Experiences with data quality control and homogenization of daily records of various meteorological elements in the Czech Republic in the period 1961–2010

0395964 - ÚVGZ 2014 RIV HU eng J - Journal Article
Štěpánek, Petr - Zahradníček, Pavel - Farda, Aleš
Experiences with data quality control and homogenization of daily records of various meteorological elements in the Czech Republic in the period 1961–2010.
Idöjárás. Quarterly journal of the Hungarian meteorological society. Roč. 117, č. 1 (2013), s. 123-141. ISSN 0324-6329. E-ISSN 0324-6329
R&D Projects: GA MŠMT(CZ) ED1.1.00/02.0073; GA ČR(CZ) GAP209/10/0605
Institutional support: RVO:67179843
Keywords : data quality control * homogenization * statistical correction of inhomogeneities * daily data processing * climatological time series
Subject RIV: DG - Athmosphere Sciences, Meteorology
Impact factor: 0.405, year: 2013

Quality control and homogenization has to be undertaken prior to any data analyses in order to eliminate any erroneous values and non-climatic biases in time series. In recent years, considerable attention was paid to daily data since it can serve, among other conventional climatological analyses, as non-biased input into extreme value analysis, correction of RCM outputs, etc. In this work, we describe and then apply our own approach to data quality control of station measurements, combining several methods: (i) by analyzing difference series between candidate and neighboring stations, (ii) by applying limits derived from interquartile ranges, and (iii) by comparing the series values tested with “expected” values – technical series created by means of statistical methods for spatial data (e.g., IDW, kriging). Because of the presence of noise in series, statistical homogeneity tests render results with some degree of uncertainty. In this work, the use of various statistical tests and reference series made it possible to increase considerably the number of homogeneity test results for each series and, thus, to assess homogeneity more reliably. Inhomogeneities were corrected on a daily scale. In the end, missing values were filled applying geostatistical methods; thus, the so-called technical series for stations were constructed, which can finally be used as quality input into further time series analysis. These methodological approaches are applied to daily data, for various meteorological elements within the area of the Czech Republic in the period 1961–2010, which allows demonstrate their usefulness. Series were processed by means of the developed ProClimDB and AnClim softwares (http://www.climahom.eu).
Permanent Link: http://hdl.handle.net/11104/0223880