Bad Weather Highlighting: Advanced Visualization of Severe Weather and Support in Air Traffic Control Displays

Ohneiser, Oliver; Kleinert, Matthias; Muth, Kathleen; Gluchshenko, Olga; Ehr, Heiko; Gross, Niklas; Temme, Marco-Michael

doi:10.1109/dasc43569.2019.9081773

Cited by 8 publications

(5 citation statements)

References 17 publications

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“…To test the usability and usefulness of the nowcasts, DLR's "4-Dimensional Cooperative Arrival Manager" AMAN (4D-CARMA) was extended to include Milano-Malpensa Airport [2]. In addition to the airspace structure with the standard approach routes and metering fixes, the local approach procedures had to be implemented for this purpose.…”

Section: Application Of Nowcasting To Air Traffic Controller Supportmentioning

confidence: 99%

“…For instance, Munich airport was affected by thunderstorms on more than 9% of days during the first half of 2018. At Frankfurt/Main airport, 45% of delays in 2010 were caused by adverse weather [2]. In the first half of 2018, weather was responsible for 8.3% of all flight delays in Europe [2].…”

Section: Introductionmentioning

confidence: 99%

“…At Frankfurt/Main airport, 45% of delays in 2010 were caused by adverse weather [2]. In the first half of 2018, weather was responsible for 8.3% of all flight delays in Europe [2]. According to the United States Air Force [3], pilots have two options when they are facing severe thunderstorms: either diverting to the closest unaffected area by traversing the thunderstorms or bypassing them.…”

Section: Introductionmentioning

confidence: 99%

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Application of Severe Weather Nowcasting to Case Studies in Air Traffic Management

et al. 2023

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Effective and time-efficient aircraft assistance and guidance in severe weather environments remains a challenge for air traffic control. Air navigation service providers around the globe could greatly benefit from specific and adapted meteorological information for the controller position, helping to reduce the increased workload induced by adverse weather. The present work proposes a radar-based nowcasting algorithm providing compact meteorological information on convective weather near airports for introduction into the algorithms intended to assist in air-traffic management. The use of vertically integrated liquid density enables extremely rapid identification and short-term prediction of convective regions that should not be traversed by aircraft, which is an essential requirement for use in tactical controller support systems. The proposed tracking and nowcasting method facilitates the anticipation of the meteorological situation around an airport. Nowcasts of centroid locations of various approaching thunderstorms were compared with corresponding radar data, and centroid distances between nowcasted and observed storms were computed. The results were analyzed with Method for the Object-Based Evaluation from the Model Evaluation tools software (MET-10.0.1, Developmental Testbed Center, Boulder, CO, US) and later integrated into an assistance arrival manager software, showing the potential of this approach for automatic air traffic assistance in adverse weather scenarios.

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Section: Application Of Nowcasting To Air Traffic Controller Supportmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Application of Severe Weather Nowcasting to Case Studies in Air Traffic Management

et al. 2023

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“…Accurately assessing the impact of weather on air traffic and making corresponding air traffic flow management strategies are long-term research hotspots and bottlenecks for scholars in this field [1]. Most of the existing researches converted the weather influence into airspace operation capacity after indexing, and then directly applied it to the traditional flow management decision model based on the balance of capacity and demand, and got the decision result [2]. This type of method was relatively simple to apply and can avoid processing high-dimensional data.…”

Section: Introductionmentioning

confidence: 99%

Study on Recognition Method of Similar Weather Scenes in Terminal Area

Ligang¹,

Jin²,

Xu³

et al. 2023

Computer Systems Science and Engineering

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Weather is a key factor affecting the control of air traffic. Accurate recognition and classification of similar weather scenes in the terminal area is helpful for rapid decision-making in air traffic flow management. Current researches mostly use traditional machine learning methods to extract features of weather scenes, and clustering algorithms to divide similar scenes. Inspired by the excellent performance of deep learning in image recognition, this paper proposes a terminal area similar weather scene classification method based on improved deep convolution embedded clustering (IDCEC), which uses the combination of the encoding layer and the decoding layer to reduce the dimensionality of the weather image, retaining useful information to the greatest extent, and then uses the combination of the pre-trained encoding layer and the clustering layer to train the clustering model of the similar scenes in the terminal area. Finally, terminal area of Guangzhou Airport is selected as the research object, the method proposed in this article is used to classify historical weather data in similar scenes, and the performance is compared with other state-of-the-art methods. The experimental results show that the proposed IDCEC method can identify similar scenes more accurately based on the spatial distribution characteristics and severity of weather; at the same time, compared with the actual flight volume in the Guangzhou terminal area, IDCEC's recognition results of similar weather scenes are consistent with the recognition of experts in the field.

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“…Meteorological information shall be provided to the air traffic controller from the meteorological services or from the airplanes themselves, which are equipped with special equipment to record meteorological phenomena, such as cumulonimbus clouds, in front of the aircraft. However, air traffic controllers themselves do not directly have the ability to see cumulonimbus clouds on their screens in controlled traffic based on pilot reports (Ohneiser et al, 2019). In the event of heavy air traffic, it may be difficult to organize the flow of aircraft smoothly, as they will be required to obtain a permit if they are asked to change their trajectory due to the cloud, and this may disrupt the original organization of air traffic.…”

Section: Introductionmentioning

confidence: 99%

Application of Software, Representing Cumulonimbus Clouds, in Air Traffic Control

Derenčius

Ragauskas

2022

Science - Future of Lithuania

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In this paper we attempt to answer the question of whether the display of cumulonimbus clouds on air traffic controller radar screens has a significant impact on air traffic control. The developed cumulonimbus cloud mapping simulator allowed the study to be performed by performing simulations with a flight control simulator. This allowed an assessment of how the air traffic controller makes decisions when cumulonimbus is displayed and when it is not. The benefits of cumulonimbus imaging for aircraft trajectories and flight time were also assessed. The research was conducted in the space of Vilnius terminal manoeuvring area.

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Bad Weather Highlighting: Advanced Visualization of Severe Weather and Support in Air Traffic Control Displays

Cited by 8 publications

References 17 publications

Application of Severe Weather Nowcasting to Case Studies in Air Traffic Management

Application of Severe Weather Nowcasting to Case Studies in Air Traffic Management

Study on Recognition Method of Similar Weather Scenes in Terminal Area

Application of Software, Representing Cumulonimbus Clouds, in Air Traffic Control

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