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Barca E, Bruno DE, Passarella G. Similarity indices of meteo-climatic gauging stations: definition and comparison. Environ Monit Assess. 2016;188(7):403doi: 10.1007/s10661-016-5407-z.
Barca, E., Bruno, D. E., & Passarella, G. (2016). Similarity indices of meteo-climatic gauging stations: definition and comparison. Environmental monitoring and assessment, 188(7), 403. https://doi.org/10.1007/s10661-016-5407-z
Barca, Emanuele, et al. "Similarity indices of meteo-climatic gauging stations: definition and comparison." Environmental monitoring and assessment vol. 188,7 (2016): 403. doi: https://doi.org/10.1007/s10661-016-5407-z
Barca E, Bruno DE, Passarella G. Similarity indices of meteo-climatic gauging stations: definition and comparison. Environ Monit Assess. 2016 Jul;188(7):403. doi: 10.1007/s10661-016-5407-z. Epub 2016 Jun 12. PMID: 27289471.
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Environ Monit Assess. 2016 Jul;188(7):403. doi: 10.1007/s10661-016-5407-z. Epub 2016 Jun 12.

Similarity indices of meteo-climatic gauging stations: definition and comparison.

Environmental monitoring and assessment

Emanuele Barca, Delia Evelina Bruno, Giuseppe Passarella

Affiliations

  1. Water Research Institute of the National Research Council (IRSA-CNR), Viale De Blasio, 5 -, 70125, Bari, Italy. [email protected].
  2. Water Research Institute of the National Research Council (IRSA-CNR), Viale De Blasio, 5 -, 70125, Bari, Italy.

PMID: 27289471 DOI: 10.1007/s10661-016-5407-z

Abstract

Space-time dependencies among monitoring network stations have been investigated to detect and quantify similarity relationships among gauging stations. In this work, besides the well-known rank correlation index, two new similarity indices have been defined and applied to compute the similarity matrix related to the Apulian meteo-climatic monitoring network. The similarity matrices can be applied to address reliably the issue of missing data in space-time series. In order to establish the effectiveness of the similarity indices, a simulation test was then designed and performed with the aim of estimating missing monthly rainfall rates in a suitably selected gauging station. The results of the simulation allowed us to evaluate the effectiveness of the proposed similarity indices. Finally, the multiple imputation by chained equations method was used as a benchmark to have an absolute yardstick for comparing the outcomes of the test. In conclusion, the new proposed multiplicative similarity index resulted at least as reliable as the selected benchmark.

Keywords: Missing data; Multiple imputation by chained equations (MICE); Similarity methods; Space-time series

References

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