电和云内（IC）雷电活动规律性：分析了四川盆地（SB）、攀西地区（PD）和川西高原（WSP）的雷电活动，并讨论了不同气候和地形条件对雷电活动的影响。结果表明：(1) 全省年均雷电总数约为 85 万次。南部山区雷电发生次数最多，西部山区 IC 和 +CG 所占比例最大。浦东新区西南部、浦东新区北中部和南部湾区东南部是三个雷电密度高值中心。(2）对于 SB，较好的热动力和湿度条件是雷电发生最多的原因。对于 PD 而言，雷电分布归因于特定气象条件和山区地形的共同作用。对于 WSP，对流较弱且较浅，导致 IC 和 +CG 比例较高。(3）集成电路闪电主要发生在 12 km 以下，集成电路高度在 WSP 上更低。集成电路高度的空间和季节变化与云底高度和云顶高度十分吻合。 (4) 三地的季节性闪电频率分布相似，但日变化差异较大。西太平洋地区的雷电活动主要发生在 1400 至 2200 LT 之间，但在南太平洋地区则表现出明显的夜间性。(5) 大部分 CG 闪电强度集中在 50 kA 以下，IC 闪电强度集中在 75 kA 以下。
{"title":"Five-Year Analysis of Lightning Activities in Different Climatic Regions of Sichuan Province, China","authors":"Liang Zhang, Zeming Zhou, Qian Li, Xiao Feng, Kangquan Yang","doi":"10.1155/2023/9953551","DOIUrl":"https://doi.org/10.1155/2023/9953551","url":null,"abstract":"Sichuan is a high-incidence area of thunderstorm activity in China. Based on the data of the total lightning location system from 2018 to 2022, the total lightning, cloud-to-ground (CG) lightning, and intracloud (IC) lightning activity regularity for the Sichuan province (SC) and its three climate subregions: Sichuan Basin (SB), Panxi district (PD), and West Sichuan Plateau (WSP) are analyzed, and the influences of different climate and topography conditions on lightning activities are also discussed. The results show that (1) for the whole province, the annual mean value of total lightning is about 850 thousand. The SB has the most lightning occurrences, and the WSP has the largest IC and +CG proportion. The southwest of PD, the north-center of PD, and the southeast of SB are the three high-value centers of lightning density. (2) For SB, the better thermodynamic and moisture conditions account for the most lightning occurrences. For PD, the lightning distribution is attributed to the joint effect of specific meteorological conditions and mountainous topography. For WSP, the convections are weak and shallow, which lead to high IC and +CG proportion. (3) The IC lightning mainly occurs below 12 km, and the IC height is much lower on WSP. The spatial and seasonal variation of IC height corresponds well to the cloud base height (CBH) and cloud top height (CTH). (4) The seasonal lightning frequency distribution in the three regions is similar, but the diurnal variation is quite different. The lightning activity mainly occurs between 1400 and 2200 LT on WSP but shows obvious nocturnal in SB. (5) Most CG intensity concentrates in the range below 50 kA, and IC concentrates in the range below 75 kA.","PeriodicalId":7353,"journal":{"name":"Advances in Meteorology","volume":"1 1","pages":""},"PeriodicalIF":2.9,"publicationDate":"2023-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138687159","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
As the unpredictable nature of the Earth’s climate persists, the scholarly attention dedicated to climate research has undergone a notable transition, shifting its emphasis from the conventional notion of global warming to a greater disconcerting occurrence commonly referred to as “global boiling.” The present article endeavors to elucidate the scientific evidence that posits a discernible alteration in climate patterns, specifically towards an exacerbation of extreme heat events. Furthermore, this study aims to delve into the various factors that are believed to be instrumental in precipitating this noteworthy phenomenon. Furthermore, we engage in a comprehensive examination of the potential ramifications on ecological systems, human communities, and the imperative necessity for proactive measures aimed at both mitigating and adapting to these challenges. This paper endeavors to elucidate the potential issues presented by the period of global boiling through a thorough examination of existing research and data. Furthermore, it seeks to underscore the significance of concerted efforts to effectively tackle this pressing matter.
{"title":"Perspective on the Era of Global Boiling: A Future beyond Global Warming","authors":"Teerachai Amnuaylojaroen","doi":"10.1155/2023/5580606","DOIUrl":"https://doi.org/10.1155/2023/5580606","url":null,"abstract":"As the unpredictable nature of the Earth’s climate persists, the scholarly attention dedicated to climate research has undergone a notable transition, shifting its emphasis from the conventional notion of global warming to a greater disconcerting occurrence commonly referred to as “global boiling.” The present article endeavors to elucidate the scientific evidence that posits a discernible alteration in climate patterns, specifically towards an exacerbation of extreme heat events. Furthermore, this study aims to delve into the various factors that are believed to be instrumental in precipitating this noteworthy phenomenon. Furthermore, we engage in a comprehensive examination of the potential ramifications on ecological systems, human communities, and the imperative necessity for proactive measures aimed at both mitigating and adapting to these challenges. This paper endeavors to elucidate the potential issues presented by the period of global boiling through a thorough examination of existing research and data. Furthermore, it seeks to underscore the significance of concerted efforts to effectively tackle this pressing matter.","PeriodicalId":7353,"journal":{"name":"Advances in Meteorology","volume":"31 1","pages":""},"PeriodicalIF":2.9,"publicationDate":"2023-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138562323","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Yan Hu, Enrong Zhao, Hongwu Liu, Lin Xu, Kexin Tan, Huanqian Liu, Qingxia Wang
Due to the unique topography and geographical location, severe snowfall is the main disastrous weather in winter in the Hunan Province of China. Based on the daily precipitation data in Hunan Province from 1961 to 2021, the regional heavy snowfall processes are classified by using the synoptic diagnostic method. In addition, the water vapor transport characteristics of typical heavy snowfall processes are analyzed by the hybrid single-particle Lagrangian integrated trajectory (HYSPLIT) air mass backward trajectory model. Then, the responses of the differences in water vapor transport to heavy snowfall under different weather situations are discussed. The results show that the spatial distribution of climatic mean heavy snowfall days in Hunan Province is extremely uneven, and the heavy snowfall days decrease from north to south, with the most in the Dongting Lake area and the least in the Nanling Mountains. In the past decades, snowstorms mainly occur in local areas, and there are fewer widespread snowstorms. The frequency of heavy snowfall days generally shows a decreasing trend, with three peaks all appearing before 1990. After the 2010s, the number of days and stations of heavy snowfall decreased noticeably, and so did the number of regional heavy snowfall processes. This result indicates that global warming has remarkable effects on the snowstorm events in Hunan Province. Heavy snowfall mainly occurs from December to February, and peaks from mid-January to early February. Over the past 61 years, more than 50% of heavy snowstorm events occurred after 2000. According to the main weather systems affecting regional heavy snowfall processes, these weather processes in Hunan Province can be classified into three categories: southern branch trough (SBT) type, blocking high collapse (BHC) type, and stepped trough type. Among them, the SBT type accounts for more than 60% of the heavy snowfall events in Hunan. In terms of the SBT type and the stepped trough type, the water vapor from the high-latitude inland and low-latitude sea surface accounts for a comparable proportion, each accounting for nearly 50%. For the SBT type, the proportion of the water vapor from warm-humid airflows is slightly higher than that from cold-humid airflows. However, in terms of the stepped trough type, the water vapor transported by cold-humid airflows from the north contributes more than that by warm-humid airflows. For the BHC type, the specific humidity and the water vapor from the high-latitude inland contribute 70% of heavy snowfall processes. In addition, the contribution of the two southwesterly water vapor channels to heavy snowfall processes is small. The water vapor sources differ remarkably for different heavy snowfall types, but all of them are dominated by the water vapor transport in the middle and lower troposphere, which is the main reason why the formation of snowfall areas under different weather types is obviously different.
{"title":"Climatic Characteristics of Heavy Snowfall and the Water Vapor Transport Characteristics in Typical Snowfall Events in Hunan Province of China","authors":"Yan Hu, Enrong Zhao, Hongwu Liu, Lin Xu, Kexin Tan, Huanqian Liu, Qingxia Wang","doi":"10.1155/2023/9509493","DOIUrl":"https://doi.org/10.1155/2023/9509493","url":null,"abstract":"Due to the unique topography and geographical location, severe snowfall is the main disastrous weather in winter in the Hunan Province of China. Based on the daily precipitation data in Hunan Province from 1961 to 2021, the regional heavy snowfall processes are classified by using the synoptic diagnostic method. In addition, the water vapor transport characteristics of typical heavy snowfall processes are analyzed by the hybrid single-particle Lagrangian integrated trajectory (HYSPLIT) air mass backward trajectory model. Then, the responses of the differences in water vapor transport to heavy snowfall under different weather situations are discussed. The results show that the spatial distribution of climatic mean heavy snowfall days in Hunan Province is extremely uneven, and the heavy snowfall days decrease from north to south, with the most in the Dongting Lake area and the least in the Nanling Mountains. In the past decades, snowstorms mainly occur in local areas, and there are fewer widespread snowstorms. The frequency of heavy snowfall days generally shows a decreasing trend, with three peaks all appearing before 1990. After the 2010s, the number of days and stations of heavy snowfall decreased noticeably, and so did the number of regional heavy snowfall processes. This result indicates that global warming has remarkable effects on the snowstorm events in Hunan Province. Heavy snowfall mainly occurs from December to February, and peaks from mid-January to early February. Over the past 61 years, more than 50% of heavy snowstorm events occurred after 2000. According to the main weather systems affecting regional heavy snowfall processes, these weather processes in Hunan Province can be classified into three categories: southern branch trough (SBT) type, blocking high collapse (BHC) type, and stepped trough type. Among them, the SBT type accounts for more than 60% of the heavy snowfall events in Hunan. In terms of the SBT type and the stepped trough type, the water vapor from the high-latitude inland and low-latitude sea surface accounts for a comparable proportion, each accounting for nearly 50%. For the SBT type, the proportion of the water vapor from warm-humid airflows is slightly higher than that from cold-humid airflows. However, in terms of the stepped trough type, the water vapor transported by cold-humid airflows from the north contributes more than that by warm-humid airflows. For the BHC type, the specific humidity and the water vapor from the high-latitude inland contribute 70% of heavy snowfall processes. In addition, the contribution of the two southwesterly water vapor channels to heavy snowfall processes is small. The water vapor sources differ remarkably for different heavy snowfall types, but all of them are dominated by the water vapor transport in the middle and lower troposphere, which is the main reason why the formation of snowfall areas under different weather types is obviously different.","PeriodicalId":7353,"journal":{"name":"Advances in Meteorology","volume":"77 1","pages":""},"PeriodicalIF":2.9,"publicationDate":"2023-12-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138545267","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The main visibility forecast factors were identified with the support of data from routine meteorological observations from the Mianyang Airport and the Mianyang Environmental Monitoring Station from 2015 to 2018, and a visibility grading forecast model was established and tested by dint of the multiple linear regression and the KNN algorithm based on big data mining technology, and the variation characteristics of visibility in winter at the Mianyang Airport were studied. The results showed that (1) in addition to having a significant positive correlation with wind speed, the visibility in winter at the Mianyang Airport has a significant negative correlation with relative humidity, dew point temperature, AQI, PM2.5 concentration, PM10 concentration, and CO, and it has the strongest correlation with relative humidity, and the correlation coefficient is −0.76. (2) The multivariate linear regression model and the KNN model were adopted for grading forecasting experiments on visibility, and the results revealed that both models could be used for visibility grading forecasts. The multiple regression model secures an accuracy of over 70% for forecasts of level 1–5 visibility. In terms of the KNN model, the forecast accuracy is the best when K = 3 or K = 5, notably for level-2, level-4, and level-5 visibility. The forecast accuracy rate is 100% for level-2 visibility, but the forecast for level-1 visibility is poor. (3) The minimum value of the average daily visibility of the Mianyang Airport in winter appeared at 09 : 00 and the maximum value appeared at 17 : 00. The level-1 visibility occurred and developed before 09 : 00 and faded and vanished between 08 : 00 and 15 : 00.
{"title":"Comparison of the Visibility Grading Forecast Method Based on Meteorological Factors and Environmental Factors","authors":"Yanyan Long, Fei Li, Wenjun Sang","doi":"10.1155/2023/5847787","DOIUrl":"https://doi.org/10.1155/2023/5847787","url":null,"abstract":"The main visibility forecast factors were identified with the support of data from routine meteorological observations from the Mianyang Airport and the Mianyang Environmental Monitoring Station from 2015 to 2018, and a visibility grading forecast model was established and tested by dint of the multiple linear regression and the KNN algorithm based on big data mining technology, and the variation characteristics of visibility in winter at the Mianyang Airport were studied. The results showed that (1) in addition to having a significant positive correlation with wind speed, the visibility in winter at the Mianyang Airport has a significant negative correlation with relative humidity, dew point temperature, AQI, PM2.5 concentration, PM10 concentration, and CO, and it has the strongest correlation with relative humidity, and the correlation coefficient is −0.76. (2) The multivariate linear regression model and the KNN model were adopted for grading forecasting experiments on visibility, and the results revealed that both models could be used for visibility grading forecasts. The multiple regression model secures an accuracy of over 70% for forecasts of level 1–5 visibility. In terms of the KNN model, the forecast accuracy is the best when K = 3 or K = 5, notably for level-2, level-4, and level-5 visibility. The forecast accuracy rate is 100% for level-2 visibility, but the forecast for level-1 visibility is poor. (3) The minimum value of the average daily visibility of the Mianyang Airport in winter appeared at 09 : 00 and the maximum value appeared at 17 : 00. The level-1 visibility occurred and developed before 09 : 00 and faded and vanished between 08 : 00 and 15 : 00.","PeriodicalId":7353,"journal":{"name":"Advances in Meteorology","volume":"17 11","pages":""},"PeriodicalIF":2.9,"publicationDate":"2023-11-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139251379","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Climate analysis at relevant time scales is important for water resources management, agricultural planning, flood risk assessment, ecological modeling, and climate change adaptation. This study analyzes the spatiotemporal variability of climate on rainfall distribution for the Hare catchment of Ethiopia. Numerous hydroclimatic variables and scenarios were developed to assess the pattern of rainfall during different seasons. The average annual precipitation varies between −37.3%, +33.1%, and −38.2%, +61.2%, for RCP 4.5 and RCP 8.5, respectively. The anticipated declines in mean seasonal rainfall changes for the Bega and Belg seasons range from −69.6% to 88.4% and from −60.6% to 15.2% for RCP 4.5 and RCP 8.5, respectively. Climate models predict that the average periodic precipitation considered for the Kiremt season will vary from −12.1% to 1.33%. The Belg, Kiremt, and Bega seasons will likely see a 28.2%, 12.2%, and 22.6% drop in mean seasonal precipitation, respectively. The decrease in stream flow accompanied by the aforementioned climate scenarios (RCP 4.5 and RCP 8.5) can be as high as 19.6% and 6.7%, respectively. Also, the amount of discharge will reduce in the near future because of a substantial reduction in rainfall and a rise in evapotranspiration in the catchment. This decline in stream flow has its own effect on the future availability of water resources. The research finding is vital to environmental protection authority, decision makers, and scientific community to undertake climate change adaption techniques for rain scare areas. A program combined with multi-RCMs to evaluate climate change effects on hydrometeorology generated a novel approach to this research with appropriate adaptation mechanisms.
{"title":"The Synergic Effects of Climate Variability on Rainfall Distribution over Hare Catchment of Ethiopia","authors":"Abebe Temesgen Ayalew","doi":"10.1155/2023/1175426","DOIUrl":"https://doi.org/10.1155/2023/1175426","url":null,"abstract":"Climate analysis at relevant time scales is important for water resources management, agricultural planning, flood risk assessment, ecological modeling, and climate change adaptation. This study analyzes the spatiotemporal variability of climate on rainfall distribution for the Hare catchment of Ethiopia. Numerous hydroclimatic variables and scenarios were developed to assess the pattern of rainfall during different seasons. The average annual precipitation varies between −37.3%, +33.1%, and −38.2%, +61.2%, for RCP 4.5 and RCP 8.5, respectively. The anticipated declines in mean seasonal rainfall changes for the Bega and Belg seasons range from −69.6% to 88.4% and from −60.6% to 15.2% for RCP 4.5 and RCP 8.5, respectively. Climate models predict that the average periodic precipitation considered for the Kiremt season will vary from −12.1% to 1.33%. The Belg, Kiremt, and Bega seasons will likely see a 28.2%, 12.2%, and 22.6% drop in mean seasonal precipitation, respectively. The decrease in stream flow accompanied by the aforementioned climate scenarios (RCP 4.5 and RCP 8.5) can be as high as 19.6% and 6.7%, respectively. Also, the amount of discharge will reduce in the near future because of a substantial reduction in rainfall and a rise in evapotranspiration in the catchment. This decline in stream flow has its own effect on the future availability of water resources. The research finding is vital to environmental protection authority, decision makers, and scientific community to undertake climate change adaption techniques for rain scare areas. A program combined with multi-RCMs to evaluate climate change effects on hydrometeorology generated a novel approach to this research with appropriate adaptation mechanisms.","PeriodicalId":7353,"journal":{"name":"Advances in Meteorology","volume":"18 22","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135589510","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
To understand the transport patterns and major sources of ozone (O3) in Nanjing, this study carried out the 48-hour backward trajectories of air masses in Nanjing from March 2021 to March 2022, based on the HYSPLIT backward trajectory model driven by GDAS global reanalysis data. The primary transmission routes and putative source locations of O3 pollution in Nanjing were determined through the integration of trajectory clustering analysis, potential source contribution function (PSCF), and concentration-weighted trajectory (CWT) analysis with meteorological data and O3 concentration data. The results showed that the high O3 concentrations and exceedance rates in Nanjing were in late spring and early summer, with the highest in June. The diurnal variation of O3 concentrations in all seasons exhibited a single peak with a maximum from 13:00 to 16:00. The southeasterly flow passing through Zhenjiang, Changzhou, Wuxi, Suzhou, and Shanghai dominated the O3 pollution in Nanjing. The PSCF and CWT presented a high consistency of O3 potential sources in Nanjing. Zhenjiang, Ma’anshan, Changzhou, Wuxi, Suzhou, and Huzhou were identified as the main potential source regions of O3 pollution in Nanjing. This study provides accurate theoretical references for regional joint prevention and control of O3 pollution in Nanjing.
{"title":"Study on O3 Variations in Nanjing and the Surrounding Source Analysis","authors":"Jiaqi Shi, Jinhu Wang, Yuqing Zhang, Dinyuan Liang, Anhong Xiao","doi":"10.1155/2023/5519469","DOIUrl":"https://doi.org/10.1155/2023/5519469","url":null,"abstract":"To understand the transport patterns and major sources of ozone (O3) in Nanjing, this study carried out the 48-hour backward trajectories of air masses in Nanjing from March 2021 to March 2022, based on the HYSPLIT backward trajectory model driven by GDAS global reanalysis data. The primary transmission routes and putative source locations of O3 pollution in Nanjing were determined through the integration of trajectory clustering analysis, potential source contribution function (PSCF), and concentration-weighted trajectory (CWT) analysis with meteorological data and O3 concentration data. The results showed that the high O3 concentrations and exceedance rates in Nanjing were in late spring and early summer, with the highest in June. The diurnal variation of O3 concentrations in all seasons exhibited a single peak with a maximum from 13:00 to 16:00. The southeasterly flow passing through Zhenjiang, Changzhou, Wuxi, Suzhou, and Shanghai dominated the O3 pollution in Nanjing. The PSCF and CWT presented a high consistency of O3 potential sources in Nanjing. Zhenjiang, Ma’anshan, Changzhou, Wuxi, Suzhou, and Huzhou were identified as the main potential source regions of O3 pollution in Nanjing. This study provides accurate theoretical references for regional joint prevention and control of O3 pollution in Nanjing.","PeriodicalId":7353,"journal":{"name":"Advances in Meteorology","volume":"20 3","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135567184","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Cold front is an important weather system that produces precipitation in East Asia. Under the background of global warming, extreme precipitation caused by cold fronts presents a significant increasing trend. Hence, it is very important to quantify the cold-front precipitation that may cause great damages. In this study, an objective identification method is proposed for cold-front precipitation, which can objectively identify the precipitation area affected by cold fronts. Then, the climatological characteristics and trends of cold-front precipitation over East Asia in the winter half years from 1989 to 2018 are investigated by using the ERA-5 reanalysis dataset. Based on the dataset of cold fronts and frontal zones, this method automatically distinguishes the precipitation area affected by cold fronts to quantitatively estimate cold-front precipitation. The results show that this identification method can well describe cold-front activities and associated precipitation during an extreme cold wave event that occurred in southern China in January 2016. In the past 30 years, cold fronts have significantly contributed to the precipitation in East Asia in winter half years. The areas with the maximum cold-front precipitation and maximum contribution rate of cold-front precipitation to total precipitation are located in the North Pacific storm track, cold-front precipitation exceeds 700 mm, and the contribution of cold-front precipitation to total precipitation exceeds 60%. In addition, the contribution rates of cold-front precipitation are also relatively large in the midlatitudes of East Asia, especially in North China and Northeast China, where cold-front precipitation accounts for 50%–60% of total precipitation. In East Asia, the total precipitation in autumn is greater than that in winter; however, cold-front precipitation and its contribution rate in winter are significantly more and larger than those in autumn. As the cold-frontal activity is more frequent and intense in winter, the rainfall in winter depends more on cold fronts. In the past 30 years, the trends of cold-front precipitation and total precipitation are consistent in most parts of East Asia, indicating that cold-front precipitation makes a great contribution to the trend of total precipitation in winter half years.
{"title":"Objective Identification Method of Cold-Front Precipitation in Winter Half Years over East Asia","authors":"Shuya He, Yujing Qin, Chuhan Lu, Mengru Feng","doi":"10.1155/2023/2361993","DOIUrl":"https://doi.org/10.1155/2023/2361993","url":null,"abstract":"Cold front is an important weather system that produces precipitation in East Asia. Under the background of global warming, extreme precipitation caused by cold fronts presents a significant increasing trend. Hence, it is very important to quantify the cold-front precipitation that may cause great damages. In this study, an objective identification method is proposed for cold-front precipitation, which can objectively identify the precipitation area affected by cold fronts. Then, the climatological characteristics and trends of cold-front precipitation over East Asia in the winter half years from 1989 to 2018 are investigated by using the ERA-5 reanalysis dataset. Based on the dataset of cold fronts and frontal zones, this method automatically distinguishes the precipitation area affected by cold fronts to quantitatively estimate cold-front precipitation. The results show that this identification method can well describe cold-front activities and associated precipitation during an extreme cold wave event that occurred in southern China in January 2016. In the past 30 years, cold fronts have significantly contributed to the precipitation in East Asia in winter half years. The areas with the maximum cold-front precipitation and maximum contribution rate of cold-front precipitation to total precipitation are located in the North Pacific storm track, cold-front precipitation exceeds 700 mm, and the contribution of cold-front precipitation to total precipitation exceeds 60%. In addition, the contribution rates of cold-front precipitation are also relatively large in the midlatitudes of East Asia, especially in North China and Northeast China, where cold-front precipitation accounts for 50%–60% of total precipitation. In East Asia, the total precipitation in autumn is greater than that in winter; however, cold-front precipitation and its contribution rate in winter are significantly more and larger than those in autumn. As the cold-frontal activity is more frequent and intense in winter, the rainfall in winter depends more on cold fronts. In the past 30 years, the trends of cold-front precipitation and total precipitation are consistent in most parts of East Asia, indicating that cold-front precipitation makes a great contribution to the trend of total precipitation in winter half years.","PeriodicalId":7353,"journal":{"name":"Advances in Meteorology","volume":"16 13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135728680","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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