Compressive Representations of Weather Scenes for Strategic Air Traffic Flow Management

Abstract:

Terse representation of high-dimensional weather scene data is explored, in support of strategic air traffic flow management objectives. Specifically, we consider whether aviation-relevant weather scenes are compressible, in the sense that each scene admits a possibly-different sparse representation in a basis of interest. Here, compression of weather scenes extracted from METAR data – including temperature, flight categories, and visibility profiles for the contiguous United States – is examined, for the graph-spectral basis. The scenes are found to be compressible, with 75-95% of the scene content captured using 0.5-4% of the basis vectors. Further, the dominant basis vectors for each scene are seen to identify time-varying spatial characteristics of the weather, and reconstruction from the compressed representation is demonstrated. Finally, potential uses of the compressive representations in strategic TFM design are briefly scoped.

Año de publicación:

2022

Keywords:

• compressive representations
• strategic traffic flow management
• aviation weather

Fuente:

scopus