GESTION DE LA INCERTIDUMBRE METEOROLOGICA PARA UN TRAFICO AEREO MAS EFICIENTE: PROVISION DE DATOS METEOROLOGICOS Y EVASION DE TORMENTAS

Website (Under construction)

Funding Entity:

Convocatorias 2018
Proyectos de I+D “EXCELENCIA” y Proyectos de I+D+I “RETOS INVESTIGACIÓN” Ministerio de Ciencia, Innovación y Universidades. Gobierno de España. Financiado por FEDER/Ministerio de Ciencia, Innovación y Universidades/Agencia Estatal de Investigación. Referencia del Proyecto RTI2018-098471-B-C32

Institutions:

  • Universidad Carlos III de Madrid: Manuel Soler (PI), Javier García-Heras, Daniel González Arribas, Aniel Jardines, Eduardo Andrés.
  • AEMET: Juan Simarro.

Abstract:

The general objective of this subproject is the development of stochastic aircraft trajectory planning algorithms in the presence of thunderstorms (modeled as stochastic objects). This needs the meteorological raw data input (an specific objective of this subproject), the statistically post-processed products (specific objective of subproject 3), and the planned trajectory (specific objective of subproject 1)

The first specific objective of this subproject is to make the different meteorological inputs, namely Ensemble Probabilistic Systems (EPS) and Rapid Developing Thunderstorms (RDT), available for all other subprojects within MetATS. We will need first to access the Meteorological information (the participation of AEMET with this subproject guarantees the access to data). Secondly, this information should be pre-processed to extract the required information our of the raw data, e.g., wind uncertainties, probability of convection, probability of Clean Air Turbulence, thuderstorms in a time-lagged ensemble. Lastly, we will build and store the pre-processed data in a database to be accessed by the partners. The specific objective is key to feed all other tasks within the project.

The second specific objective os this subproject is to develop different aircraft trajectory planning algorithms in the presence of evolving thunderstorms (modeled as stochastic objects). We will explore two different methodologies, namely reach & avoid and a GPU-based heuristic optimization, each with advantages and disadvantages, to tackle the problem. The ambition is to solve it in three-dimensions, including thus the vertical characterization of the thunderstorm and its eventual vertical avoidance. Yet, computational speed and robustness is demanded to make it compatible with short-term planning tools. The resulting trajectories should ensure safety (to certain degree of confidence) and be compatible with both airborne (pilots/dispatchers) and ground (controllers) systems.

We ambition to transfer know-how to the industry. There is a final task envisioned to collaborate with GTD -http://www.gtd.es-. In particular, to develop additional functionalities for EWAS dispatching tool -http://www.gtd.es/es/productos/ewas-. It has advanced meteorological features (all of them deterministic), including thunderstorm evolution based on the RDT product. They have expressed interest in its stochastic evolution and the capabilities to propose trajectories capable of avoiding them.

All in all, the potential impact of this research is tremendous, since today airborne and ground systems lack of thunderstorm probabilistic information to anticipate decisions and plan in a more robust manner. Recall that the inherently uncertain nature of thunderstorms causes major safety risks: Strong conflicting up and downdrafts lead to heavy turbulence; Hail, severe icing and lightning can also inflict significant damage to aircraft equipment and windshields. Also, convective weather is one of the leading causes of weather delay (responsible of 60% of all delays greater than 15 min), with almost half of weather related delays in the busy summer months being caused by it.