Verifying Trends in Extreme Rainfall in Italy through a New Comprehensive Database
Abstract
Climate change and its influence on the spatio-temporal distribution of rainfall is a hot topic in the hydro-climatologic literature. Many studies aimed at detecting trends in the magnitude of extreme rainfall across the world have been published, adopting different statistical techniques to evaluate the possible nonstationary behavior of different precipitation dataset at different time scales and spatial resolutions. From this point of view, Italy turns out to be a challenging case study, due to its climatologic and orographic variability and to the administrative fragmentation of the national hydrological monitoring network, that led to many different local studies providing conflicting outcomes about the presence of change in extreme rainfall magnitudes. This work aims at exploiting the potentialities of the I-RED, the first national dataset of annual maxima for sub-daily durations, for assessing a national framework of the changes in the extreme rainfall regime in the last decades. At first, a preliminary analysis at the national level is carried out, adopting consolidated methodologies for trend detection (e.g., Mann-Kendall and Sen's slope techniques) and advanced techniques aimed at limiting the influence of the growing monitoring network on the outcomes (e.g., quantile regression). Despite the presence of both upward and downward trends, results seem to suggest that most of them are not significant when the whole country is considered, and compatible with a stationary climate. The same techniques are then applied considering different spatial aggregations, in order to analyse the impact of the uneven distribution of the monitoring network on the results. The presence of trends in the frequency of record breaking rainfall at the single-station and aggregated levels is also explored. Results seems to underline the significant influence of the configuration of the monitoring network on the detection of trends, providing evidence of the importance of considering carefully the study cases setting for making these kind of analysis effective and robust.
- Publication:
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AGU Fall Meeting Abstracts
- Pub Date:
- December 2018
- Bibcode:
- 2018AGUFM.H51L1460C
- Keywords:
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- 1817 Extreme events;
- HYDROLOGYDE: 1821 Floods;
- HYDROLOGYDE: 1833 Hydroclimatology;
- HYDROLOGYDE: 1860 Streamflow;
- HYDROLOGY