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Atmosphere
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Advance in Transportation Meteorology (2nd Edition)
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Advance in Transportation Meteorology (2nd Edition)

A special issue of Atmosphere (ISSN 2073-4433). This special issue belongs to the section "Meteorology".

Deadline for manuscript submissions: 20 January 2025 | Viewed by 5484

Special Issue Editors

Prof. Dr. Duanyang Liu

E-Mail Website
Guest Editor
Key Laboratory of Transportation Meteorology of CMA, Nanjing Joint Institute for Atmospheric Sciences, Nanjing 210041, China
Interests: transportation meteorology; low visibility; transportation meteorological observation; transportation meteorology service; fog
Special Issues, Collections and Topics in MDPI journals
Dr. Hongbin Wang

E-Mail Website
Guest Editor
Key Laboratory of Transportation Meteorology of CMA, Nanjing Joint Institute for Atmospheric Sciences, Nanjing 21041, China
Interests: fog; remote sensing; transportation interruption and weather; transportation meteorological observation
Special Issues, Collections and Topics in MDPI journals
Dr. Shoupeng Zhu

E-Mail Website
Guest Editor
Key Laboratory of Transportation Meteorology of CMA, Nanjing Joint Institute for Atmospheric Sciences, Nanjing 21041, China
Interests: transportation meteorology; meteorological extremes; numerical model forecast; model output application; statistical postprocessing; transportation meteorological forecast method; Meteorology and transportation economics
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

This Special Issue is a follow-up to the first Special Issue entitled “Advances in Transportation Meteorology” (https://www.mdpi.com/journal/atmosphere/special_issues/Transportation_Meteorology) published in Atmosphere in 2023.

Transportation is one of the most crucial aspects across the world, supporting the daily life of human beings and the sustainable development of the whole society. Generally, meteorology causes various impacts on the transportation operation, safety and efficiency. In the context of global warming, increasing numbers of extreme weather and climate events (such as fog, icy roads, and extreme winds) have been detected worldwide and are expected to occur more frequently in the future. Meanwhile, extreme events such as dense fog, rainstorm and blizzard tend to damage the transportation and the traffic facilities (such as express ways, port, airport, and high speed railway) and induce serious traffic blocks and accidents.

In recent decades, concentrated and continuous efforts have been made to carry out meteorological analyses regardless of the urban traffic or transportation conditions, including those of highways, shipping, aviation, etc. A number of methods and techniques have been intensively developed to promote the qualities of both observations and forecasts. More recently, state-of-the-art machine learning frameworks have also been widely introduced into studies regarding transportation meteorology and many other fields.

The current Special Issue seeks original reviews and papers encompassing all aspects related to the abovementioned topics, from observations, forecast method, formation mechanism to influence analysis of transportation meteorology and linked extreme events, aiming to explore the well-established but rapidly growing field of transportation meteorology and to prevent and reduce the associated hazards more sufficiently.

Prof. Dr. Duanyang Liu
Dr. Hongbin Wang
Dr. Shoupeng Zhu
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Atmosphere is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • transportation meteorology
  • maritime meteorology
  • aviation meteorology
  • transportation safety
  • high impact weather on transportation
  • transportation meteorology service
  • transportation meteorological observation method
  • transportation meteorological forecast method
  • meteorology and transportation economics
  • transportation meteorological disaster
  • road surface temperature
  • low visibility
  • wind shear
  • fog

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Published Papers (5 papers)

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Research

20 pages, 9945 KiB  
Article
Analysis of the Meteorological Conditions and Atmospheric Numerical Simulation of an Aircraft Icing Accident
by Haoya Liu, Shurui Peng, Rong Fang, Yaohui Li, Lian Duan, Ten Wang, Chengyan Mao and Zisheng Lin
Atmosphere 2024, 15(10), 1222; https://doi.org/10.3390/atmos15101222 - 14 Oct 2024
Viewed by 737
Abstract
With the rapid development of the general aviation industry in China, the influence of high-impact aeronautical weather events, such as aircraft icing, on flight safety has become more and more prominent. On 1 March 2021, an aircraft conducting weather modification operations crashed over [...] Read more.
With the rapid development of the general aviation industry in China, the influence of high-impact aeronautical weather events, such as aircraft icing, on flight safety has become more and more prominent. On 1 March 2021, an aircraft conducting weather modification operations crashed over Ji’an City, due to severe icing. Using multi-source meteorological observations and atmospheric numerical simulations, we analyzed the meteorological causes of this icing accident. The results indicate that a cold front formed in northwestern China and then moved southward, which is the main weather system in the icing area. Based on the icing index, we conducted an analysis of the temperature, relative humidity, cloud liquid water path, effective particle radius, and vertical flow field, it was found that aircraft icing occurred behind the ground front, where warm-moist airflows rose along the front to result in a rapid increase of water vapor in 600–500 hPa. The increase of water vapor, in conjunction with low temperature, led to the formation of a cold stratiform cloud system. In this cloud system, there were a large number of large cloud droplets. In addition, the frontal inversion increased the atmospheric stability, allowing cloud droplets to accumulate in the low-temperature region and forming meteorological conditions conducive to icing. The Weather Research and Forecasting model was employed to provide a detailed description of the formation process of the atmospheric conditions conducive to icing, such as the uplifting motion along the front and supercooled water. Based on a real case, we investigated the formation process of icing-inducing meteorological conditions under the influence of a front in detail in this study and verified the capability of a numerical model to simulate the meteorological environment of frontal icing, in order to provide a valuable reference for meteorological early warnings and forecasts for general aviation. Full article
(This article belongs to the Special Issue Advance in Transportation Meteorology (2nd Edition))
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19 pages, 5918 KiB  
Article
Identification of Urban Ventilation Corridor System Using Meteorology and GIS Technology: A Case Study in Zhengzhou, China
by Pan Pan, Fengxiu Li, Yeyu Zhu, Pengpeng Xu, Yulong Shang and Rongwei Liao
Atmosphere 2024, 15(9), 1034; https://doi.org/10.3390/atmos15091034 - 27 Aug 2024
Viewed by 810
Abstract
Urban ventilation corridors are designed to enhance air quality, alleviate urban thermal conditions, reduce pollution and energy consumption, as well as improve human comfort within cities. They play a pivotal role in mitigating environmental impacts, particularly in densely populated urban areas. Based on [...] Read more.
Urban ventilation corridors are designed to enhance air quality, alleviate urban thermal conditions, reduce pollution and energy consumption, as well as improve human comfort within cities. They play a pivotal role in mitigating environmental impacts, particularly in densely populated urban areas. Based on satellite remote sensing data, meteorological observations, basic geographic information of Zhengzhou City and its surroundings, and urban planning data, we analyzed the urban wind environment, urban heat island, ecological cold sources, and ventilation potential. The findings reveal several key insights: (1) Dominant winds in Zhengzhou City predominantly originate from the northwest, northeast, and south, influenced by topography and the monsoon climate, with seasonal variations. These wind patterns are crucial considerations for designing primary ventilation corridors. (2) The urban heat island exhibits a polycentric spatial distribution, with intensity decreasing from the city center towards the periphery. Ecological cold sources, primarily situated in the city outskirts, act as reservoirs of fresh air that mitigate the urban heat island effect through designated corridors. (3) A preliminary corridor system, termed “eight primary and thirteen secondary corridors”, is proposed for Zhengzhou City based on an integrated assessment of ventilation potential, urban surface roughness, and sky view factor. This research contributes to advancing the understanding of urban ventilation systems and provides practical insights for policymakers, urban planners, and researchers seeking sustainable solutions to mitigate climate impacts in rapidly urbanizing environments in the region. Full article
(This article belongs to the Special Issue Advance in Transportation Meteorology (2nd Edition))
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16 pages, 18889 KiB  
Article
Improvement in the Forecasting of Low Visibility over Guizhou, China, Based on a Multi-Variable Deep Learning Model
by Dongpo He, Yuetong Wang, Yuanzhi Tang, Dexuan Kong, Jing Yang, Wenyu Zhou, Haishan Li and Fen Wang
Atmosphere 2024, 15(7), 752; https://doi.org/10.3390/atmos15070752 - 24 Jun 2024
Viewed by 743
Abstract
High-quality visibility forecasting benefits traffic transportation safety, public services, and tourism. For a more accurate forecast of the visibility in the Guizhou region of China, we constructed several visibility forecasting models via progressive refinements in different compositions of input observational variables and the [...] Read more.
High-quality visibility forecasting benefits traffic transportation safety, public services, and tourism. For a more accurate forecast of the visibility in the Guizhou region of China, we constructed several visibility forecasting models via progressive refinements in different compositions of input observational variables and the adoption of the Unet architecture to perform hourly visibility forecasts with lead times ranging from 0 to 72 h over Guizhou, China. Three Unet-based visibility forecasting models were constructed according to different inputs of meteorological variables. The model training via multiple observational variables and visibility forecasts of a high-spatiotemporal-resolution numerical weather prediction model (China Meteorological Administration, Guangdong, CMA-GD) produced a higher threat score (TS), which led to substantial improvements for different thresholds of visibility compared to CMA-GD. However, the Unet-based models had a larger bias score (BS) than the CMA-GD model. By introducing the U2net architecture, there was a further improvement in the TS of the model by approximately a factor of two compared to the Unet model, along with a significant reduction in the BS, which enhanced the stability of the model forecast. In particular, the U2net-based model performed the best in terms of the TS below the visibility threshold of 200 m, with a more than eightfold increase over the CMA-GD model. Furthermore, the U2net-based model had some improvements in the TS, BS, and RMSE (root-mean-square error) compared to the LSTM_Attention model. The spatial distribution of the TS showed that the U2net-based model performed better at the model grid scale of 3 km than at the scale of individual weather stations. In summary, the visibility forecasting model based on the U2net algorithm, multiple observational variables, and visibility data from the CMA-GD model performed the best. The compositions of input observational variables were the key factor in improving the deep learning model’s forecasting capability, and these improvements could improve the value of forecasts and support the socioeconomic needs of sectors reliant on visibility forecasting. Full article
(This article belongs to the Special Issue Advance in Transportation Meteorology (2nd Edition))
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16 pages, 3809 KiB  
Article
Exploring the Spatio-Temporal Trends of Geomorphological Incidents Induced by Precipitation on Chinese Highways
by Jie Zhang, Hua Tian and Jianyang Song
Atmosphere 2024, 15(4), 391; https://doi.org/10.3390/atmos15040391 - 22 Mar 2024
Viewed by 882
Abstract
The spatiotemporal distribution of geomorphological incidents was examined in the present study, including the characteristics of obstruction distances and durations, by utilizing nationwide incident mitigation data and precipitation observation records from the period spanning 2019 to 2022. By comparing rainfall features over different [...] Read more.
The spatiotemporal distribution of geomorphological incidents was examined in the present study, including the characteristics of obstruction distances and durations, by utilizing nationwide incident mitigation data and precipitation observation records from the period spanning 2019 to 2022. By comparing rainfall features over different temporal scales across various regions, the aim of the present study was to enhance the current comprehension of the patterns through which regional precipitation initiates incidents on highways by comparing rainfall characteristics over distinct temporal scales across diverse geographical areas. The findings indicate that: (1) The spatial distribution of highway incidents in China is significantly correlated with regional natural environments, predominantly concentrated in the southern parts of the country’s second and third topographical terraces. The temporal distribution closely aligns with annual and monthly precipitation patterns, with the majority of occurrences taking place from June to September. Further, notable disparities in the distribution of highway-related incidents were observed among counties across most provinces; (2) National highways experience a notably higher frequency of incidents than expressways and provincial roads, with most obstruction lengths concentrated within 1 km and durations predominantly under 3 days; (3) The probability of daily rainfall inducing highway incidents is distinctly higher than that of short-duration rainfall, with eastern and southern China experiencing significantly greater inducing precipitation volumes than other regions. The majority of areas are susceptible to incidents within a 3-day window following heavy rainfall or within 24 h after intense short-duration rainfall. Moreover, it is observed that incidents are more closely associated with extreme precipitation occurring within a single day; (4) There is a certain lag between the timing of incidents and the occurrence of extreme short-duration heavy rainfall, with the highest frequency of incidents coinciding with continuous rainfall periods of 3 to 6 days. Full article
(This article belongs to the Special Issue Advance in Transportation Meteorology (2nd Edition))
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21 pages, 8362 KiB  
Article
Assessment of Crosswind Speed over the Runway Glide Path Using an Interpretable Local Cascade Ensemble Approach Aided by Wind Tunnel Experiments
by Afaq Khattak, Jianping Zhang, Pak-Wai Chan, Feng Chen and Hamad Almujibah
Atmosphere 2023, 14(10), 1561; https://doi.org/10.3390/atmos14101561 - 13 Oct 2023
Viewed by 1184
Abstract
The close proximity of crosswinds to airport runways presents great hazards to landing operations. As a result, an aircraft is susceptible to encountering a loss of control. Elevated levels of turbulence are commonly linked with strong crosswind speeds over the runway glide path. [...] Read more.
The close proximity of crosswinds to airport runways presents great hazards to landing operations. As a result, an aircraft is susceptible to encountering a loss of control. Elevated levels of turbulence are commonly linked with strong crosswind speeds over the runway glide path. Therefore, it is imperative to evaluate the factors that impact crosswind speeds. The susceptibility of the runways at Hong Kong International Airport (HKIA) to severe crosswinds is well established. This study aimed to build a scaled model of HKIA, along with its surrounding terrain/buildings, within a TJ-3 ABL wind tunnel to compute the crosswind speeds under different wind directions over the runway glide path. Subsequently, utilizing the outcomes of the experiment, a cutting-edge local cascade ensemble (LCE) model was employed in conjunction with a tree-structured Parzen estimator (TPE) to evaluate the crosswind speed over the north runway glide path. The comparative analysis of the TPE-LCE model was also conducted with other machine learning models. The TPE-LCE model demonstrated superior predictive capabilities in comparison to alternative models, as assessed by MAE (0.490), MSE (0.381), RMSE (0.617), and R2 (0.855). The SHAP analysis, which utilized TPE-LCE predictions, revealed that two factors, specifically “Effect of Terrain/Buildings” and “Distance from Runway,” exhibiting noteworthy influence over the probability of encountering elevated crosswind speeds over the runway glide path. The optimal conditions for high-crosswind speeds were found to be characterized by the absence of nearby terrain features or structures, a smaller distance from HKIA’s north runway threshold, and with a wind direction ranging from 125 to 180 degrees. Full article
(This article belongs to the Special Issue Advance in Transportation Meteorology (2nd Edition))
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