1,721,054 research outputs found

    Certified accuracy of rainfall data as a standard requirement in scientific investigations.

    No full text
    This paper elaborates on the rationale behind the proposed standard limits for the accuracy of rainfall intensity measurements obtained from tipping-bucket and other types of rain gauges. Indeed, based on experimental results obtained in the course of international instrument Intercomparison initiatives and specific laboratory tests, it is shown here that the accuracy of operational rain gauges can be reduced to the limits of ±1% after proper calibration and correction. This figure is proposed as a standard accuracy requirement for the use of rain data in scientific investigations. This limit is also proposed as the reference accuracy for operational rain gauge networks in order to comply with quality assurance systems in meteorological observations

    Non-parametric error distribution analysis from the laboratory calibration of various rainfall intensity gauges

    No full text
    The analysis of counting and catching errors of both catching and non-catching types of rain intensity gauges was recently possible over a wide variety of measuring principles and instrument design solutions, based on the work performed during the recent Field Intercomparison of Rainfall Intensity Gauges promoted by World Meteorological Organization (WMO). The analysis reported here concerns the assessment of accuracy and precision of various types of instruments based on extensive calibration tests performed in the laboratory during the first phase of this WMO Intercomparison. The non-parametric analysis of relative errors allowed us to conclude that the accuracy of the investigated RI gauges is generally high, after assuming that it should be at least contained within the limits set forth by WMO in this respect. The measuring principle exploited by the instrument is generally not very decisive in obtaining such good results in the laboratory. Rather, the attention paid by the manufacturer to suitably accounting and correcting for systematic errors and time-constant related effects was demonstrated to be influential. The analysis of precision showed that the observed frequency distribution of relative errors around their mean value is not indicative of an underlying Gaussian population, being much more peaked in most cases than can be expected from samples extracted from a Gaussian distribution. The analysis of variance (one-way ANOVA), assuming the instrument model as the only potentially affecting factor, does not confirm the hypothesis of a single common underlying distribution for all instruments. Pair-wise multiple comparison analysis revealed cases in which significant differences could be observed
    corecore