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| Flumignan,Danilton L.; Rezende,Maiara K. A.; Comunello,Eder; Fietz,Carlos R.. |
| ABSTRACT Net radiation (Rn) of reference surface is important information that has many applications, but its measurement is rare due to the high cost of the sensor and the complexity involved on the measurement. Therefore, estimate Rn from another variable is desirable, as from solar radiation (Rs); however, standard methods used are complex, making interesting the use of simplified methodologies. Considering these aspects, the present study aimed to set two empirical methods to estimate Rn from Rs for Dourados region, Mato Grosso do Sul, Brazil. One method was based on mathematical modeling (Gauss Method). The other one was a more simplified and practical approach (Practical Method) comprising the determination of fixed monthly conversion factors. It was... |
| Tipo: Info:eu-repo/semantics/article |
Palavras-chave: Weather station; Gauss Method; Practical Method; Reference evapotranspiration. |
| Ano: 2018 |
URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0100-69162018000100032 |
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| Radons,Sidinei Z.; Heldwein,Arno B.; Loose,Luís H.; Bortoluzzi,Mateus P.; Brand,Silvane I.; Engers,Lana B. de O.. |
| 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... |
| Tipo: Info:eu-repo/semantics/article |
Palavras-chave: Meteorological data; Sinusoidal and linear models; Weather station. |
| Ano: 2019 |
URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S1415-43662019001100807 |
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