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Atmosphere
Special Issues
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: 15 August 2024 | Viewed by 1916

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

Published Papers (2 papers)

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Research

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 571
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 776
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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