Spatio-temporal dynamics of flying rivers: assessment of precipitation model effectiveness and its influence on the SACZ

• Ano de defesa: 2025
• Autor(a) principal: Silva, Arthur Amaral e
• Tipo de documento: Tese
• Tipo de acesso: Acesso aberto
• Idioma: eng
• Instituição de defesa: Universidade Federal de Viçosa; Engenharia Civil
• Palavras-chave em Português: Precipitação (Meteorologia) - Variabilidade - Brasil.; Florestas tropicais - Amazonas; Zonas climáticas - Brasil; Mudanças climáticas; Sensoriamento remoto; CIENCIAS EXATAS E DA TERRA::GEOCIENCIAS::GEODESIA
• Link de acesso: https://locus.ufv.br/handle/123456789/34247; https://doi.org/10.47328/ufvbbt.2025.403

The Amazon Rainforest plays a fundamental role in regulating global and regional climate patterns, sustaining one of the most complex hydrological cycles on the planet. Its continuous evapotranspiration process generates atmospheric moisture, which is essential for the formation of both local and distant rainfall, contributing to moisture redistribution through the so-called "Flying Rivers." These large-scale atmospheric moisture transport systems carry vast amounts of water vapor from the Amazon Basin to other regions of South America, particularly southeastern Brazil, ensuring the continuity of precipitation and influencing the regional hydrological regime. However, increasing deforestation and climate change have significantly disrupted this process, compromising the intensity and consistency of the Flying Rivers and, consequently, altering precipitation patterns in southeastern Brazil. One of the primary meteorological systems influenced by the Flying Rivers is the South Atlantic Convergence Zone (SACZ), a key climatic phenomenon responsible for rainfall distribution in southeastern Brazil, especially during the austral summer. The SACZ is characterized by an extensive band of cloud cover and precipitation stretching from the Amazon to the South Atlantic Ocean, regulating water availability, agricultural productivity, and the frequency of extreme climate events such as droughts and floods. Given this climatic interconnectivity, this study aims to assess the variability of precipitation patterns associated with the SACZ and its relationship with the Flying Rivers using advanced remote sensing techniques, climate modeling, and statistical analysis. First, four widely used climate models were analyzed to forecast precipitation, applying statistical approaches to a 20-year time series to evaluate their accuracy against in situ measurements. Additionally, cluster analyses were conducted to examine seasonal rainfall patterns across Brazil and assess the influence of environmental and climatic factors—including temperature, evapotranspiration, NDVI, and topography—on precipitation distribution. Finally, the relationship between SACZ precipitation patterns and other atmospheric phenomena was analyzed over a 21-year period to better understand atmospheric moisture circulation dynamics and its hydrological impacts in Minas Gerais. The results highlight the increasing vulnerability of southeastern Brazil to changes in moisture transport patterns, with significant implications for water resource management and climate adaptation strategies. The use of advanced Big Data techniques and machine learning improved the predictive analysis of precipitation patterns, reinforcing the importance of integrating satellite data with ground-based measurements for effective climate monitoring. Keywords: Amazon Rainforest; Flying Rivers; South Atlantic Convergence Zone (SACZ); Climate Change; Remote Sensing; Precipitation Patterns; Climate Modeling.