Temporal scale influence on multifractal properties of agro-meteorological time series

Scale issues become very important when applying weather time series. We address problems associated with transferring meteorological data across time scales by comparing multifractal properties of hourly and daily meteorological time series. The multifractal detrended fluctuation approach revealed that temporal aggregation of agro-meteorological time series can impact on their multifractal properties. The most apparent evidence of changing the time scale on multifractal properties was found for precipitation. It was the least noticeable for the wind speed time series. The change from hourly to daily time scale had an effect on the long-range correlations and the broadness of the probability density function. The contribution of these two components to series multifractality was smaller than before data aggregation. Our results confirm the loss of unique multifractal features at daily time scale as compared to hourly time series.