TY - JOUR
T1 - A simplified MEV formulation to model extremes emerging from multiple nonstationary underlying processes
AU - Marra, Francesco
AU - Zoccatelli, Davide
AU - Armon, Moshe
AU - Morin, Efrat
N1 - Publisher Copyright:
© 2019 Elsevier Ltd
PY - 2019/5
Y1 - 2019/5
N2 - This paper presents a Simplified Metastatistical Extreme Value formulation (SMEV) able to model hydro-meteorological extremes emerging from multiple underlying processes. The formulation explicitly includes the average intensity and probability of occurrence of the processes allowing to parsimoniously model changes in these quantities to quantify changes in the probability of occurrence of extremes. SMEV allows (a) frequency analyses of extremes emerging from multiple underlying processes and (b) computationally efficient analyses of the sensitivity of extreme quantiles to changes in the characteristics of the underlying processes; moreover, (c) it provides a robust framework for explanatory models, nonstationary frequency analyses, and climate projections. The methodology is applied to daily precipitation data from long recording stations in the eastern Mediterranean, using Weibull distributions to model daily precipitation amounts generated by two classes of synoptic systems. At-site application of SMEV provides spatially consistent estimates of extreme quantiles, in line with regional GEV estimates and generally characterized by reduced uncertainties. The sensitivity of extreme quantiles to changes and uncertainty in the intensity and yearly occurrences of events generated by different synoptic classes is examined, and an application of SMEV for the projection of future extremes is provided.
AB - This paper presents a Simplified Metastatistical Extreme Value formulation (SMEV) able to model hydro-meteorological extremes emerging from multiple underlying processes. The formulation explicitly includes the average intensity and probability of occurrence of the processes allowing to parsimoniously model changes in these quantities to quantify changes in the probability of occurrence of extremes. SMEV allows (a) frequency analyses of extremes emerging from multiple underlying processes and (b) computationally efficient analyses of the sensitivity of extreme quantiles to changes in the characteristics of the underlying processes; moreover, (c) it provides a robust framework for explanatory models, nonstationary frequency analyses, and climate projections. The methodology is applied to daily precipitation data from long recording stations in the eastern Mediterranean, using Weibull distributions to model daily precipitation amounts generated by two classes of synoptic systems. At-site application of SMEV provides spatially consistent estimates of extreme quantiles, in line with regional GEV estimates and generally characterized by reduced uncertainties. The sensitivity of extreme quantiles to changes and uncertainty in the intensity and yearly occurrences of events generated by different synoptic classes is examined, and an application of SMEV for the projection of future extremes is provided.
KW - Climate change
KW - Daily precipitation
KW - Extreme value analysis
KW - Metastatistical extreme value
KW - Nonstationary processes
UR - http://www.scopus.com/inward/record.url?scp=85063991138&partnerID=8YFLogxK
U2 - 10.1016/j.advwatres.2019.04.002
DO - 10.1016/j.advwatres.2019.04.002
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AN - SCOPUS:85063991138
SN - 0309-1708
VL - 127
SP - 280
EP - 290
JO - Advances in Water Resources
JF - Advances in Water Resources
ER -