R. Padulano, Giuseppe Francesco Cesare Lama, G. Rianna, M. Santini, M. Mancini, M. Stojiljković
{"title":"Future rainfall scenarios for the assessment of water availability in Italy","authors":"R. Padulano, Giuseppe Francesco Cesare Lama, G. Rianna, M. Santini, M. Mancini, M. Stojiljković","doi":"10.1109/MetroAgriFor50201.2020.9277599","DOIUrl":null,"url":null,"abstract":"This research aims at understanding and analyzing the possible effect of climate change on the seasonal rainfall regime over Italy. First, rainfall patterns are identified by applying a clustering procedure based on the Self-Organizing Map, by adopting and comparing the results of different gridded datasets describing current climate (1981-2010). Second, for the identified clusters the impact of climate change in the near (2021-2050) and the far future (2051-2080) is assessed by employing an ensemble of bias-adjusted EUROCORDEX climate projections under the Representative Concentration Pathways (RCP) 2.6, 4.5 and 8.5. The results of this study show that, for the considered models’ ensemble, a significant decrease in cumulative rainfall values should be expected in the future, reflecting in a decrease in monthly values across all the seasons.","PeriodicalId":124961,"journal":{"name":"2020 IEEE International Workshop on Metrology for Agriculture and Forestry (MetroAgriFor)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"8","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 IEEE International Workshop on Metrology for Agriculture and Forestry (MetroAgriFor)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/MetroAgriFor50201.2020.9277599","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 8
Abstract
This research aims at understanding and analyzing the possible effect of climate change on the seasonal rainfall regime over Italy. First, rainfall patterns are identified by applying a clustering procedure based on the Self-Organizing Map, by adopting and comparing the results of different gridded datasets describing current climate (1981-2010). Second, for the identified clusters the impact of climate change in the near (2021-2050) and the far future (2051-2080) is assessed by employing an ensemble of bias-adjusted EUROCORDEX climate projections under the Representative Concentration Pathways (RCP) 2.6, 4.5 and 8.5. The results of this study show that, for the considered models’ ensemble, a significant decrease in cumulative rainfall values should be expected in the future, reflecting in a decrease in monthly values across all the seasons.