Application of Benford's law in monthly series of precipitation
DOI:
https://doi.org/10.55761/abclima.v37i21.19740Keywords:
Data quality control, Gap filling, Goodness of fit test, Logarithmic distributionAbstract
Benford's Law describes a logarithmic distribution of leading digits in real-world data, with smaller digits occurring more frequently than larger ones. Accordingly, this study investigated the application of this law to monthly precipitation series recorded at nine automatic weather stations in the state of Espírito Santo, Brazil, from 2006 to 2023. The objective was to assess the conformity of the data with the theoretical distribution predicted by Benford's Law, both in the original data and after filling gaps in the series. Two gap-filling methods were used: the average of the same months from other years with data and linear interpolation. Adherence to Benford's Law was verified using the Chi-square test, comparing the observed distribution of the first and second digits with the expected theoretical pattern. The results indicated that the original precipitation series adheres to Benford's Law, suggesting the reliability of the records. Gap-filling with the average altered the digit distribution, particularly for the second digit, compromising this conformity. In contrast, linear interpolation preserved the numerical pattern and adherence to the law. It is concluded, therefore, that Benford's Law has the potential to assess the quality of precipitation series, and linear interpolation is recommended for treating missing data when it is necessary to preserve the initial natural distribution of the data.
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