Classification of Weather Translation Models for NextGen

In past work, we have surveyed the state-of-the-art in weather translation models and Air Traffic Management (ATM) impact models for the Next Generation Air Transportation System (NextGen). We have found that the literature often blurs the distinction between weather translation and ATM impact models, and to this end, we have in this paper explored a rigorous definition and classification of fundamental weather translation models for NextGen. Weather translation models transform weather forecast data into aviation constraints and threshold events. In general, weather translation models reflect how aircraft, pilots, or airlines respond to weather phenomena, independent of the time of day or location in the National Airspace System (NAS) (that is, independent of the ATM operational state and ATM application). Given the ATM operational state (e.g., demand on an ATM resource) and ATM resources (airport, runway, and fix locations, routes, sector and center boundaries, etc), weather translation models are used to derive the impacts of weather on ATM resources. In this paper, we study weather translation models and identify the distinguishing characteristics which classify a technology into either a weather translation technology or an ATM impact technology, regardless of whether the model is a deterministic model or a probabilistic model. For instance, we identify how weather translation models may be categorized by domain as either airport or airspace translation models. Airport translation models include the translation of weather forecast data into airport IMC, MVMC, or VMC conditions, runway usability, runway configuration usability, Airport Departure Rate (ADR), or Airport Arrival Rate (AAR). Airspace weather translation models first and foremost include pilot behavior models, which identify how a pilot will respond to a given weather state, in particular, a weather state that constitutes a safety hazard. Pilot behavior models apply to convective weather avoidance, turbulence avoidance, in-flight icing avoidance, volcanic ash avoidance, as well as to space weather avoidance. Weather Avoidance Fields (WAFs) results from the transformation of the weather forecast data through pilot-behavior models – the Convective Weather Avoidance Model (CWAM) being one of the most popular. While WAFs are a weather translation output, they may be further processed (translated) to create Route Availability (RA) (conversely, route Blockage (RB)) and airspace permeability information. In our definition of a weather translation model, we make a distinction between when a weather translation model processes a generic or historical demand verses when the weather translation model processes the specific traffic demand characteristics and operational conditions of a given time and date. In doing so, we are able to classify a directional capacity concept to be a weather translation model if it may simply describes the permeability of the weather system in terms of a cardinal direction (north, east, south, or west), however, if it specifically addresses the directional capacity given the specific amount of traffic flowing in a particular direction, capacity limits of an airspace (e.g., workload, complexity, or Monitor Alert Parameter (MAP) values), and aircraft performance limits (e.g., ceiling, speed, or navigation performance), then we classify it as an ATM impact model. While we classify a technology that evaluates the usability of a runway or runway configuration as a weather translation model, we classify a runway configuration prediction or airport throughput algorithm as an ATM impact model – a subtle distinction being that in order to predict the runway configuration that is going to be used or throughput that will result requires operational data (e.g., upstream demand level and aircraft types) beyond just the weather state. In NextGen, it is envisioned that automated Decision Support Tools (DSTs) will fully integrate weather information into ATM planning processes. Data exchange and forecast dissemination will utilize a virtual four-dimensional (4D) Weather Data Cube (WDC) as a “one-stop-shopping place” for weather information. A subset of that data repository, the Single Authoritative Source (SAS), will contain the primary weather information for ATM decision making. Weather translation models will process data coming out of the 4D WDC into valuable ATM-relevant information, without the need for operational data or ATM constraint information. Thus, weather translation models will be at the root of transforming raw weather forecast “data” into high level ATM-relevant “information”. When combined with operational data, this ATM-relevant information will be used by ATM decision makers and their DSTs to control the NAS in NextGen. Since different government agencies are researching and building different components of this system (e.g., the National Weather Service (NWS) is developing the 4D WDC, while the FAA has separate organizations researching, building, and deploying weather translation models, ATM impact models, and DSTs), it is important to have well-defined boundaries between these system components for funding, research and development, and transfer of technology reasons.