ALBERT

Description: Among its many other functions, the Federal Aviation Administrations En Route Automation Modernization (ERAM) provides external systems with real-time air traffic data for flights in enroute airspace in the National Airspace System. It replaced the En Route Host computer and backup system used at 20 FAA Air Route Traffic Control Centers (Centers) nationwide. Among the new features of ERAM, its output data stream of flight plan and track data includes a unique identifier for a flight originating in any one of the 20 ERAM Centers. The unique identifier, called the Global Unique Flight Identifier (GUFI), is persistent across all the Centers that track the flight. However, certain factors make it difficult to correlate data using the GUFI. First, the value of the GUFI is only unique within a time window of seven days. Second, the GUFI is attached only to flight-plan related data messages. Finally, track positions reported by ERAM do not reference the GUFI. In order to correlate historical as well as real time flight-plan and position related ERAM data, an efficient, heuristic approach was developed, and a prototype was developed. The approach showed that the processing speed, through parallel processing, is sufficient to correlate ERAM data in real-time. As described in this paper, when there are multiple track positions reported from multiple Centers within a few seconds, each position is assigned with a weighted score to indicate the quality of the position relative to its last know position. The weighted score can be used to eliminate potentially duplicate track positions. The approach is database-agnostic, and can be implemented in a Big Data system such as an Apache Hadoop system, as well as in traditional database systems.

Description: Aviation Routine Weather Report (METAR) provides surface weather information at and around observation stations, including airport terminals. These weather observations are used by pilots for flight planning and by air traffic service providers for managing departure and arrival flights. The METARs are also an important source of weather data for Air Traffic Management (ATM) analysts and researchers at NASA and elsewhere. These researchers use METAR to correlate severe weather events with local or national air traffic actions that restrict air traffic, as one example. A METAR is made up of multiple groups of coded text, each with a specific standard coding format. These groups of coded text are located in two sections of a report: Body and Remarks. The coded text groups in a U.S. METAR are intended to follow the coding standards set by National Oceanic and Atmospheric Administration (NOAA). However, manual data entry and edits made by a human report observer may result in coded text elements that do not follow the standards, especially in the Remarks section. And contrary to the standards, some significant weather observations are noted only in the Remarks section and not in the Body section of the reports. While human readers can infer the intended meaning of non-standard coding of weather conditions, doing so with a computer program is far more challenging. However such programmatic pre-processing is necessary to enable efficient and faster database query when researchers need to perform any significant historical weather analysis. Therefore, to support such analysis, a computer algorithm was developed to identify groups of coded text anywhere in a report and to perform subsequent decoding in software. The algorithm considers common deviations from the standards and data entry mistakes made by observers. The implemented software code was tested to decode 12 million reports and the decoding process was able to completely interpret 99.93 of the reports. This document presents the deviations from the standards and the decoding algorithm. Storing all decoded data in a database allows users to quickly query a large amount of data and to perform data mining on the data. Users can specify complex query criteria not only on date or airport but also on weather condition. This document also describes the design of a database schema for storing the decoded data, and a Data Warehouse web application that allows users to perform reporting and analysis on the decoded data. Finally, this document presents a case study correlating dust storms reported in METARs from the Phoenix International airport with Ground Stops issued by Air Route Traffic Control Centers (ATCSCC). Blowing widespread dust is one of the weather conditions when dust storm occurs. By querying the database, 294 METARs were found to report blowing widespread dust at the Phoenix airport and 41 of them reported such condition only in the Remarks section of the reports. When METAR is a data source for an ATM research, it is important to include weather conditions not only from the Body section but also from the Remarks section of METARs.