NDLI: Prediction of weather impacted airport capacity using RUC-2 forecast

Content Provider	IEEE Xplore Digital Library
Author	Yao Wang
Copyright Year	2012
Description	Author affiliation: NASA Ames Res. Center, Moffett Field, CA, USA (Yao Wang)
Abstract	Weather induced airborne delays have caused significant problems at the major commercial airports in the United States. Using Rapid Updated Cycle forecast data (RUC-2), this paper presents real case studies for assessing the impact of weather on airport capacities by Quadratic Response Surface (QRS) linear regression models and ensemble Bagging Decision Tree regression (BDT) models. Three high-demand major airports: Newark Liberty International Airport (EWR), Chicago O'Hare International Airport (ORD), and Atlanta International Airport (ATL) were selected for the analysis. Both QRS and BDT models were developed and evaluated using the Federal Aviation Administration (FAA) Aviation System Performance Metrics (ASPM) data and RUC-2 weather forecasts for these airports. The performances of the two weather impacted airport capacity models were compared and the errors between estimates and observations of airport arrival rates (AAR) were evaluated. The accuracy of AAR predictions in several hour look-ahead times using RUC-2 forecast weather was examined. The experimental results show that the accuracies of AAR estimations by nonlinear BDT regression models are much better than that from QRS multiple linear regression models. With airport AAR BDT models, the errors on weather corresponding AAR estimates using RUC weather data are smaller than that by METAR surface weather observations. Considering RUC includes much more weather information than METAR does, these findings strongly suggest that the adverse weather impact on airport capacity is complicated, relies on many predicting variables carried by RUC and it is inherently nonlinear. As a consequence, by using RUC weather forecasts, root mean squared error (RMSE) of the airport AAR BDT model predictions at one-hour look-ahead time are less than one and two arrival aircrafts per quarterly-hour for EWR and ORD/ATL airport, respectively. The ratio between AAR RMSE and average AAR for AAR predictions at one to eight hour look-ahead time is less than 10% for all three airports with nonlinear BDT models using RUC-2 weather forecasts. These results appear to be reasonably good.
Sponsorship	Aerosp. Electron. Syst. Soc.
File Size	602127
File Format	PDF
ISBN	9781467316996
ISSN	21557195
e-ISBN	9781467317009
DOI	10.1109/DASC.2012.6382312
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-10-14
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Airports Weather forecasting Atmospheric modeling Data models Predictive models Economic indicators
Content Type	Text
Resource Type	Article
Subject	Electrical and Electronic Engineering Aerospace Engineering

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