Modeling hourly air temperature based on internationally agreed times and the daily minimum temperature

• Autor(a) principal: Radons,Sidinei Z.
• Data de Publicação: 2019
• Outros Autores: Heldwein,Arno B., Loose,Luís H., Bortoluzzi,Mateus P., Brand,Silvane I., Engers,Lana B. de O.
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Revista Brasileira de Engenharia Agrícola e Ambiental (Online)
• Texto Completo: http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1415-43662019001100807
• topic: meteorological data; sinusoidal and linear models; weather station

ABSTRACT There are several fields that require knowledge of air temperature variation throughout the day, such as disease prediction or calculation of chill-hours. However, automatic meteorological stations are not always located in the vicinity to accurately monitor this variable. In this sense, models that describe the daily temporal variation of air temperature can be used to meet this demand, and transform the climatic data series of conventional meteorological stations into an estimated hourly series. The aim of this study was to adjust and validate models for the hourly air temperature variation through data obtained at internationally agreed times (0, 12 and 18 h Universal Time Coordinated: UTC) and the daily minimum air temperature. The hourly database of the automatic station was used for model adjustment and validation. Functions were adjusted based on values measured at internationally agreed times and the daily minimum air temperature for certain daily variation patterns. The air temperature estimation was performed on an hourly basis using sinusoidal and linear models. The model that presented the lowest root mean square error (RMSE) was used for the estimation. The accuracy of the air temperature estimates varied according to the time, presenting RMSE from 0.7 to 1.6 °C, with maximum mean deviation of 0.4 °C. The results of this study showcase the necessity of knowledge of the daily air temperature variation, as well as a series of data from conventional meteorological stations, which can be estimated using hourly models.