Fernando Gomes

Holds a Master's degree in Meteorology from the Federal University of Pelotas (UFPel) and a Bachelor's degree in Meteorology from the Federal University of Rio de Janeiro (UFRJ). During the Master's, conducted research as a scholarship student in a Research and Development (R&D) project in the area of Nowcasting applied to the study of severe thunderstorms using the Thunderstorm Identification, Tracking, Analysis, and Nowcasting (TITAN) algorithm. Developed further work in the areas of Cloud Physics and Agroclimatology, and has experience in Weather Forecasting, Agrometeorology and Air Quality. Has knowledge of programming languages - such as Python and GrADS Script Language (GSL) -, Data Science and computational modeling in the SWAP/WOFOST software. Currently working as a nowcasting forecaster in the Paraná Environmental Monitoring and Technology System (SIMEPAR).

Had the opportunity to deeply study North American climatology during his Master's, developing a special interest in meteorological systems and phenomena of the Northern Hemisphere. Has a C2 Proficient level in English, which allows to not only understand meteorological issues but also engage with various subjects in this language, enabling effective collaboration with people from all over the world. Some of the professional interests lie in expanding his expertise in global weather patterns and leveraging his language skills in diverse international environments.

Recently had work accepted for presentation at the 2024 Pan-American Meteorology Conference, and currently taking the course ‘’IBM Data Analyst Professional Certificate'.
 

Fernando Gomes is a skilled meteorologist with a bachelor's and master's degree in Meteorology, boasting extensive experience in operational forecasting, data analysis, and leveraging advanced technologies. At SIMEPAR, he has excelled in providing medium- and short-term weather forecasts, issuing real-time alerts, and conducting environmental monitoring for key sectors such as energy. His expertise includes working with radar and satellite data, numerical models, and programming tools like Python, TITAN, and Google Earth Engine.

In addition to his technical skills, Fernando has a strong academic background, having conducted research on storm forecasting methods and served as a lecturer for undergraduate meteorology courses. These experiences demonstrate his ability to develop and review educational materials and communicate complex meteorological concepts effectively.

Fernando also brings valuable interpersonal skills, gained through client meetings, media interactions, and coordination with stakeholders. His certifications in Machine Learning, data science, and advanced English proficiency (C2 level) highlight his commitment to continuous learning and his capacity to integrate innovative methodologies into operational processes. These qualifications position him to address technical challenges and contribute to the company’s success effectively.

Holds a Master’s degree in Meteorology from the Federal University of Pelotas, where he contributed to a research project focused on blending techniques for storm forecasting with atmospheric lightning discharges, in partnership with an energy company. He also completed his Bachelor's degree at the Federal University of Rio de Janeiro, where his final project involved agroclimatic suitability studies using advanced satellite data applications.