Advances in Meteorology最新文献

{"title":"The Characteristics of Thunderstorms and Their Lightning Activity on the Qinghai-Tibetan Plateau","authors":"Lei Hui, Yunjun Zhou, Zhi-teng Yan","doi":"10.1155/2022/9102145","DOIUrl":"https://doi.org/10.1155/2022/9102145","url":null,"abstract":"This paper discusses the temporal and spatial distribution characteristics of cloud-to-ground (CG) lightning activity over the Qinghai-Tibetan Plateau (QTP) from 2009 to 2018 and their dependence on meteorological factors. It is found that (1) the number of CG flashes fluctuates, reaches a maximum in 2014, and then gradually decreases. The main active period of CG lightning is from June to September each year, after which it decreases rapidly. CG lightning is mainly distributed in the valley areas at around 4800 m above sea level at Lhasa, Nagqu, and Chamdo, and there are differences in the characteristics of CG activity in these three areas. The peak of daily CG lightning occurs at 1000 UTC, and the lowest value is at 0400 UTC. The distribution of CG lightning in all seasons has obvious differences in peak time and the proportion of positive CG (+CG) lightning, with the ratio of +CG lightning to total CG lightning flashes in spring and autumn exceeding 50%. (2) The ratio of +CG lightning to total CG lightning flashes over the QTP is influenced by a combination of thermodynamic and microphysical factors. Over the QTP, greater vertical wind shear leads to the movement of upper positive charges and promotes the occurrence of +CG lightning. Also, the higher total column liquid water content implies higher cloud water content in the warm-cloud region, and the higher cloud-base height implies a thicker warm-cloud region, which is not conducive to the occurrence of +CG lightning. (3) During high-value years (in this study, 2010, 2012, 2014, and 2016), the midlatitude (30°N–60°N) high pressure is strong and the plateau is situated at the intersection of the East Asian and South Asian monsoons and the cold air from the northwest, which strengthens the water vapor convergence and increases the frequency of thunderstorms. When the plateau is under the control of the southerly monsoon from June to September every year, its atmosphere is full of water vapor and lightning activity is accordingly high, with the proportion of +CG lightning being about 10%. Meanwhile, in the remaining months, when controlled by the westerly wind belt, the plateau’s water vapor condition is poor, the level of lightning activity weakens, and the proportion of +CG lightning gradually increases to more than 50%.","PeriodicalId":7353,"journal":{"name":"Advances in Meteorology","volume":" ","pages":""},"PeriodicalIF":2.9,"publicationDate":"2022-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45978732","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}

{"title":"Modifying Covariance Localization to Mitigate Sampling Errors from the Ensemble Data Assimilation","authors":"Mingheng Chang, H. Zuo, Jikai Duan","doi":"10.1155/2022/6101721","DOIUrl":"https://doi.org/10.1155/2022/6101721","url":null,"abstract":"The ensemble-based Kalman filter requires at least a considerable ensemble (e.g., 10,000 members) to identify relevant error covariance at great distances for multidimensional geophysical systems. However, increasing numerous ensemble sizes will enlarge sampling errors. This study proposes a modified Cholesky decomposition based on the covariance localization (CL) scheme, namely a covariance localization scheme with modified Cholesky decomposition (CL-MC). Our main idea utilizes a modified Cholesky (MC) decomposition technique for estimating the background error covariance matrix; meanwhile, we employ the tunable singular value decomposition method on the background error covariance to improve the ensemble increment and avoid the imbalance of the system. To verify if the proposed method can effectively mitigate the sampling errors, numerical experiments are conducted on the Lorenz-96 model and large-scale model (SPEEDY model). The results show that the CL-MC method outperforms the CL method for different data assimilation parameters (ensemble sizes and localizations). Furthermore, by performing one year of assimilation experiments on the SPEEDY model, it is found that the 1-day forecast RMSEs obtained by the CL are approximately equal to the 5-day forecast RMSEs of CL-MC. So, the CL-MC method has potential advantages for long-term forecasting. Maybe the proposed CL-MC method achieves good prospects for widespread application in atmospheric general circulation models.","PeriodicalId":7353,"journal":{"name":"Advances in Meteorology","volume":" ","pages":""},"PeriodicalIF":2.9,"publicationDate":"2022-10-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43591217","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}

{"title":"Study on the Precursor Signal Capturing of Unfavorable Weather: Months/Years in Advance to Ultra-Early Forecast for Hourly Transient Weather Changes during the Beijing Winter Olympics","authors":"Deying Wang, Jizhi Wang, Yuanqin Yang, Liangke Liu, Wenxing Jia, J. Zhong, Yaqiang Wang","doi":"10.1155/2022/1409229","DOIUrl":"https://doi.org/10.1155/2022/1409229","url":null,"abstract":"Today, among the existing numerical weather prediction models, those detailing target classifications have been sufficiently explored; however, there are still many weather forecasting goals and needs, and research from theoretical to practical methods still needs additional study. For example, it is important to know as early as possible (months to years in advance) the forecast during a “specific large public event,” such as the hourly weather forecast for the Olympic Games. This study elaborates on the theory and methods for such ultra-early prediction of severe transient weather processes in the atmosphere. The main results of this study include (1) establishing the academic concept to capture precursor signals in modern meteorology and provide definitions; (2) establishing methods for capturing precursory signal quantification of unfavorable weather and proposing quantitative measurable thresholds; and (3) proposing the “ultra-early prediction” target task. A typical case is discussed: the meteorological conditions of the Beijing Winter Olympics, which serves as an example of social demand for weather forecasting of “special large-scale public activities,” as the case results show that the real-time observations during the Beijing Winter Olympics are consistent with the forecast and followed the precursor signal developed using the theoretical and methodological approaches in this study. The numerical quantization indicators for precursor signals include: (1) for a decrease in the height of the mixed layer hidden in the diurnal change; the precursor signal threshold is defined as a drop of more than 100 m for 3 consecutive days; (2) the signal of the δΘe displayed as a change by “negative ⟶ positive” of more than seven days in a continuous period. (3) the supersaturation (S) with thresholds reaching 6–7%, as well as the threshold <0.5 × 10−3 for saturated condensation flux signals (ξp); and (4) the hourly resolution transport index of PLAM (parameter linking air-pollution to meteorological condition) PLAM ⟶ obj remaining continuous for 48 h, with its threshold reaching more than 100.","PeriodicalId":7353,"journal":{"name":"Advances in Meteorology","volume":" ","pages":""},"PeriodicalIF":2.9,"publicationDate":"2022-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45694534","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}

{"title":"Local-Scale Weather Forecasts over a Complex Terrain in an Early Warning Framework: Performance Analysis for the Val d’Agri (Southern Italy) Case Study","authors":"G. Giunta, A. Ceppi, R. Salerno","doi":"10.1155/2022/2179246","DOIUrl":"https://doi.org/10.1155/2022/2179246","url":null,"abstract":"Forecasting applications based on hourly meteorological predictions for weather variables are nowadays used in energy market operations, planning of gas and power supply, and renewable energy, among others. Available meteorological and climatological data, as well as critical thresholds of rainfall, may also have a key role in the hazard classification, related to slope instabilities of pipelines and critical infrastructures along routes. The present study concerns the performance of a weather forecast model in the framework of an early warning system (EWS) application, which supports the integrity management of oil and gas pipelines. This EWS has been applied on to a specific area: the Val d’Agri basin in the Basilicata region of Southern Italy, which is extensively affected by several landslides and floods. The hourly precipitation forecasts are provided by a dedicated meteorological model, the KALM-HD, using two different horizontal resolutions, 1.25 and 5 km, to analyze possible influences of the mesh grid size as well. On this area, several weather stations were specifically deployed to obtain observed data in a region where hydrogeological hazards are relevant for asset management. A comparison among observations and the KALM-HD scaled forecasts on six of these weather stations is presented to assess the model performance. Besides, precipitation, temperature, and wind speed are evaluated as well. The forecasting analysis is performed considering two years of data both on an overall and seasonal basis. Results show that the KALM-HD performs well with the 1.25 km grid, particularly on temperature and wind speed variables. Since weather stations can be gathered in two main sets depending on their positions, differences arise in the forecast quality of these two groups, related to orography and thermal effects, whose detection is difficult in the typical narrow valleys characterizing the area of study. This issue prevalently influences temperatures and local winds, which, these latter, are generally underestimated, while precipitation is mainly driven by synoptic circulation and its interaction with mesoscale meteorological features.","PeriodicalId":7353,"journal":{"name":"Advances in Meteorology","volume":" ","pages":""},"PeriodicalIF":2.9,"publicationDate":"2022-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45846166","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}

{"title":"Improving Wind Speed Forecasting for Urban Air Mobility Using Coupled Simulations","authors":"Mounir Chrit, M. Majdi","doi":"10.1155/2022/2629432","DOIUrl":"https://doi.org/10.1155/2022/2629432","url":null,"abstract":"Hazardous weather, turbulence, wind, and thermals pose a ubiquitous challenge to Unmanned Aircraft Systems (UAS) and electric-Vertical Take-Off and Landing (e-VTOL) aircrafts, and the safe integration of UAS into urban area requires accurate high-granularity wind data especially during landing and takeoff phases. Two models, namely, Open-Source Field Operation and Manipulation (OpenFOAM) software package and Weather Research and Forecasting (WRF) model, are used in the present study to simulate airflow over Downtown Oklahoma City, Oklahoma, United States. Results show that computational fluid dynamics wind simulation driven by the atmospheric simulation significantly improves the simulated wind speed because the accurate modeling of the buildings affects wind patterns. The evaluation of different simulations against six Micronet stations shows that WRF-CFD numerical evaluation is a reliable method to understand the complicated wind flow within built-up areas. The comparison of wind distributions of simulations at different resolutions shows better description of wind variability and gusts generated by the urban flows. Simulations assuming anisotropy and isotropy of turbulence show small differences in the predicted wind speeds over Downtown Oklahoma City given the stable atmospheric stratification showing that turbulent eddy scales at the evaluation locations are within the inertial subrange and confirming that turbulence is locally isotropic.","PeriodicalId":7353,"journal":{"name":"Advances in Meteorology","volume":" ","pages":""},"PeriodicalIF":2.9,"publicationDate":"2022-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47483624","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}

{"title":"Variation of Leaf Area Index (LAI) under Changing Climate: Kadolkele Mangrove Forest, Sri Lanka","authors":"Randika K. Makumbura, Upaka S. Rathnayake","doi":"10.1155/2022/9693303","DOIUrl":"https://doi.org/10.1155/2022/9693303","url":null,"abstract":"Mangroves are an essential plant community in coastal ecosystems. While the importance of mangrove ecosystems is well acknowledged, climate change is expected to have a considerable negative impact on them, especially in terms of temperature, precipitation, sea level rise (SLR), ocean currents, and increasing storminess. Sri Lanka ranks near the bottom of the list of countries researching this problem, even though the scientific community's interest in examining the variation in mangrove health in response to climate change has gained significant attention. Consequently, this study illustrates how the leaf area index, a measure of mangrove health, fluctuates in response to varying precipitation, particularly during droughts in Sri Lanka's Kadolkele mangrove forest. The measurements of the normalized difference vegetation index (NDVI) were used to produce the leaf area index (LAI), which was then combined with the standard precipitation index (SPI) to estimate the health of the mangroves. The climate scenario, RCP8.5, was used to forecast future SPI (2021–2100), and LAI was modeled under the observed (1991–2019) and expected (2021–2100) drought events. The study reveals that the forecasted drought intensities modeled using the RCP8.5 scenario have no significant variations on LAI, even though some severe and extreme drought conditions exist. Nevertheless, the health of the mangrove ecosystem is predicted to deteriorate under drought conditions and rebound when drought intensity decreases. The extreme drought state (-2.05) was identified in 2064; therefore, LAI has showcased its lowest (0.04). LAI and SPI are projected to gradually increase from 2064 to 2100, while high fluctuations are observed from 2021 to 2064. Limited availability of LAI values with required details (measured date, time, and sample locations) and cloud-free Landsat images have affected the study results. This research presents a comprehensive understanding of Kadolkele mangrove forest under future droughts; thus, alarming relevant authorities to develop management plans to safeguard these critical ecosystems.","PeriodicalId":7353,"journal":{"name":"Advances in Meteorology","volume":" ","pages":""},"PeriodicalIF":2.9,"publicationDate":"2022-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41849518","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}

{"title":"Blue-Green Space Changes of Baiyangdian Wetland in Xiong’an New Area, China","authors":"Chunlei Zhao, S. Qian, Chengzhe Meng, Yufei Chang, Wenzhe Guo, Sha Wang, Yinglong Sun","doi":"10.1155/2022/4873393","DOIUrl":"https://doi.org/10.1155/2022/4873393","url":null,"abstract":"As a regulator of ecological environment, Baiyangdian Wetland is in a pivotal position in constructing the blue-green space (BGS) of Xiong’an New Area in China. This study aims to reveal the spatiotemporal changes of the BGS in Baiyangdian Wetland from 2016 to 2021. It uses Google Earth Engine (GEE) to calculate NDVI and NDWI based on Sentinel-2 Satellite remote sensing data and extracts the blue-green space by a classification model driven by NDVI and NDWI. Moreover, the land-use transfer matrix and landscape pattern indices are applied for evaluating the BGS changes in the wetland. According to the results, vegetation in the wetland shows no obvious spatial transfer. From 2016 to 2020, the BGS proportion in the wetland showed a stable increase, with the blue space getting larger by 10.8%. The indicators of the Number of Patches (NP), Patch Density (PD), Largest Patch Index (LPI), Contagion, and Landscape Shape Index (LSI) of the wetland decreased, suggesting a better ecological environment since the establishment of Xiong’an New Area in 2017. Based on the results, the author makes the following conclusion: the construction of BGS in Baiyangdian Wetland results in a well-organized ecological environment. The study provides a reference for building Xiong’an New Area and monitoring BGS changes in other regions.","PeriodicalId":7353,"journal":{"name":"Advances in Meteorology","volume":" ","pages":""},"PeriodicalIF":2.9,"publicationDate":"2022-09-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43993148","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}

{"title":"Frost Forecasting considering Geographical Characteristics","authors":"Hyo-Sook Kim, Jong-Min Kim, Sa-Heon Kim","doi":"10.1155/2022/1127628","DOIUrl":"https://doi.org/10.1155/2022/1127628","url":null,"abstract":"Regional accuracy was examined using extreme gradient boosting (XGBoost) to improve frost prediction accuracy, and accuracy differences by region were found. When the points were divided into two groups with weather variables, Group 1 had a coastal climate with a high minimum temperature, humidity, and wind speed and Group 2 exhibited relatively inland climate characteristics. We calculated the accuracy in the two groups and found that the precision and recall scores in coastal areas (Group 1) were significantly lower than those in the inland areas (Group 2). Geographic elements (distance from the nearest coast and height) were added as variables to improve accuracy. In addition, considering the continuity of frost occurrence, the method of reflecting the frost occurrence of the previous day as a variable and the synthetic minority oversampling technique (SMOTE) pretreatment were used to increase the learning ability.","PeriodicalId":7353,"journal":{"name":"Advances in Meteorology","volume":" ","pages":""},"PeriodicalIF":2.9,"publicationDate":"2022-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48538821","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}

{"title":"Wavelet Analysis of the Interconnection between Atmospheric Aerosol Types and Direct Irradiation over Cameroon","authors":"Yaulande Alotse Douanla, O. Mamadou, André Dembélé, Djidjoho Renaud Roméo Koukoui, Fifamè Edwige Akpoly, A. Lenouo","doi":"10.1155/2022/1030330","DOIUrl":"https://doi.org/10.1155/2022/1030330","url":null,"abstract":"The comparative analysis of the intra- and interannual dynamics between the Direct Normal Irradiation (DNI) under clear sky conditions and five aerosol types (Dust, Sea Salt, Black Carbon, Organic Carbon, and Sulfate) is the purpose of this study. To achieve this aim, we used fifteen-year DNI and aerosols data downloaded at 3-hour time intervals in nine defined zones throughout Cameroon. The wavelet transform is a powerful tool for studying local variability of amplitudes in a temporal dataset and constitutes our principal tool. The results show unequal distribution of aerosol types according to zones, but the Desert Dusts (DU) and Organic Carbon (OM) aerosols have been found as dominant particles in the studied region. The wavelet coherence analysis between DNI and each aerosol type reveals three bands of periodicity: \u0000 \u0000 ∼\u0000 \u0000 4-month band, 8–16-month band, and sometimes after-32-month band, with the most important frequency at 8–16-month band period. However, the intensity of coherence across bands varies with respect to aerosol type as well as each of the nine climate zones. A significant anticorrelation relationship was obtained between DNI and each type of aerosol, emphasizing that the presence of such atmospheric particles could dampen the renewable energy utilized by power systems. Also, the analysis shows that scattering aerosols such as Sulfate and Sea Salt (SU and SS, respectively) lead DNI in phase while absorbing aerosols such as Organic Carbon, Black Carbon, and Dust (OM, BC, and DU, respectively) give phase lag with DNI.","PeriodicalId":7353,"journal":{"name":"Advances in Meteorology","volume":" ","pages":""},"PeriodicalIF":2.9,"publicationDate":"2022-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45949025","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}

{"title":"Data-Driven versus Köppen–Geiger Systems of Climate Classification","authors":"Vajira Lasantha, T. Oki, Daisuke Tokuda","doi":"10.1155/2022/3581299","DOIUrl":"https://doi.org/10.1155/2022/3581299","url":null,"abstract":"Climate zone classification promotes our understanding of the climate and provides a framework for analyzing a range of environmental and socioeconomic data and phenomena. The Köppen–Geiger classification system is the most widely used climate classification scheme. In this study, we compared the climate zones objectively defined using data-driven methods with Köppen–Geiger rule-based classification. Cluster analysis was used to objectively delineate the world’s climatic regions. We applied three clustering algorithms—k-means, ISODATA, and unsupervised random forest classification—to a dataset comprising 10 climatic variables and elevation; we then compared the obtained results with those from the Köppen–Geiger classification system. Results from both the systems were similar for some climatic regions, especially extreme temperature ones such as the tropics, deserts, and polar regions. Data-driven classification identified novel climatic regions that the Köppen–Geiger classification could not. Refinements to the Köppen–Geiger classification, such as precipitation-based subdivisions to existing Köppen–Geiger climate classes like tropical rainforest (Af) and warm summer continental (Dfb), have been suggested based on clustering results. Climatic regions objectively defined by data-driven methods can further the current understanding of climate divisions. On the other hand, rule-based systems, such as the Köppen–Geiger classification, have an advantage in characterizing individual climates. In conclusion, these two approaches can complement each other to form a more objective climate classification system, wherein finer details can be provided by data-driven classification and supported by the intuitive structure of rule-based classification.","PeriodicalId":7353,"journal":{"name":"Advances in Meteorology","volume":" ","pages":""},"PeriodicalIF":2.9,"publicationDate":"2022-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42967435","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}