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Atmosphere
Special Issues
Aviation Meteorology: Developments and Latest Achievements
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Aviation Meteorology: Developments and Latest Achievements

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

Deadline for manuscript submissions: 1 January 2026 | Viewed by 1798

Special Issue Editor

Dr. Afaq Khattak

E-Mail Website
Guest Editor
Department of Civil, Structural and Environmental Engineering, Trinity College Dublin, D02 PN40 Dublin, Ireland
Interests: sustainable transportation; AI in transportation; transport policy; transportation systems modeling; aviation meteorology
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

This Special Issue explores the transformative advancements in aviation meteorology, with a particular emphasis on the integration of artificial intelligence (AI) alongside other novel methods and technologies in weather forecasting. Aviation safety and operational efficiency heavily depend on precise and timely weather data, and recent developments in both AI and traditional meteorological techniques are opening new frontiers in this area.

The issue will feature articles that highlight cutting-edge research and practical applications of AI in turbulence forecasting, wind shear detection, and real-time monitoring of hazardous weather conditions, as well as achievements in traditional aviation meteorology. These advances help optimize flight paths, minimize weather-related delays, and improve decision-making processes. In doing so, we aim to foster discussions around enhancing weather prediction accuracy, mitigating weather-related risks, and contributing to safer skies.

By bridging AI-driven innovations and traditional meteorological methods, this Special Issue outlines the future of aviation, focusing on how both AI and other advancements are shaping a safer and more efficient aviation ecosystem.

Dr. Afaq Khattak
Guest Editor

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

  • aviation meteorology
  • artificial intelligence in weather forecasting
  • turbulence prediction
  • wind shear detection
  • real-time weather monitoring
  • aviation safety
  • AI-driven meteorological analysis
  • weather-related risk mitigation
  • predictive analytics in aviation
  • traditional weather forecasting methods

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Further information on MDPI's Special Issue policies can be found here.

Published Papers (2 papers)

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Research

24 pages, 5555 KiB  
Article
A Signal Processing-Guided Deep Learning Framework for Wind Shear Prediction on Airport Runways
by Afaq Khattak, Pak-wai Chan, Feng Chen, Hashem Alyami and Masoud Alajmi
Atmosphere 2025, 16(7), 802; https://doi.org/10.3390/atmos16070802 - 1 Jul 2025
Viewed by 497
Abstract
Wind shear at the Hong Kong International Airport (HKIA) poses a significant safety risk due to terrain-induced airflow disruptions near the runways. Accurate assessment is essential for safeguarding aircraft during take-off and landing, as abrupt changes in wind speed or direction can compromise [...] Read more.
Wind shear at the Hong Kong International Airport (HKIA) poses a significant safety risk due to terrain-induced airflow disruptions near the runways. Accurate assessment is essential for safeguarding aircraft during take-off and landing, as abrupt changes in wind speed or direction can compromise flight stability. This study introduces a hybrid framework for short-term wind shear prediction based on data collected from Doppler LiDAR systems positioned near the central and south runways of the HKIA. These systems provide high-resolution measurements of wind shear magnitude along critical flight paths. To predict wind shear more effectively, the proposed framework integrates a signal processing technique with a deep learning strategy. It begins with optimized variational mode decomposition (OVMD), which decomposes the wind shear time series into intrinsic mode functions (IMFs), each capturing distinct temporal characteristics. These IMFs are then modeled using bidirectional gated recurrent units (BiGRU), with hyperparameters optimized via the Tree-structured Parzen Estimator (TPE). To further enhance prediction accuracy, residual errors are corrected using Extreme Gradient Boosting (XGBoost), which captures discrepancies between the reconstructed signal and actual observations. The resulting OVMD–BiGRU–XGBoost framework exhibits strong predictive performance on testing data, achieving R2 values of 0.729 and 0.926, RMSE values of 0.931 and 0.709, and MAE values of 0.624 and 0.521 for the central and south runways, respectively. Compared with GRUs, LSTM, BiLSTM, and ResNet-based baselines, the proposed framework achieves higher accuracy and a more effective representation of multi-scale temporal dynamics. It contributes to improving short-term wind shear prediction and supports operational planning and safety management in airport environments. Full article
(This article belongs to the Special Issue Aviation Meteorology: Developments and Latest Achievements)
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15 pages, 3497 KiB  
Article
Climate Change Impacts on Maximum Aviation Payloads of Chinese Airports
by Haijun Song, Tinglong Zhang, Jian Zou and Xianbiao Kang
Atmosphere 2025, 16(5), 597; https://doi.org/10.3390/atmos16050597 - 15 May 2025
Viewed by 428
Abstract
This research investigates climate change impacts on the maximum aviation payload capacity across China’s airport network. Through analysis of projections from 30 Coupled Model Intercomparison Project Phase 6 (CMIP6) models under the Shared Socioeconomic Pathway 5-8.5 (SSP5-8.5) scenario, we quantify the temperature and [...] Read more.
This research investigates climate change impacts on the maximum aviation payload capacity across China’s airport network. Through analysis of projections from 30 Coupled Model Intercomparison Project Phase 6 (CMIP6) models under the Shared Socioeconomic Pathway 5-8.5 (SSP5-8.5) scenario, we quantify the temperature and the pressure effects on maximum take-off weight (MTOW) at 184 Chinese airports. The results reveal that all airports experience MTOW reductions by 2081–2100, with high-plateau airports (>2438 m) facing more moderate decreases (−1.25%) than plain airports (<1500 m) (−1.72%). This counterintuitive pattern stems from elevation-dependent pressure compensation: high-altitude regions benefit from significant pressure increases (4.6 hPa) that partially offset temperature-induced density reductions, while lowland areas receive minimal pressure compensation (0.9 hPa). For commercial aircraft, these changes translate to 1.3–2.9 tons of payload reduction for narrow-body aircraft at plain airports. Our findings demonstrate how topography modulates climate impacts on aviation operations, highlighting the need for regionally tailored adaptation strategies with a focus on economically vital lowland hubs. Full article
(This article belongs to the Special Issue Aviation Meteorology: Developments and Latest Achievements)
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