Statistical methods to detect trends in historical climate data: bibliographic review

Authors

  • Louise Pereira Silva Engenheira de energias renováveis, doutoranda do curso de pós-graduação em Engenharia Mecânica, João Pessoa, PB.
  • Paula Rose de Araújo Santos Engenheira ambiental, doutoranda do curso de pós-graduação em Engenharia Mecânica. João Pessoa, PB.
  • Giusep Magno da Silva Ribeiro Graduando pelo curso de Engenharia de Energias Renováveis, João Pessoa, PB.
  • Susane Eterna Leite Medeiros Bacharel em Física Computacional, doutoranda do curso de pós-graduação em Física, João Pessoa, PB.
  • Wallysson Klebson de Medeiros Silva Bacharel em Administração, doutorando do curso de pós-graduação em Administração, João Pessoa, PB.
  • Raphael Abrahão Engenheiro agrícola, doutor em Engenharia Química e Ambiental, professor do Departamento de Engenharia de Energias Renováveis da Universidade Federal da Paraíba (UFPB), João Pessoa, PB.

DOI:

https://doi.org/10.35977/0104-1096.cct2022.v39.26929

Keywords:

historical data, climate change, climate parameters

Abstract

In this work, a systematic review was carried out, using keywords, through the scientific research databases of Science Direct and Web of Science, approaching the statistical methods used to assess trends in historical climate data. Among the articles obtained in this selection, a study was found in Brazil, which analyzed trends in climate parameters, evaluating the impact on the energy sector, in a small hydroelectric power plant and in a solar plant. Linear regression and the nonparametric Mann-Kendall test, associated with the Sen’s slope, were the most used statistical methods in the analysis of historical climate trends. Compared to others, these tests are less influenced by the presence of outliers. The most studied climatic parameters were precipitation and air temperature. It was noticed that few articles addressed climate trends in combination with impacts on the energy sector, especially those based on renewable resources, which are the most susceptible to climate change, opening a gap for further studies along this line.

Downloads

Published

2022-05-19

How to Cite

Silva, L. P., Santos, P. R. de A., Ribeiro, G. M. da S., Medeiros, S. E. L., Silva, W. K. de M., & Abrahão, R. (2022). Statistical methods to detect trends in historical climate data: bibliographic review. Science & Technology Journals, 39(1), e26929. https://doi.org/10.35977/0104-1096.cct2022.v39.26929

Issue

Vol. 39 No. 1 (2022)

Section

Artigos

License

After publication of the work, the Authors are authorized to non-exclusively distribute the version of the published work (for example: publish in an institutional repository, as a book chapter, create links on electronic pages, etc.), as long as the authorship and initial publication in this journal are mentioned.