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Atmosphere
Special Issues
Meteorological Issues for Low-Altitude Economy
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Meteorological Issues for Low-Altitude Economy

A special issue of Atmosphere (ISSN 2073-4433). This special issue belongs to the section "Atmospheric Techniques, Instruments, and Modeling".

Deadline for manuscript submissions: 30 June 2026 | Viewed by 2464

Special Issue Editors

Dr. Yongjing Ma

E-Mail Website
Guest Editor
Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China
Interests: atmospheric boundary layer; Doppler wind lidar; large-eddy simulation; turbulent flows; machine learning
Special Issues, Collections and Topics in MDPI journals
Dr. Chongshui Gong

E-Mail
Guest Editor
Institute of Arid Meteorology, China Meteorological Administration, Lanzhou 730030, China
Interests: boundary-layer data assimilation; LES-EnKF integration; machine learning; high-resolution numerical simulation
Special Issues, Collections and Topics in MDPI journals
Dr. Dandan Zhao

E-Mail Website
Guest Editor
Institute of Aeronautical Meteorology, Civil Aviation Flight University of China, Guanghan 618307, China
Interests: atmospheric boundary layer; large-eddy simulation; wind shear; wind power

Special Issue Information

Dear Colleagues,

The low-altitude economy (typically referring to economic activities within the airspace from the ground to around 1000–2000 meters) is reshaping the future industrial ecosystem at an unprecedented pace. The explosive growth of emerging sectors such as drone logistics, urban air mobility (UAM), precision agricultural aviation, and low-altitude tourism is expected to produce a global market size of over CNY one trillion by 2030. However, this sustainable development is highly dependent on a deep understanding and precise forecasting of low-altitude meteorology, especially for the atmospheric boundary layer dynamic field.

This Special Issue of Atmosphere aims to cover papers related to all aspects of new and advanced meteorological techniques that can be applied for the development of the low-altitude economy, such as wind LiDAR remote sensing, the high-resolution modeling of complex-terrain dynamics, UAV measurements, and machine learning.

Dr. Yongjing Ma
Dr. Chongshui Gong
Dr. Dandan Zhao
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 250 words) can be sent to the Editorial Office for assessment.

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

  • atmospheric boundary layer dynamics
  • low-altitude economy
  • high-resolution wind prediction
  • turbulent motions
  • wind shear
  • machine learning

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Published Papers (4 papers)

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16 pages, 6421 KB  
Article
Evaluation of Wind Field for ERA5 Reanalysis Data in Offshore East China Sea
by Yibo Yuan, Yining Ma, Li Dai, Yuxin Zang, Keteng Ke and Xiaoxiang Huang
Atmosphere 2026, 17(3), 310; https://doi.org/10.3390/atmos17030310 - 18 Mar 2026
Viewed by 81
Abstract
This study evaluates the applicability of ERA5 wind speed (WS) and wind direction (WD) in the East China Sea, using high-resolution vertical wind profiles measured by a floating LiDAR at the Shanghai Nanhui Offshore Wind Farm from 15 January 2022 to 15 January [...] Read more.
This study evaluates the applicability of ERA5 wind speed (WS) and wind direction (WD) in the East China Sea, using high-resolution vertical wind profiles measured by a floating LiDAR at the Shanghai Nanhui Offshore Wind Farm from 15 January 2022 to 15 January 2023. Key findings are as follows: (1) Strong positive correlations exist between LiDAR-measured and ERA5 WS across all evaluated heights, with correlation coefficients of 0.76 (ground level), 0.86 (50 m), 0.88 (100 m), and 0.90 (200 m), respectively, and corresponding root mean square errors (RMSEs) of 2.33 m/s, 1.78 m/s, 1.73 m/s, and 1.77 m/s. This systematic improvement in correlation and modest reduction in RMSE with increasing height indicate that ERA5 captures vertical wind structure with progressively higher fidelity above the surface layer. (2) Both the ERA5 dataset and LiDAR measurements consistently show dominant wind frequencies in the NNE and SSE directions, with peaks at approximately 1000 occurrences. The minimal differences in the two datasets demonstrate the ERA5’s robust representation of near-surface offshore WD climatology. (3) The ERA5 reanalysis data of typhoon Muifa can better illustrate the increase in the initial WS and its subsequent decreases. However, the peak WS lags behind measurements by 2 h, and the extreme WS is significantly lower than that measured. Evaluations of the multi-year return period WS demonstrate an underestimation of extreme WS by 16.06–16.51% for the ERA5 data. Regarding the WD, the measured direction is clockwise, while that of the ERA5 is counterclockwise, revealing a fundamental deficiency in its representation of mesoscale cyclonic wind structure. Therefore, ERA5 reanalysis data provides reliable characterization of typical offshore WS and WD within the operational wind turbine hub-height range (100–200 m). For typhoon-related wind engineering assessments, the applicability of ERA5 data necessitates caution and potentially bias correction. Full article
(This article belongs to the Special Issue Meteorological Issues for Low-Altitude Economy)
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21 pages, 9784 KB  
Article
Low-Level Wind Shear Characteristics in the Qinghai-Tibet Plateau by Long-Term Wind Lidar Observations and the Improved Algorithm
by Huiyu Ding, Dandan Zhao, Lian Duan, Junjie Wu, Wenjun Sang, Guangjing Liu, Tianyi Wang, Shaoqing Zhang and Yaohui Li
Atmosphere 2026, 17(1), 6; https://doi.org/10.3390/atmos17010006 - 22 Dec 2025
Viewed by 499
Abstract
The complex terrain of the Qinghai–Tibetan Plateau (QTP) makes low-level wind shear (LLWS) detection challenging. Using May–September 2023 high-resolution Doppler Wind Lidar (DWL) observations, this study analyzed the spatiotemporal characteristics of LLWS and proposed an optimized detection algorithm. A key novelty of this [...] Read more.
The complex terrain of the Qinghai–Tibetan Plateau (QTP) makes low-level wind shear (LLWS) detection challenging. Using May–September 2023 high-resolution Doppler Wind Lidar (DWL) observations, this study analyzed the spatiotemporal characteristics of LLWS and proposed an optimized detection algorithm. A key novelty of this work lies in the development of a hybrid physical–statistical detection scheme that combines horizontal divergence with logistic regression to dynamically modulate the shear field. This approach effectively reduces noise-induced false alarms in complex plateau terrain. The results show that LLWS occurred mainly near the surface at night in June, while in September it appeared more frequently during daytime throughout the boundary layer. Horizontally, the dominant directions of LLWS shifted seasonally from northwest and west in June to south and east in September. The proposed optimization method effectively suppressed false alarms, reducing moderate and strong LLWS frequencies by 30–40%. In June, optimization significantly reduced spurious detections of LLWS in the northeast and southwest. The frequency of LLWS in the northeast direction was reduced by up to 0.03. In September, scattered shear was removed and strong shear became more organized in the southeast, while southwest shear frequency decreased by up to 0.04, confirming LLWS patterns and method effectiveness. Full article
(This article belongs to the Special Issue Meteorological Issues for Low-Altitude Economy)
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17 pages, 5835 KB  
Article
Evaluation of Aircraft Cloud Seeding for Ecological Restoration in the Shiyang River Basin Using Remote Sensing
by Wei Wang, Mei Zhang and Linfei Ma
Atmosphere 2025, 16(12), 1344; https://doi.org/10.3390/atmos16121344 - 27 Nov 2025
Viewed by 648
Abstract
The use of aircraft for cloud seeding to enhance rainfall serves as an effective meteorological intervention and plays a vital role in ensuring ecological security within the context of the low-altitude economy. This study utilized ground-based precipitation observations from the Shiyang River Basin, [...] Read more.
The use of aircraft for cloud seeding to enhance rainfall serves as an effective meteorological intervention and plays a vital role in ensuring ecological security within the context of the low-altitude economy. This study utilized ground-based precipitation observations from the Shiyang River Basin, in conjunction with Landsat satellite remote sensing imagery (2000–2024), regional historical regression, vegetation index retrieval, and spectral mixture analysis, to evaluate the effectiveness of aircraft-based cloud seeding for enhancing rainfall. The normalized difference vegetation index and the fraction of vegetation cover were calculated to examine the spatiotemporal dynamics and growth patterns of surface vegetation before and after the implementation of this rainfall enhancement measure, thus offering a quantitative assessment of the ecological restoration effect in the Shiyang River Basin. A novel application of cloud-seeding technology for ecological recovery has been developed. It provides one of the first quantitative assessments of aircraft-based cloud seeding in inland river basins of China, linking meteorological intervention directly to measurable ecological restoration outcomes. The findings indicate that: (1) Aircraft-based cloud seeding for rainfall enhancement has yielded significant results, with an average relative precipitation increase of 20.8% (p < 0.1%) in the operational area; (2) Following the commencement of this rainfall enhancement practice in 2010, normalized difference vegetation index and fraction of vegetation cover values within the study area have shown a marked increase, with the percentage of regions with low vegetation coverage declining from 30.36% to 25.21%; and (3) Since the implementation of this measure in 2010, vegetation conditions in the Shiyang River Basin have generally stabilized, demonstrating substantial improvement and a reduction in degradation. The percentage of regions classified as improved or slightly improved increased significantly, from 14.20% before the implementation of this measure to 36.24%, indicating a transition in the vegetation ecosystem from localized enhancement to overall improvement. These results demonstrate that ecological restoration efforts in the Shiyang River Basin have shown considerable improvement after the introduction of aircraft-based cloud-seeding operations, resulting in significant increases in vegetation coverage throughout extensive regions of the basin. The research connects scientific results to policy and management, suggesting that low-altitude economy-based cloud seeding can play a key role in water resource management, ecological stability, and climate resilience. Full article
(This article belongs to the Special Issue Meteorological Issues for Low-Altitude Economy)
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18 pages, 4864 KB  
Technical Note
A Pilot Study on Meteorological Support for the Low-Altitude Economy—Consistency of Meteorological Measurements on UAS with Numerical Simulation Results
by Ming Chun Lam, Wai Hung Leung, Ka Wai Lo, Kai Kwong Lai, Pak Wai Chan, Jun Yi He and Qiu Sheng Li
Atmosphere 2026, 17(1), 107; https://doi.org/10.3390/atmos17010107 - 20 Jan 2026
Viewed by 870
Abstract
Meteorological measurements from Unmanned Aircraft Systems (UASs) increase the volume of observations available for validating and improving high-spatiotemporal-resolution models. Accurate model forecasts for UAS operations are essential to the successful development of the low-altitude economy (LAE). In this study, two UAS test flights [...] Read more.
Meteorological measurements from Unmanned Aircraft Systems (UASs) increase the volume of observations available for validating and improving high-spatiotemporal-resolution models. Accurate model forecasts for UAS operations are essential to the successful development of the low-altitude economy (LAE). In this study, two UAS test flights were analyzed to assess the consistency between UAS measurements and Regional Atmospheric Modeling System model outputs, thereby evaluating model forecast skill. UAS measurements were compared with ground-based anemometer and radiosonde observations to meet the World Meteorological Organization observational requirements at both the Threshold and Goal levels. Model-forecast turbulence exhibited strong agreement with atmospheric turbulence derived from high-frequency UAS wind data. The numerical weather prediction model at high spatial and temporal resolution is found to have sufficiently accurate forecasts to support UAS operation. A computational fluid dynamics model was also tested for high-resolution wind and turbulence forecasting; however, it did not yield improvements over the meteorological model. This work represents the first study of its kind for LAE applications in Hong Kong, and further statistical analyses are planned. Full article
(This article belongs to the Special Issue Meteorological Issues for Low-Altitude Economy)
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