Correction of Precipitation Data in Weather Files for the Subtropical Climate in Southern Brazil
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Keywords

Weather files
Building energy simulations
Test Reference Year
Typical Meteorological Year

How to Cite

BULIGON, L. B.; GABRIEL, E.; LIMA, S. F. S.; GRIGOLETTI, G. C.; PICCILLI, D. G. A. Correction of Precipitation Data in Weather Files for the Subtropical Climate in Southern Brazil. Sociedade & Natureza, [S. l.], v. 35, n. 1, 2023. DOI: 10.14393/SN-v35-2023-67645. Disponível em: https://seer.ufu.br/index.php/sociedadenatureza/article/view/67645. Acesso em: 21 jun. 2024.

Abstract

The thermal performance of buildings can be evaluated prior to its construction by modeling it using a specialized software. Climate boundary conditions must be represented by a weather file that is composed of a weather dataset organized hourly according to a defined year structure such as Test Reference Year (TRY) or Typical Meteorological Year (TMY). Before this study, there were a few weather files available for cities in southern Brazil, notably, Santa Maria, RS, classified as a humid subtropical climate. The most recent available weather file was built in 2014 and presents inconsistencies with respect to precipitation data. Therefore, the objetive of this study was to process and analyze the climate data of Santa Maria over an eighteen-year period (2002-2020), to generate a more reliable weather file. The applied method considered the following procedures: data collection and processing; TRY (TRY17) and TMY2 (TMY0220) definition; solar radiation data calculation; EPW files generation; and comparison between the new EPW files and the previous existing files. As a result, in a short period of time (2014-2020), significant differences among the weather files were observed. The importance of updating weather files in time intervals shorter than 30 years was emphasized. In relation to the comparative analysis, both weather files (TRY17 and TMY0220) presented dry bulb temperatures in consonance with the other files previously available. Although, the correction of precipitation data could originate building simulations closer to the reality.

https://doi.org/10.14393/SN-v35-2023-67645
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Copyright (c) 2022 Liliane Bonadiman Buligon, Elaíse Gabriel, Selton Fernandes Sousa Lima, Giane Grigoletti, Daniel Gustavo Allasia Piccilli

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