This study analyzes the relationship between fires and climate extremes in the Caatinga biome from 2012 to 2023 by integrating Fire Radiative Power (FRP) from VIIRS (S-NPP and NOAA-20), Vapor Pressure Deficit (VPD) and air temperature from ERA5, drought indices (SPI-1 and SPI-6), and heatwave events from the Xavier database. Daily percentiles of maximum (CTX90pct) and minimum (CTN90pct) temperatures were used to characterize heatwaves. Spatial and temporal dynamics of fire patterns were identified using the HDBSCAN algorithm, an unsupervised Machine Learning clustering method applied in three-dimensional space (latitude, longitude, and time). A marked seasonality was observed, with fire activity peaking from August to November, especially in October, when FRP reached ~1000 MW/h. The years 2015, 2019, 2021, and 2023 exhibited the highest fire intensities. A statistically significant upward trend in cluster frequency was detected (+1094.96 events/year; p < 0.001). Cross-correlations revealed that precipitation deficits (SPI) preceded FRP peaks by about four months, while VPD and air temperature exerted immediate positive effects. FRP correlated positively with heatwave frequency (r = 0.62) and negatively with SPI (r = −0.69). These findings highlight the high vulnerability of the Caatinga to compound drought and heat events, indicating that fire management strategies should account for both antecedent drought conditions, monitored through SPI, and real-time atmospheric dryness, measured by VPD, to effectively mitigate fire risks.

Resumo Este estudo apresenta a segunda etapa da avaliação espaço-temporal das tendências a longo prazo nos valores da Coluna Total de Ozônio (CTO) sobre o Nordeste Brasileiro (NEB) durante a atuação do modo de variabilidade atmosférica El Niño - Oscilação Sul (ENOS), com foco na fase La Niña (modalidades Canônica e Modoki). O objetivo é analisar a variação anual e os efeitos desse fenômeno na região de estudo no período entre 1997 e 2018. Os dados utilizados são provenientes de sensoriamento remoto, gerados pelos sensores Total Ozone Mapping Spectrometer (TOMS) e Ozone Monitoring Instrument (OMI), disponibilizados pela National Aeronautics and Space Administration (NASA), e analisados através de médias, valores de anomalias e diagramas hovmoller. Foi constatado que eventos La Niña provocam, predominantemente, aumento na concentração de ozônio sobre o NEB. Nos períodos de atuação desse modo de variabilidade a desaceleração da Circulação Brewer-Dobson (CBD) é causada pela intensificação dos ventos alísios gerando acúmulo de ozônio na região tropical. Entre as duas modalidades, fenômenos Modoki apresentam esse efeito mais intensificado. O maior (+6,5) e menor (-3,0) valor médio mensal de anomalia obtidos ocorreram durante sua atuação, registrados na região norte do NEB em julho e setembro, respectivamente.

Resumo O objetivo deste trabalho é analisar a variação anual e os efeitos do modo de variabilidade atmosférica El Niño (Canônico e Modoki) na Coluna Total de Ozônio (CTO) sobre o Nordeste Brasileiro (NEB) entre 1997 e 2018 utilizando dados dos sensores Total Ozone Mapping Spectrometer (TOMS) e Ozone Monitoring Instrument (OMI). Foi constatada uma variação mensal média em toda área estudada com comportamento típico de domínio do ciclo anual na variabilidade sazonal, apresenta valor mínimo no mês de maio e máximo em outubro. Observou-se uma tendência de decaimento na série dos valores médios durante o período analisado. Análises de agrupamento revelaram que diferentes regiões da NEB possuem comportamentos e valores médios de CTO diferenciados. Análise de ondeletas expôs ciclos de doze meses de duração atuando na CTO em toda área estudada, ciclos de seis meses, demonstrando que o ciclo semianual domina a variabilidade sazonal em menores latitudes, e ciclos de dois-três anos, representando a importante atuação da Oscilação Quase Bienal (OQB). As médias das anomalias mostram que eventos El Niño afetam a CTO causando, predominantemente, diminuição de seus valores. Esses eventos em modalidade Modoki tem maior potencial em afetar a CTO que os Canônicos com anomalias negativas de maior intensidade.

This study aims to quantify and regionalize future changes in daily minimum (T _min ), maximum (T _max ), and the diurnal temperature range (DTR = T _max − T _min ) across South America for 2015–2100, addressing the current lack of dedicated sub-regional assessments of DTR projections using Coupled Model Intercomparison Project Phase 6 (CMIP6) models. Model skill was assessed against the Climatic Research Unit (CRU) Time-Series (TS) dataset, and the five best-performing members were used to build sub-regional ensembles for ten predefined domains to improve local signal detection. Trend analysis shows a continent-wide tendency toward DTR compression driven by stronger nighttime warming: median DTR trends are − 7.6 × 10⁻³ °C year⁻¹ (SSP2-4.5; Shared Socioeconomic Pathways) and − 1.28 × 10⁻² °C year⁻¹ (SSP5-8.5), with mean reductions between 2015 and 2025 and 2090–2100 of ≈ − 0.71 °C (SSP2-4.5) and ≈ − 1.04 °C (SSP5-8.5). The spatial pattern is heterogeneous: most domains exhibit the largest declines, while parts of the eastern coast show near-neutral DTR under the low-emission pathway and a clear tendency to increase under the high-emission pathway. Trend significance was evaluated using a modified Mann–Kendall test (α = 0.05) and Theil–Sen slope estimates; 5 of 10 sub-regions display statistically significant DTR trends under SSP2-4.5, increasing to 8 of 10 under SSP5-8.5, indicating stronger and more widespread signals under higher forcing. Crucially, regionalizing ensembles uncovers coastal signatures masked in continental means, offering a novel contribution to CMIP6-based assessments of DTR in South America. Given model limitations, targeted attribution studies and investments in high-resolution observational networks and regional climate modeling are recommended. Despite these uncertainties, the results provide valuable guidance for adaptation planning in health, agriculture, and energy sectors across South America. Graphical Abstract This visual summary presents a study that quantifies projected changes in T _min , T _max , and the DTR across South America through 2100, using subregional ensembles of CMIP6 models composed of the five highest-skill members in each domain. It conveys the workflow and main results through integrated visual components: the top-left panel maps South America into 10 subregions; the central-top panel displays the multimodel CMIP6 catalogue; the top-right panel shows Taylor diagrams and historical series used to select the top five models per subregion; the central flow outlines spatial aggregation, skill evaluation, ensemble construction, trend estimation with the Theil–Sen estimator, and significance testing via a modified Mann–Kendall test; the bottom-right contains time-series panels of T _min and T _max under scenarios; and the bottom maps present projected DTR anomalies (SSP2-4.5, SSP5-8.5) while the bottom-left summarizes DTR by subregion, highlighting spatial heterogeneity. Projections indicate continent-wide DTR compression, with median trends of -7.6 × 10⁻³ °C year⁻¹ (SSP2-4.5) and − 1.28 × 10⁻² °C year⁻¹ (SSP5-8.5), and mean reductions from 2015 to 2025 to 2090–2100 of ≈ − 0.71 °C and ≈ − 1.04 °C. The decline reflects warming of both T _max and T _min , with a stronger rise in T _min . This asymmetric warming may be related to enhanced longwave radiation, higher humidity, cloud-cover changes, or land-use alterations. Most domains show robust, significant DTR declines, while parts of the eastern coast exhibit neutral or positive trends in some seasons and scenarios — patterns revealed only by the subregional ensemble approach. These shifts imply hotter nights, reduced thermal comfort, greater stress on health and energy systems, altered phenology, and uneven agricultural impacts between interior and coastal regions, underscoring the need for locally targeted adaptation and high-resolution attribution studies.