Supporting weather forecasting performance management at aerodromes through anomaly detection and hierarchical clustering

Model for Managing Divert Risk Caused by Low Visibility in Airline Operations Management

“…Novotny et al ( 27 ) studied the generation and realization ratio of TAFs according to the methodology in ICAO Annex 3 ( 27 ). Similarly, Harris ( 28 ) studied the accuracy of TAFs with different scoring methods for comparison, and Patriarca et al ( 32 ) studied determining TAF accuracy levels in managing airport weather forecasts with anomaly detection and hierarchical clustering because of its importance for decision-makers. The studies have shown that the accuracy of TAFs varies by airport.…”

Intrinsic Explainable Self-Enforcing Networks Using the ICON-D2-Ensemble Prediction System for Runway Configurations

“…Weather forecasts are fundamental to flight safety and management. The functioning of airport-related meteorological services supports decision-making regarding flight routes and planning [1].…”

“…The digitalization and increase in, e.g., sensors and satellite imagery, create a large amount of data that is analyzed with various tools (for an overview, see [8]). For example, Key Performance Indicators (KPIs) are recommended to be used as a propensity metric in the preparation of Terminal Aerodrome Forecasts (TAFs) for future weather conditions [1]. Parameters for traffic management initiatives (TMI) under uncertain weather conditions are proposed using an epsilon greedy approach and a Softmax algorithm [2].…”

“…Proc. 2023, 39, 41 2 of 12 data and group similar forecasts [1]. Additional methods are used, e.g., Transductive Long Short Term Memory (T-LSTM) for weather forecasting [16] or Spatio-Temporal Graph Convolutional Network to estimate the arrival and departure capacity under weather impact [17].…”