Faculty of Informatics
Università della Svizzera italiana
Via Giuseppe Buffi 13
Data-Based Spatio-Temporal Analysis of Extreme Events
Extreme events like sample maxima or threshold excesses define the outliers of a process. Examples can be found in various fields: heavy precipitations and heat waves in meteorological systems, earthquakes in geology and financial crashes in economics. Data-driven modeling of extremes is essential for reducing their negative social and financial losses. This project focuses on understanding the dependence, occurrence, and intensity of spatio-temporal extremes in presence of for systematically missing (unresolved) information.
Statistical Modeling of Atmospherical Gravity Waves
Atmospherical gravity waves contribute signicantly to the middle atmospheric circulation, structure and variability. While rographic and convective gravity waves are well understood and parametrized, a parametrization of gravity waves of low frequencies, often denoted as inertiagravity waves (IGWs), from jets and fonts is still missing. The dynamics of IGWs emission is a part of a complex process which involves multiple spatio/temporal multiscale processes, thus the parametrization of spontaneous IGW emission is a challenging task.
Being part of the SNF project 156398 "MSGWaves" our aim is the stochastic parametrization of the multiscale dynamics of IGWs. Thereby, Finite Element Methodology (FEM) for nonstationary, non-homogenous and non-parametric time series analysis developed at the research group Computational Time Series Analysis at the University della Svizzera Italiana will be extended towards multiscale modeling of IGWs.
O. Kaiser and I. Horenko. Data-driven spatio-temporal modeling of threshold excesses with unresolved covariates. Submitted to Water Research Journal, 2015.
O.Kaiser, Data-based abalysis of extreme events: inferecen, numerics, applications, Ph.D. Thesis, 2015.
O.Kaiser, D.Igdalov and I.Horenko, Statistical regression analysis of threshold excesses with systematically missing covariates, Multiscale Model. Simul., 13(2), 594-613, 2015.
O. Kaiser and I. Horenko, On inference of statistical regression models for extreme events based on incomplete observation data, Communications in Applied Mathematics and Computational Science 9(1), 2014
O.Kaiser and I.Horenko, Statistical regression analysis of exceedances over a high threshold based on incomplete observtion data, International conference on Time Series, 2014