Abstract
This paper explores climate changes in Italy over the last 30 years. The data come from the European observation gridded dataset and are concerned with the temperature throughout the country. We focus our attention on two Italian regions (Lombardy in northern Italy and Campania in southern Italy) and on two particular years roughly thirty years apart (1986 and 2015). Our primary aim is to assess the most important changes in temperature in Italy using some variants of correspondence analysis for ordered categorical variables. Such variants are based on a decomposition method using orthogonal polynomials instead of singular vectors and allow one to easily classify the meteorological station observations. A simulation study, based on bootstrap sampling, is undertaken to demonstrate the reliability of the results.
Highlights
For over a century the scientific community has undertaken a huge amount of research focusing on the many aspects of climate change, which remains one of the most challenging problems that humanity shall face in the immediate future
To analyze the association between the months that span over time and classes formed from the temperature change, we consider two recent methodologies, both of which are based on orthogonal polynomials for categorical variables [24,25,26,27]
After performing ordered multiple correspondence analysis for classifying the meteorological stations of two specific years (1986 and 2015) in different classes we perform doubly ordered correspondence analysis to highlight those months that are mainly associated with higher temperature values
Summary
For over a century the scientific community has undertaken a huge amount of research focusing on the many aspects of climate change, which remains one of the most challenging problems that humanity shall face in the immediate future. No studies exist that demonstrate the utility of correspondence analysis for investigating climate change in Italy This, it seems, is primarily because the focus of analyzing such changes has involved time series modeling of temperature or precipitation for which suitable predictive models exist in the literature [12,13,14,15]. In this paper some climatological investigations are carried out using two variants of ordered correspondence analysis [20,21] for providing an automatic classification of meteorological stations with respect to classes of temperature that have been observed monthly during the first and last year of reference, i.e., 1986 and 2015.
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
