2018
DOI: 10.1002/joc.5836
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Filling missing meteorological data in heating and cooling seasons separately

Abstract: Hourly weather data are needed for building energy calculations; however, many available data from previous years are 3-hr-based. Therefore, appropriate interpolation methods should be employed in order to fill the gaps of the data. In this paper, linear and cubic spline functions are used to interpolate the weather data of Kerman, Iran. Weather data have different behaviours in heating and cooling seasons. Therefore, this paper analyses the interpolation methods in heating and cooling seasons separately. In o… Show more

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Cited by 7 publications
(5 citation statements)
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“…Many studies are currently underway to find methods for filling in the regular time gaps in meteorological data [42][43][44]. "Regular gaps" refer to the 2-h-long gaps in 3-h data [42].…”
Section: Study Of Methods For Converting Temporal Resolutions To High...mentioning
confidence: 99%
See 3 more Smart Citations
“…Many studies are currently underway to find methods for filling in the regular time gaps in meteorological data [42][43][44]. "Regular gaps" refer to the 2-h-long gaps in 3-h data [42].…”
Section: Study Of Methods For Converting Temporal Resolutions To High...mentioning
confidence: 99%
“…Many studies are currently underway to find methods for filling in the regular time gaps in meteorological data [42][43][44]. "Regular gaps" refer to the 2-h-long gaps in 3-h data [42]. Previous studies have attempted to use linear interpolation, Lagrange interpolation, spline interpolation, and so on as methods to fill in these time gaps.…”
Section: Study Of Methods For Converting Temporal Resolutions To High...mentioning
confidence: 99%
See 2 more Smart Citations
“…For this purpose, the thermal energy demands of two reference residential buildings in Madrid based on meteorological parameters of the last forty years, twenty years and ten years were investigated. Anjomshoaa A. and Salmanzadeh M. [4] investigated the effects of air psychrometric properties such as temperature, pressure, humidity and relative humidity on the calculation of energy consumption of buildings. Pappaccogli G. et al [38] simulated the energy consumption of a building in Bolzano, Italy, under various meteorological conditions.…”
mentioning
confidence: 99%