An important function of traffic flow management is ensuring the number of aircraft entering a sector does not exceed the amount that can be safely controlled by the sector controller. One factor that makes this task difficult is the uncertainty of the impact of convective weather, as both the weather forecast and the impact given specific weather is uncertain. In this investigation, we study this effect indirectly by exploring the relationship between convective weather forecasts and observed

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... eak sector occupancy. Specifically, we measure how well the peak sector occupacy can be predicted using area-based and directional-based weather models. We also present a methodology for comparing weather models using a machine learning approach. When the forecast is for light weather, the impact of weather is presumably minimal and little difference is observed between models in our evaluation. In contrast, when heavy weather is forecast, the weather models outperform those without a weather component and also have statistically significant differences among each other. Nomenclature CIWS = Corridor Integrated Weather System FWCI = Forecast Weather Coverage Index CWAM1 = Convective Weather Avoidance Model MAP = Monitor Alert Parameter DFWCI = Divided Forecast Weather Coverage Index WITI = Weather Impacted Traffic Index