Teleconnection-informed frequency analysis of rainfall extremes

Código

I-EBHE0029

Autores

Andrea Magnini, Valentina Pavan, Attilio Castellarin

Tema

WG 1.10: Hydrologic Design - Solutions & Communication

Resumo

A growing number of scientific contributions reports on strong relationships between global climatic indexes (or teleconnections) and precipitation across diverse geographical regions worldwide. Some studies investigate the use of selected teleconnections as covariates when modeling the frequency regime of rainfall annual maxima (e.g., Ragno et al., 2018, Ouarda et al., 2019). Typically, they are based on a few single time series, that are often sparse in space. However, the presence of regional structures in the dependency of rainfall annual maxima on teleconnections is still poorly explored. This study provides a comprehensive assessment of the informative content of teleconnections for representing and modeling the frequency regime of rainfall extremes at regional scale. The study area is a large and climatically diverse region in Northern Italy. Our dataset consists of approximately 700 annual maximum series (AMS) of sub-daily (i.e., 1 and 24 hours durations) rainfall depth, recorded between 1921 and 2022. Based on relevant previous literature (e.g., Caroletti et al., 2021; Romano et al., 2021), we select six global climate indexes: the North Atlantic Oscillation (NAO), Pacific Decadal Oscillation (PDO), East Atlantic ? West Russia pattern (EA-WR), El Niño Southern Oscillation (ENSO), Mediterranean Oscillation Index (MOI), and Western Mediterranean Oscillation Index (WeMOI). Instead of considering the raw AMS, we define sliding time windows in order to obtain time series of L-moments, which characterize the distribution of sub-daily rainfall extremes. Then, we evaluate the correlation of teleconnections with time series of spatially gridded L-moments. In analyzing the spatial patterns of gridded L-moments, we consider a discretization of the study region into tiles with resolutions up to 100 km. Finally, we show a preliminary application of climate-informed regional frequency analysis of rainfall extremes, where the L-moments are modelled as functions of WeMOI. We selected WeMOI as it shows a notably higher number of significant correlations with the statistics of sub-daily rainfall maxima than the other teleconnections. Moreover, the relationship between WeMOI and L-moments of sub-daily extreme rainfall show clear spatial patterns across the study area, whose robustness is confirmed by their limited sensitivity to the chosen grid resolution. Overall, our research suggests promising pathways for climate-informed local and regional frequency analysis of rainfall extremes. References Caroletti, G.N., Coscarelli, R., Caloiero, T., 2021. A sub?regional approach to the influence analysis of teleconnection patterns on precipitation in Calabria (southern Italy). Intl Journal of Climatology 41, 4574?4586. https://doi.org/10.1002/joc.7087 Ouarda, T.B.M.J., Yousef, L.A., Charron, C., 2019. Non?stationary intensity?duration?frequency curves integrating information concerning teleconnections and climate change. Intl Journal of Climatology 39, 2306?2323. https://doi.org/10.1002/joc.5953 Ragno, E., AghaKouchak, A., Love, C.A., Cheng, L., Vahedifard, F., Lima, C.H.R., 2018. Quantifying Changes in Future Intensity?Duration?Frequency Curves Using Multimodel Ensemble Simulations. Water Resources Research 54, 1751?1764. https://doi.org/10.1002/2017WR021975 Romano, E., Petrangeli, A.B., Salerno, F., Guyennon, N., 2022. Do recent meteorological drought events in central Italy result from long?term trend or increasing variability? Intl Journal of Climatology 42, 4111?4128. https://doi.org/10.1002/joc.7487