Air Traffic Decision Analysis During Convective Weather Events in Arrival Airspace

2012 ◽  
Author(s):  
Scot Campbell ◽  
Michael Matthews ◽  
Richard Delaura
Keyword(s):  
Decision Analysis ◽  
Air Traffic ◽  
Weather Events ◽  
Convective Weather

How to Evaluate Remote Tower Metrics in Connection With Weather Observations

2018 ◽  
Vol 8 (2) ◽  
pp. 100-111 ◽  
Author(s):  
Maik Friedrich ◽  
Christoph Möhlenbrink
Keyword(s):  
Traffic Control ◽  
Air Traffic Control ◽  
Influential Factors ◽  
Air Traffic ◽  
Weather Event ◽  
Evaluation Of Performance ◽  
Weather Events ◽  
Weather Observations ◽  
Validation Experiment ◽  
Remote Controller

Abstract. Owing to the different approaches for remote tower operation, a standardized set of indicators is needed to evaluate the technical implementations at a task performance level. One of the most influential factors for air traffic control is weather. This article describes the influence of weather metrics on remote tower operations and how to validate them against each other. Weather metrics are essential to the evaluation of different remote controller working positions. Therefore, weather metrics were identified as part of a validation at the Erfurt-Weimar Airport. Air traffic control officers observed weather events at the tower control working position and the remote control working position. The eight participating air traffic control officers answered time-synchronized questionnaires at both workplaces. The questionnaires addressed operationally relevant weather events in the aerodrome. The validation experiment targeted the air traffic control officer’s ability to categorize and judge the same weather event at different workplaces. The results show the potential of standardized indicators for the evaluation of performance and the importance of weather metrics in relation to other evaluation metrics.

En Route Flight Time Prediction Under Convective Weather Events

2018 ◽  
Author(s):  
Guodong Zhu ◽  
Chris Matthews ◽  
Peng Wei ◽  
Matt Lorch ◽  
Subhashish Chakravarty
Keyword(s):  
Flight Time ◽  
Time Prediction ◽  
Weather Events ◽  
Convective Weather

Development of a Probabilistic Convective Weather Forecast Threshold Parameter for Flight-Routing Decisions

2013 ◽  
Vol 28 (5) ◽  
pp. 1175-1187 ◽  
Author(s):  
Kapil Sheth ◽  
Thomas Amis ◽  
Sebastian Gutierrez-Nolasco ◽  
Banavar Sridhar ◽  
Daniel Mulfinger
Keyword(s):  
Traffic Control ◽  
Weather Forecast ◽  
Threshold Value ◽  
Air Traffic ◽  
Weather Data ◽  
Traffic Data ◽  
Threshold Parameter ◽  
Probability Threshold ◽  
Convective Cells ◽  
Convective Weather

Abstract This paper presents a method for determining a threshold value of probabilistic convective weather forecast data. By synchronizing air traffic data and an experimental probabilistic convective weather forecast product, it was observed that aircraft avoid areas of specific forecasted probability. Both intensity and echo top of the forecasted weather were synchronized with air traffic data to derive the probability threshold parameter. This value can be used by dispatchers for flight planning and by air traffic managers to reroute streams of aircraft around convective cells. The main contribution of this paper is to provide a method to compute the probability threshold parameters using a specific experimental probabilistic convective forecast product providing hourly guidance up to 6 h. Air traffic and weather data for a 4-month period during the summer of 2007 were used to compute the parameters for the continental United States. The results are shown for different altitudes, times of day, aircraft types, and airspace users. Threshold values for each of the 20 Air Route Traffic Control Centers were also computed. Additional details are presented for seven high-altitude sectors in the Fort Worth, Texas, center. For the analysis reported here, flight intent was not considered and no assessment of flight deviation was conducted since only aircraft tracks were used.

Predicting Convective Storm Characteristics using Machine Learning from Hi-Resolution NWP Forecasts

2021 ◽  
Author(s):  
Aniel Jardines
Keyword(s):  
Machine Learning ◽  
Weather Forecasting ◽  
Binary Classification ◽  
Air Traffic ◽  
Mitigation Strategies ◽  
Supervised Machine Learning ◽  
Machine Learning Techniques ◽  
Traffic Flow Management ◽  
Storm Characteristics ◽  
Convective Weather

<p>Convective weather represents a significant disruption to air traffic flow management (ATFM) operations. Thunderstorms are the cause for a substantial amount of delay in both the en-route and airport environment. Before the day of operations, poor prediction capability of convective weather prohibits traffic managers from considering weather mitigation strategies during the pre-tactical phase of ATFM planning. As a result, convective weather is mitigated tactically, possibly leading to excessive delays.  </p><p>The skill of weather forecasting has greatly improved in recent years. Hi-resolution weather models can predict the future state of the atmosphere for some weather parameters. However, incorporating the output from these sophisticated weather products into an ATFM solution that provides easily interpreted information by the air traffic managers remains a challenge. </p><p>This paper combines data from high-resolution numerical weather predictions with actual storm observations from lightning detecting and satellite images. It applies supervised machine learning techniques such as binary classification, multiclass classification, and regression to train neural networks to predict the occurrence, severity, and altitude of thunderstorms. The model predictions are given up to 36hr in advance, within timeframes necessary for pre-tactical planning of ATFM, providing traffic managers with valuable information for developing weather mitigation plans. </p>

scholarly journals Weather Impact on Airport Performance

Aerospace ◽  
2018 ◽  
Vol 5 (4) ◽  
pp. 109 ◽  
Author(s):  
Michael Schultz ◽  
Sandro Lorenz ◽  
Reinhard Schmitz ◽  
Luis Delgado
Keyword(s):  
Traffic Management ◽  
Probability Distributions ◽  
Weather Conditions ◽  
Air Traffic ◽  
Weather Data ◽  
Data Set ◽  
Airport Capacity ◽  
Weather Events ◽  
The Individual ◽  
The Impact

Weather events have a significant impact on airport performance and cause delayed operations if the airport capacity is constrained. We provide quantification of the individual airport performance with regards to an aggregated weather-performance metric. Specific weather phenomena are categorized by the air traffic management airport performance weather algorithm, which aims to quantify weather conditions at airports based on aviation routine meteorological reports. Our results are computed from a data set of 20.5 million European flights of 2013 and local weather data. A methodology is presented to evaluate the impact of weather events on the airport performance and to select the appropriate threshold for significant weather conditions. To provide an efficient method to capture the impact of weather, we modelled departing and arrival delays with probability distributions, which depend on airport size and meteorological impacts. These derived airport performance scores could be used in comprehensive air traffic network simulations to evaluate the network impact caused by weather induced local performance deterioration.

scholarly journals Initial results of the project SINOPTICA (Satellite-borne and IN-situ Observations to Predict The Initiation of Convection for ATM) 

2021 ◽  
Author(s):  
Laura Esbri ◽  
Maria Carmen Llasat ◽  
Tomeu Rigo ◽  
Massimo Milelli ◽  
Vincenzo Mazzarella ◽  
...  
Keyword(s):  
Weather Prediction ◽  
Wrf Model ◽  
Remote Sensing Data ◽  
Weather Forecast ◽  
Relevant Information ◽  
Air Traffic ◽  
Severe Weather ◽  
Radar Images ◽  
Weather Events ◽  
Adverse Weather

<p>In the framework of the SINOPTICA project (EU H2020 SESAR, 2020 – 2022), different meteorological forecasting techniques are being tested to better nowcast severe weather events affecting Air Traffic Management (ATM) operations. Short-range severe weather forecasts with very high spatial resolution will be obtained starting from radar images, through an application of nowcasting techniques combined with Numerical Weather Prediction (NWP) model with data assimilation. The final goal is to integrate compact nowcast information into an Arrival Manager to support Air Traffic Controllers (ATCO) when sequencing and guiding approaching aircraft even in adverse weather situations. The guidance-support system will enable the visualization of dynamic weather information on the radar display of the controller, and the 4D-trajectory calculation for diversion coordination around severe weather areas. This meteorological information must be compact and concise to not interfere with other relevant information on the radar display of the controller.</p><p>Three severe weather events impacting different Italian airports have been selected for a preliminary radar analysis. Some products are considered for obtaining the best radar approach to characterize the severity of the events for ATM interests. Combining the Vertical Integrated Liquid and the Echo Top Maximum products, hazard thresholds are defined for different domains around the airports. The Weather Research and Forecasting (WRF) model has been used to simulate the formation and development of the aforementioned convective events. In order to produce a more accurate very short-term weather forecast (nowcasting), remote sensing data (e.g. radar, GNSS) and conventional observations are assimilated by using a cycling three-dimensional variational technique. This contribution presents some preliminary results on the progress of the project.</p>

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