- Nationality: Spanish
- Funding entity and Program:
- PIF UC3M
- SESAR Engage KTN PhD

PhD Thesis
A pilot/dispatcher support tool based on the enhanced provision of thunderstorm forecasts considering its inherent uncertainty.
Supervisors
Manuel Soler (UC3M), Manuel Sanjurjo-Rivo (UC3M) and Maryam Kamgarpour (University of British Columbia)
Abstract
The intrinsic uncertainty of thunderstorms poses a major threat for flights, as it jeopardizes the safety of the passengers and the airframe. The aim of this thesis consists in developing new methodologies for aircraft trajectory planning in real time assuming stochastic weather forecasts and suggest safe and efficient detours to pilots and ATCs.
Project participation

MetATS – Managing meteorological uncertainty for a more efficient air traffic system.
RTI2018-098471-B-C32. CONVOCATORIA 2018 DE PROYECTOS I+D+i «RETOS INVESTIGACIÓN» DEL PROGRAMA ESTATAL DE I+D+i ORIENTADA A LOS RETOS DE LA SOCIEDAD- MINISTERIO DE CIENCIA, INNOVACIÓN Y UNIVERSIDADES. 2019-2021. 2019-2021.
STORMY – A pilot/dispatcher support tool based on the enhanced provision of thunderstorm forecasts considering its inherent uncertainty.
Grant agreement No 783287. Funded by Engage, The SESAR H2020 Research Knowledge Transfer. 2019-2021
Research Stays

Institutions: Escuela Politécnica Federal de Lausana (EPFL)
Department/Group: SYCAMORE Lab, (EPFL)
Host: Maryam Kamgarpour
Period: from to December 2021 to March 2022