Scheda di dettaglio – i prodotti della ricerca
| Dato | Valore |
|---|---|
| Title | Similarity indices of meteo-climatic gauging stations: definition and comparison |
| 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. |
| Source | Environmental monitoring and assessment (Print) 188 (7) |
| Keywords | Similarity methodsMissing dataSpace-time seriesMultiple imputation by chained equations (MICE) |
| Journal | Environmental monitoring and assessment (Print) |
| Editor | Kluwer Academic Publishers, London, Paesi Bassi |
| Year | 2016 |
| Type | Articolo in rivista |
| DOI | 10.1007/s10661-016-5407-z |
| Authors | Barca, Emanuele; Bruno, Delia Evelina; Passarella, Giuseppe |
| Text | 359978 2016 10.1007/s10661 016 5407 z ISI Web of Science WOS 000378840300020 Scopus 2 s2.0 84975721250 SpringerLink http //link.springer.com/article/10.1007/s10661 016 5407 z PubMed 27289471 Similarity methods Missing data Space time series Multiple imputation by chained equations MICE Similarity indices of meteo climatic gauging stations definition and comparison Barca, Emanuele; Bruno, Delia Evelina; Passarella, Giuseppe National Research Council IRSA CNR 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. 188 Published version http //link.springer.com/article/10.1007/s10661 016 5407 z Barca, E., Bruno, D.E. Passarella, G. Environ Monit Assess 2016 188 403. doi 10.1007/s10661 016 5407 z 06/06/2016 Similarity indices of meteo climatic gauging stations definition and comparison Barca et al. EMAS 2016 02.pdf Articolo in rivista Kluwer Academic Publishers 0167 6369 Environmental monitoring and assessment Print Environmental monitoring and assessment Print Environ. monit. assess. Print Environmental monitoring and assessment. Print giuseppe.passarella PASSARELLA GIUSEPPE emanuele.barca BARCA EMANUELE deliaevelina.bruno BRUNO DELIA EVELINA TA.P04.005.008 Integrazione di metodologie per il monitoraggio e la modellizzazione per la gestione delle risorse idriche |