Meteorological Applications最新文献_第2页

Multi-site collaborative forecasting of regional visibility based on spatiotemporal convolutional network 基于时空卷积网络的区域能见度多站点协同预报

IF 2.3 4区地球科学

Meteorological Applications Pub Date : 2024-09-30 DOI: 10.1002/met.2206

Wei Tian, Chen Lin, Yunlong Wu, Cheng Jin, Xin Li

{"title":"Multi-site collaborative forecasting of regional visibility based on spatiotemporal convolutional network","authors":"Wei Tian, Chen Lin, Yunlong Wu, Cheng Jin, Xin Li","doi":"10.1002/met.2206","DOIUrl":"https://doi.org/10.1002/met.2206","url":null,"abstract":"Regional visibility forecasting encounters challenges due to data imbalance, temporal non-linearity and the consideration of multi-scale spatial factors. To tackle these challenges, this study introduces a novel approach for collaborative multi-site visibility forecasting based on spatiotemporal convolutional networks. Firstly, we preprocess the ERA5 reanalysis dataset and ground observation dataset, standardizing the spatiotemporal dimensions. We employ correlation coefficient analysis to select relevant meteorological factors. Subsequently, we create a spatiotemporal convolutional network model (TCN_GCN), which combines the power of temporal convolutional network (TCN) and graph convolutional network (GCN). Additionally, a weighted loss function is incorporated, accounting for the distribution of visibility values. The model is trained with multi-site data, enabling it to learn spatiotemporal visibility patterns across various sites. This empowers the model to generate multi-site visibility forecasts, thereby significantly improving regional visibility forecasting accuracy. Using 50 meteorological stations in Fujian Province, China, as a case study, we assess the model's predictions using key metrics such as mean absolute error (MAE), root mean square error (RMSE) and coefficient of determination (R2). The experimental results demonstrate that the inclusion of both temporal and spatial features leads to a substantial enhancement in model prediction performance. The TCN_GCN model outperforms other deep learning methods in multi-site visibility forecasting, highlighting its effectiveness and superiority in improving regional visibility forecasting accuracy.","PeriodicalId":49825,"journal":{"name":"Meteorological Applications","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2024-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/met.2206","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142360053","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Detection of land surface albedo changes over Iran using remote sensing data 利用遥感数据探测伊朗陆地表面反照率的变化

IF 2.3 4区地球科学

Meteorological Applications Pub Date : 2024-08-24 DOI: 10.1002/met.2224

Omid Reza Kefayat Motlagh, Mohammad Darand

引用次数: 0

Comparative analysis of satellite and reanalysis data with ground-based observations in Northern Ghana 加纳北部卫星和再分析数据与地面观测数据的比较分析

IF 2.3 4区地球科学

Meteorological Applications Pub Date : 2024-08-19 DOI: 10.1002/met.2226

Josephine Thywill Katsekpor, Klaus Greve, Edmund Ilimoan Yamba, Ebenezer Gyampoh Amoah

{"title":"Comparative analysis of satellite and reanalysis data with ground-based observations in Northern Ghana","authors":"Josephine Thywill Katsekpor, Klaus Greve, Edmund Ilimoan Yamba, Ebenezer Gyampoh Amoah","doi":"10.1002/met.2226","DOIUrl":"https://doi.org/10.1002/met.2226","url":null,"abstract":"Accurate predictions of streamflow and flood events are contingent upon the availability of reliable hydrometeorological data. In regions characterized by scarcity of ground-based hydrometeorological observations, satellite and reanalysis data assume prominence as alternative predictors. Floods and droughts have emerged as a significant concern in Northern Ghana, yet the scarcity of ground-based hydrometeorological data impedes effective prediction of these hydrological events. Consequently, the identification of suitable surrogate hydrometeorological data holds paramount importance in addressing these challenges. This study, therefore, assessed the accuracy of satellite and reanalysis data against ground-based data in Northern Ghana. Rainfall and mean temperature spanning from 1998 to 2019 and soil moisture datasets from 2019 to 2022 were collected from GMet, ISMN (ground-based), CHIRPS, PERSIANN-CDR, ERA5, ARC2, MERRA-2, TRMM and CFSR (satellite and reanalysis). Employing rigorous statistical measures, namely standard deviation, mean absolute error (MAE) and mean bias error (MBE), the accuracy of these datasets was thoroughly evaluated. The results revealed that CHIRPS and PERSIANN-CDR exhibited superior accuracy in rainfall simulation, with CHIRPS demonstrating particularly consistent congruence with observed data. In terms of mean temperature prediction, ERA5 surpassed MERRA-2 and CFSR. Regarding soil moisture assessments, both ERA5 and CFSR offered satisfactory simulations. Hence, our findings advocate for the preference of CHIRPS (for rainfall data), ERA5 (for temperature data) and a combination of CFSR/ERA5 (for soil moisture data) as dependable primary data sources for streamflow modelling, drought analysis, flood prediction and water resource management in the context of Northern Ghana.","PeriodicalId":49825,"journal":{"name":"Meteorological Applications","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2024-08-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/met.2226","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142002549","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

The use of vehicle-based observations in weather prediction and decision support 在天气预测和决策支持中使用基于车辆的观测数据

IF 2.3 4区地球科学

Meteorological Applications Pub Date : 2024-08-14 DOI: 10.1002/met.2225

Amanda R. Siems-Anderson

引用次数: 0

Skilful probabilistic medium-range precipitation and temperature forecasts over Vietnam for the development of a future dengue early warning system 为开发未来登革热预警系统而对越南进行熟练的中程降水和气温概率预报

IF 2.3 4区地球科学

Meteorological Applications Pub Date : 2024-08-07 DOI: 10.1002/met.2222

Lucy Main, Sarah Sparrow, Antje Weisheimer, Matthew Wright

{"title":"Skilful probabilistic medium-range precipitation and temperature forecasts over Vietnam for the development of a future dengue early warning system","authors":"Lucy Main, Sarah Sparrow, Antje Weisheimer, Matthew Wright","doi":"10.1002/met.2222","DOIUrl":"https://doi.org/10.1002/met.2222","url":null,"abstract":"Dengue fever is a source of substantial health burden in Vietnam. Given the well-established influence of temperature and precipitation on vector biology and disease transmission, predictions of meteorological variables, such as those issued by ECMWF as a world-leading provider of global ensemble forecasts, are likely to be valuable model inputs to a future dengue early warning system. In the absence of established verification at municipal and regional scales, this study assesses the skill of rainy season (May–October) ensemble precipitation and 2-m temperature retrospective forecasts over North and South Vietnam initialized for dates during the period 2001–2020, evaluated against the ERA5 reanalysis for the same period. Forecasts are found to be significantly skilful compared with both climatology and persistence for lead times up to 10 days, including for cumulative precipitation values considered against independent rain gauge data. Rank histograms demonstrate that ensembles generally avoid excessive bias and consistently positive CRPSS values indicate substantial skill for temperature and cumulative precipitation forecasts for all spatial scales considered, despite differences in rainy season characteristics between North and South Vietnam. This forecast reliability demonstrates that meteorological input data based on ECMWF ensemble forecasts would add appreciably more value to the development of a future dengue early warning system compared to reference forecasts like climatology or persistence. These results raise hope for further exploration of predictive skill for relevant meteorological variables, particularly focused on their downscaling to produce district-level epidemiological forecasts for urban areas where dengue is most prevalent.","PeriodicalId":49825,"journal":{"name":"Meteorological Applications","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2024-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/met.2222","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141967588","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Distribution of PM10, PM2.5, and NO2 in the Cergy-Pontoise urban area (France) 法国赛尔吉-蓬图瓦兹城区 PM10、PM2.5 和 NO2 的分布情况

IF 2.3 4区地球科学

Meteorological Applications Pub Date : 2024-08-07 DOI: 10.1002/met.2223

Souad Lagmiri, Salem Dahech

{"title":"Distribution of PM10, PM2.5, and NO2 in the Cergy-Pontoise urban area (France)","authors":"Souad Lagmiri, Salem Dahech","doi":"10.1002/met.2223","DOIUrl":"10.1002/met.2223","url":null,"abstract":"This study employed a network comprising 16 fixed “Ecosmart” sensors deployed in the Cergy-Pontoise conurbation. Continuous measurements of PM10, PM2.5, and NO2, significant pollutants in the Paris region, were conducted from April 8 to June 6, 2022. The collected data were represented as statistically composite spatial matrices due to the heterogeneous urban landscape and the overlapping of multiple pollution sources. Temporal variations on a daily basis were influenced by both traffic and meteorological conditions. Daytime, characterized by denser traffic compared to nighttime, exhibited higher concentrations of PM10 and PM2.5. Conversely, NO2 concentration levels displayed two peaks associated with traffic volume, and relatively elevated nocturnal values compared with midday due to atmospheric vertical stability during the nighttime phase. The analysis of weather-type impacts revealed that during unstable weather conditions, elevated particle concentrations stemmed from dust resuspension from the ground and long-range transport. Maximum NO2 concentrations were observed during stable weather conditions, whereas minimum concentrations occurred during unstable weather.","PeriodicalId":49825,"journal":{"name":"Meteorological Applications","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2024-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/met.2223","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141946671","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Utilization of the Google Earth Engine for the evaluation of daily soil temperature derived from Global Land Data Assimilation System in two different depths over a semiarid region 利用谷歌地球引擎评估全球陆地数据同化系统得出的半干旱地区两个不同深度的每日土壤温度

IF 2.3 4区地球科学

Meteorological Applications Pub Date : 2024-07-29 DOI: 10.1002/met.2221

Abolghasem Akbari, Majid Rajabi Jaghargh, Azizan Abu Samah, Jonathan Peter Cox, Mojtaba Gholamzadeh, Alireza Araghi, Patricia M. Saco, Khabat Khosravi

{"title":"Utilization of the Google Earth Engine for the evaluation of daily soil temperature derived from Global Land Data Assimilation System in two different depths over a semiarid region","authors":"Abolghasem Akbari, Majid Rajabi Jaghargh, Azizan Abu Samah, Jonathan Peter Cox, Mojtaba Gholamzadeh, Alireza Araghi, Patricia M. Saco, Khabat Khosravi","doi":"10.1002/met.2221","DOIUrl":"10.1002/met.2221","url":null,"abstract":"The Google Earth Engine (GEE) was used to investigate the performance of the Global Land Data Assimilation System (GLDAS) soil temperature (ST) data against observed ST from 13 synoptic stations over a semiarid region in Iran. Three-hourly ST data were collected and analyzed in two depths (0–10 cm; 40–100 cm) and 5 years. In each depth, GLDAS-Noah ST data were evaluated for daily minimum, maximum, and average ST (i.e., Tmin, Tmax, and Tavg). Based on the correlation coefficient, Kling–Gupta Efficiency, and Nash–Sutcliffe Efficiency the overall performance of the GLDAS-Noah is 0.96, 0.66, and 0.79 for Tmin; 0.97, 0.84, and 0.89 for Tavg; and 0.95, 0.89, and 0.89 for Tmax, respectively in the first layer. Likewise, 0.97, 0.85, and 0.86 for Tmin; 0.97, 0.77, and 0.80 for Tavg; and 0.97, 0.69, and 0.69 for Tmax are obtained in the second layer. However, there is a significant negative bias which tends to underestimate ST in the two investigated layers, given by an average bias over all the stations analyzed of −24%, −12%, and −5% for Tmin, Tavg, and Tmax in the first layer, and average bias of −8%, −13%, and −17% for Tmin, Tavg, and Tmax in the second layer. This study reveals that GLDAS-Noah-derived ST can be used in arid regions where little or no observation data is available. Moreover, GEE performed as an advanced geospatial processing tool in regional scale analysis of ST in different layers.","PeriodicalId":49825,"journal":{"name":"Meteorological Applications","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2024-07-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/met.2221","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141868828","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

What can we learn from nested IoT low-cost sensor networks for air quality? A case study of PM2.5 in Birmingham, UK 我们能从用于空气质量的嵌套式物联网低成本传感器网络中学到什么？英国伯明翰 PM2.5 案例研究

IF 2.3 4区地球科学

Meteorological Applications Pub Date : 2024-07-22 DOI: 10.1002/met.2220

Nicole Cowell, Clarissa Baldo, Lee Chapman, William Bloss, Jian Zhong

{"title":"What can we learn from nested IoT low-cost sensor networks for air quality? A case study of PM2.5 in Birmingham, UK","authors":"Nicole Cowell, Clarissa Baldo, Lee Chapman, William Bloss, Jian Zhong","doi":"10.1002/met.2220","DOIUrl":"10.1002/met.2220","url":null,"abstract":"Low-cost sensing and the Internet of Things (IoT), present new possibilities for unconventional monitoring of environmental parameters. This paper describes a series of intersecting networks of particulate matter sensors that were deployed across the Birmingham conurbation for a 12-month period. The networks consisted of a combination of commercially available sensors and University developed sensors. Data from these networks were assimilated with data from a third-party Zephyr deployment, along with the DEFRA AURN network, which was hosted on an open-source online platform. This nesting of sensor networks allowed for new insights into sensor performance, including the accuracy of a large network to detect regional concentrations and the number of sensors needed for effective monitoring beyond indicative measurements. After comprehensive data validation steps, the sensors were shown to perform well during co-location with reference instrumentation (exhibiting slopes of 0.74–1.3). The sensors demonstrated good capability of detecting temporal patterns of regional PM2.5 with the mean of the entire sensor network recording an annual mean PM2.5 concentration within 0.2 μgm−3 of the regulatory network annual mean observation. Network-derived statistics for estimating urban background concentrations compared to a reference site increase in-line with the number of sensors available, however when assessing this for near-source concentrations the importance of sensor location rather than the number of sensors is highlighted. Overall, the network provided novel insights into local concentrations, detecting similar hotspots to those identified by a high-resolution model. The increased spatial coverage afforded by the sensor network has the potential to support higher resolution evaluation of models and provide unprecedented spatial evidence for air pollution management interventions.","PeriodicalId":49825,"journal":{"name":"Meteorological Applications","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2024-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/met.2220","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141785517","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Severe compound events of low wind and cold temperature for the British power system 英国电力系统遭遇低风低温的严重复合事件

IF 2.3 4区地球科学

Meteorological Applications Pub Date : 2024-07-18 DOI: 10.1002/met.2219

Lucie J. Lücke, Chris J. Dent, Gabriele C. Hegerl, Amy L. Wilson, Andrew P. Schurer

{"title":"Severe compound events of low wind and cold temperature for the British power system","authors":"Lucie J. Lücke, Chris J. Dent, Gabriele C. Hegerl, Amy L. Wilson, Andrew P. Schurer","doi":"10.1002/met.2219","DOIUrl":"https://doi.org/10.1002/met.2219","url":null,"abstract":"Britain's power system has shifted towards a major contribution from wind energy. However, wind is highly variable, and exceptionally low wind events can simultaneously occur with cold conditions, which increase demand. These conditions can pose a threat for the security of energy supply. Here we use bias-corrected wind supply data and the estimated temperature-related part of demand to analyse events of potential weather-related energy shortfall based on the historic meteorological record. We conduct sensitivity studies with varying scenarios of Britain's total wind energy capacity and the temperature sensitivity of national demand. These scenarios are estimates for present-day conditions as well as potential future changes of the power system. We apply a new methodology to estimate the potential severity of an event for the power system, and analyse the atmospheric conditions associated with the most severe events. We find that events of potentially severe shortfall are relatively rare and short-lived, and often occur with an atmospheric pattern broadly resembling a negative North Atlantic Oscillation. This broad tendency emerges from a wide range of individual daily weather patterns that cause cold and still conditions. With an increase in wind capacity, it is likely that severe events will become rarer, although the most severe days of the record are relatively insensitive to changes in wind supply and temperature sensitivity of demand under our assumptions.","PeriodicalId":49825,"journal":{"name":"Meteorological Applications","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2024-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/met.2219","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141730217","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Mitigating against the between-ensemble-member precipitation bias in a lagged sub-seasonal ensemble 减少滞后亚季节集合中集合成员间降水偏差

IF 2.7 4区地球科学

Meteorological Applications Pub Date : 2024-06-14 DOI: 10.1002/met.2197

Marion Mittermaier, Seshagiri Rao Kolusu, Joanne Robbins

{"title":"Mitigating against the between-ensemble-member precipitation bias in a lagged sub-seasonal ensemble","authors":"Marion Mittermaier, Seshagiri Rao Kolusu, Joanne Robbins","doi":"10.1002/met.2197","DOIUrl":"https://doi.org/10.1002/met.2197","url":null,"abstract":"The Met Office GloSea5-GC2 sub-seasonal-to-seasonal 40-member lagged ensemble consists of members who are up to 10 days different in age such that the between-ensemble-member bias is not internally consistent. Reforecasts tend to be used to convert these ensemble forecasts into anomalies from a normal state. These anomalies are however not that useful for applications where individual ensemble members are needed to drive downstream applications in the hazard and impact space. Here we explore whether there is a way of correcting for the within-ensemble bias without using reforecasts. An investigation into the individual daily precipitation distributions from the JJAS 2019 Indian monsoon season, stratified by forecast horizon, highlights how the distribution changes, and shows that the model distribution is markedly different to the observed. Initial results suggest that it could be better to use recent model forecast distribution(s) as the reference for adjusting the model rainfall accumulations as a function of lead day horizon, that is, not attempting to correct the members to a vastly different (observed) distribution shape, but a more subtle shift towards the model's best guess of reality, rather than reality itself, to remove the between-ensemble-member bias. A combination of Exponential and Generalized Pareto distributions are used for parametric quantile mapping to remove this internal ensemble bias using computationally efficient pre-computed lookup tables. Within- and out-of-sample results for the 2019 and 2020 monsoon seasons show that the method is effective in tightening precipitation gradients, with improvements in spread, accuracy and skill, especially for low accumulations.","PeriodicalId":49825,"journal":{"name":"Meteorological Applications","volume":null,"pages":null},"PeriodicalIF":2.7,"publicationDate":"2024-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/met.2197","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141326510","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0