Minimum temperature trend and its regression straight for Amparo de São Francisco – Sergipe, Brazil

• Autor(a) principal: Fança, Manoel Vieira de
• Data de Publicação: 2022
• Outros Autores: Medeiros, Raimundo Mainar de, Holanda, Romildo Morant de, Saboya, Luciano Marcelo Fallé, Sousa, Francisco de Assis Salviano
• Tipo de documento: Artigo
• Idioma: por
• Título da fonte: Research, Society and Development
• Texto Completo: https://rsdjournal.org/index.php/rsd/article/view/25633
• topic: Fluctuaciones térmicas; Climatología; Estadística descriptiva.; Flutuações térmicas; Climatologia; Estatística descritiva.; Thermal fluctuations; Climatology; Descriptive statistics.

Information on climate fluctuations in a given area is fundamental knowledge to improve family agricultural production, sustainable agriculture and the prevention of atmospheric phenomena. The objective is to analyze the minimum thermal distributions between 1963 and 2020, observe the possible behavior of linear trends, as well as the variability of the regression coefficient, taking into account the monthly evaluation of the years in order to identify the months with the highest and lowest thermal fluctuations , thus providing information regarding the spatial and temporal thermal variation in Amparo de São Francisco, Sergipe. We used the minimum thermal data estimated by the estima_T software between 1963-2020, and calculated the mean, standard deviation, coefficient of variance, maximum and minimum, absolute values, linear equation to define the equation of the straight line, R2, monthly, annual and seasonal. This study can be a tool for planning actions aimed at the best way to manage thermal indices to be used in agriculture, health, thermal comfort in cities, among other applications. The possibility of reductions in minimum temperatures to 20.4 °C could occur in the next five years with a 45% probability. This article aims to provide subsidies for designers, planners of adaptation and/or mitigation strategies of their possible negative impacts or take advantage of possible favorable climatic conditions.