Nowcasting using machine learning and deterministic models: a Brazilian initiative to improve aviation meteorology

Abstract

The present book is a compilation of recent research dedicated to the applications of prediction models for weather nowcasting linked to aeronautical meteorology. Models embrace differential equations for atmospheric dynamics, as well as data-driven approaches. Convective weather, wind, clear air turbulence, visibility, and ceiling are the significant phenomena affecting aviation events investigated by the “Cátedra” project of aeronautical meteorology. The project is a joint effort between the graduate meteorology program from the Federal University of Rio de Janeiro (UFRJ), the Department of Airspace Control (DECEA) and the Air Force University (UNIFA). The book focuses on aviation operational meteorology and deals with numerical weather forecast simulation results obtained by deterministic and hybrid models. The latter is based on the composition of deterministic modeling and computational intelligence techniques. The studies presented in this publication make use of data from remote sensing sensors, such as satellite, radiometer, ceilometer, and sodar, as well as information from insitu observations for monitoring and developing short-term forecast models. These aim to predict convective weather, surface wind shifts, wind gusts, clear air turbulence, low visibility due to fog, and low ceilings. All these are important for landing and takeoff procedures, as well as for scheduling flights and increasing safety on Brazilian air routes. This volume provides a comprehensive overview of research results, including comments on the currently existing knowledge, and the numerous remaining difficulties in predicting and measuring issues related to aforementioned meteorological events at different time and space scales. It will be helpful to academics with an interest in operational meteorology and aviation as well as weather offices, pilots, meteorologists, aviation experts, scientists, college students, postgraduates, and others. Most of the chapters are produced by “Cátedra” project´s researchers and published in scientific journals.