Filling missing daily data in records of climatological time series
DOI:
https://doi.org/10.29312/remexca.v13i4.2514Keywords:
Fourier series, missing data, normal ratio, square of the inverse of the distanceAbstract
The lack of daily data in weather stations is frequent and this does not allow the series to be used in agroclimatic studies. With the above, the temporal and spatial variation of the variables that make up the agroclimate of a region is not known. The objective of this work was to estimate and verify by means of the methods: normal ratio, Fourier series and square of the inverse of the distance, the method with the least error for the filling of missing daily data of the variables: precipitation, solar brightness, evaporation, maximum temperature, minimum temperature and relative humidity of the weather stations surrounding the rice production area in the department of Valle del Cauca, Colombia. Nine stations were analyzed, which do not present distances greater than 50 km, nor altitudinal differences of more than 750 m. These were used with different study periods according to the variable in progress and the methods were evaluated with the statistical indices: root mean square error and coefficient of determination, the first allowed knowing the maximum admissible value of error and the second, the level of adjustment between the observed and the estimated values. Therefore, these allowed inferring that the variable solar brightness and evaporation obtained the best results with the normal ratio; the minimum temperature and relative humidity with the Fourier series and the square of the inverse of the distance for precipitation and maximum temperature.
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