Alan Prestes

This research applies continuous wavelet analysis and seasonal correlation analysis to tree-ring data from Três Barras National Forest (FLONA Três Barras), revealing diverse influences on growth, including climate, solar activity, and external factors. The methodology involved tree-ring collection and subsequent wavelet and seasonal analyses to unveil the non-stationary characteristics of and multifaceted influences on growth. Key findings include the subtle effects of El Niño events on tree-ring development, the sensitivity of Araucaria angustifolia to temperature changes, the significant influence of precipitation during drought periods, and the intricate relationship between tree growth and solar cycles. The El Niño–Southern Oscillation (ENSO) emerges as a primary climatic driver during specific intervals, with external factors (precipitation, temperature, and solar cycle–solar irradiance) influencing tree response between 1936 and 1989. Additionally, the seasonal correlation analysis highlighted the importance of sub-annual climate variability, capturing specific intervals, such as a 3-month season ending in March of the previous year, that significantly impacted tree-ring growth. The study underscores the importance of protecting the endangered Araucaria angustifolia for climatic studies and local communities. Historically, in Brazil, Araucaria angustifolia seeds played a vital role in sustaining indigenous populations, which in turn helped to disperse and propagate forests, creating anthropogenic landscapes that highlight the interconnected relationship between humans and the preservation of these forests.

This article explores the dendrochronological potential of Ocotea porosa (Nees & Mart) Barroso (Imbuia) for reconstructing past climate conditions in the General Carneiro region, Southern Brazil, utilizing well-established dendroclimatic techniques. A total of 41 samples of Imbuia were subjected to dendroclimatic analysis to reconstruct precipitation and temperature patterns over the period from 1446 to 2011. Notably, we achieved the longest reconstructions of spring precipitation and temperature for the Brazilian southern region, spanning an impressive 566-year timeframe, by employing a mean chronology approach. To achieve our objectives, we conducted a Pearson’s correlation analysis between the mean chronology and the climatic time series, with a monthly temporal resolution employed for model calibration. Impressively, our findings reveal significant correlations with coefficients as high as |r_x,P| = 0.32 for precipitation and |r_x,T| = 0.45 for temperature during the spring season. Importantly, our climate reconstructions may elucidate a direct influence of the El Niño—South Oscillation phenomenon on precipitation and temperature patterns, which, in turn, are intricately linked to the natural growth patterns of the Imbuia trees. These results shed valuable light on the historical climate variability in the Southern Brazil region and provide insights into the climatic drivers affecting the growth dynamics of Ocotea porosa (Nees & Mart) Barroso.

In part 1 of our physics education series, we introduced a novel solution based on Yoon-Lui’s solutions 1 and 2. Building upon that, this follow-up presents a new solution obtained by combining the generating functions of Yoon-Lui-1 and Yoon-Lui-3, resulting in a new and simplified general solution. We also calculate the singular points and determine their coordinates for various parameter values. A graphical representation of the solution is presented, showing the magnetic field lines and current density distribution. The behavior of the magnetic field and the effect of varying the parameter are discussed. The observed magnetic islands and singular points are relevant in the fields of Plasma Physics and Space Physics, providing insights into magnetic structures in plasmas and their impact on confinement and stability. Furthermore, this study encourages innovation and equips researchers and students with the necessary tools to make meaningful contributions to the field, emphasizing the integration of scientific literature into physics education to promote a comprehensive understanding of physical concepts and their practical applications.

Este trabalho utiliza amostras da espécie Imbuia, (Ocotea porosa (Nees & Mart) Barroso), coletadas na cidade de General Carneiro, região Sudeste do Estado do Paraná (26º24’01 25"S 51º24’03 91"O), Brasil, para gerar a série dendrocronológica desta região. As amostras selecionadas para este estudo foram obtidas por meio de Análise de Clusters, que classifica objetos (amostras) com base em suas semelhanças. Com a finalidade de obter a série dendrocronológica, aplicou-se o método estatístico Análise de Componentes Principais (do inglês Principal Component Analysis- PCA). Obtidas as Componentes Principais (Principal Componentes - PCs), reconstruiu-se as séries sem a 1ª PC, sendo uma estimativa da tendência que melhor representa o crescimento natural de todas as árvores do local. A média das séries sem a 1ª PC é a série dendrocronológica. O método de PCA traz diversas vantagens sobre o método tradicional de obtenção da série cronológica como o processamento rápido de dados, uma forma automatizada de remover a tendência natural de crescimento em todas as amostras ao mesmo tempo, e também, o fato de integrar uma ferramenta poderosa, o método dos mínimos quadrados alternados (do inglês Alternating Least Squares – ALS), para estimar ou recuperar falhas de dados.

O artigo visa o desenvolvimento de um novo algoritmo via Python para estudar eventos de Atividade Auroral Contínua do Índice AE (Eletrojato Auroral), de Grande Intensidade e Longa Duração, HILDCAAs e HILDCAAs* (no qual * corresponde ao fenômeno HILDCAA flexibilizado). Este algoritmo é baseado e validado por meio do algoritmo previamente desenvolvido por Prestes et al. (2017a) em MATLAB. O intuito deste novo algoritmo proposto aqui é tornar o fluxograma deste acessível a todos os usuários, além de complementar e atualizar o algoritmo em MATLAB já existente. Um importante aspecto é o fato da linguagem de programação de alto nível Python ser uma ferramenta gratuita. Ademais, o artigo também objetiva a comparação dos eventos encontrados no ano de 1998 neste trabalho com aqueles obtidos por Prestes et al. (2017a) e Guarnieri (2006). A nova flexibilização adotada aqui não tem a intensão de suprimir ou modificar a concepção original das HILDCAAs, mostra que os eventos encontrados aqui continuam associados aos fenômenos HSSs/CIRs (Feixes Rápidos do Vento Solar/Regiões de Interações Corrotantes).

Amostras do lenho de Araucaria angustifolia coletadas em Painel, no estado de Santa Catarina, foram analisadas em comparação com séries climatológicas locais, a fim de se conhecer a influência do clima no crescimento das árvores. Foram utilizadas séries de precipitação, temperatura e da evapotranspiração. O estudo aponta que as variáveis climatológicas influenciam no crescimento das árvores, porém atuam em conjunto, deixando claro que não são os valores extremos dessas variáveis que influenciam, mas sim o balanço entre elas que deixa o solo em condições favoráveis para o desenvolvimento dos vegetais. Na análise sazonal, ficou claro que o excesso de chuva pode ser prejudicial, porém, se atrelada a temperaturas mais elevadas, pode representar um auxílio no crescimento. A evapotranspiração local segue a tendência da temperatura e nos regimes sazonais mostrou que a influência conjunta da precipitação e da temperatura define seu grau de influência no crescimento das plantas. Não se descarta a hipótese de que uma cronologia mais robusta e com maior alcance temporal poderia elencar mais características do local. Mesmo assim, os resultados apontam que as plantas desse sítio são sensíveis ao clima local e podem ser utilizadas como registros naturais.

In this work, the Sun–Earth–climate relationship is studied using tree growth rings of Araucaria angustifolia (Bertol.) O. Kuntze collected in the city of Passo Fundo, located in the state of Rio Grande do Sul (RS), Brazil. These samples were previously studied by Rigozo et al. (2008); however, their main interest was to search for the solar periodicities in the tree-ring width mean time series without interpreting the rest of the periodicities found. The question arises as to what are the drivers related to those periodicities. For this reason, the classical method of spectral analysis by iterative regression and wavelet methods are applied to find periodicities and trends present in each tree-ring growth, in Southern Oscillation Index (SOI), and in annual mean temperature anomaly between the 24 and 44 ^∘ S. In order to address the aforementioned question, this paper discusses the correlation between the growth rate of the tree rings with temperature and SOI. In each tree-ring growth series, periods between 2 and 7 years were found, possibly related to the El Niño/La Niña phenomena, and a ∼ 23-year period was found, which may be related to temperature variation. These novel results might represent the tree-ring growth response to local climate conditions during its lifetime, and to nonlinear coupling between the Sun and the local climate variability responsible to the regional climate variations. Keywords.  History of geophysics (solar–planetary relationships) – meteorology and atmospheric dynamics (climatology; palaeoclimatology)