The daily air temperature and precipitation records of four meteorological observation stations over China are used to investigate the differences of scaling property employing the detrended fluctuation analysis (DFA) method. The results show that the values in DFA-exponent for temperature are higher than those for precipitation compared by different orders DFA1–3. A 95% significance test is also applied to verify LRCs by resampling the temperature and precipitation records 10000 times in Beijing. The values of scaling exponent from original temperature and precipitation records are larger than the upper range value of the interval threshold after shuffling the data records, which implies there are positive LRCs. For temperature records, the value of scaling exponent calculated by FA is greater than those by DFA1–3 at all four stations. This indicates that the FA curve overestimates the scaling behavior due to the effect of trends. By contrast, the values of scaling exponent in precipitation are almost the same by using FA and DFA1–3 for all time scales, respectively. Furthermore, there are crossovers on short time scales in different orders DFA1–3 for the temperature records, while the slopes keep almost consistent on all time scales for the precipitation records.
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