The potential for climate catastrophes, represented by 'fat-tailed' distributions on consequences, has attracted much attention recently. To date, however, most integrated assessment models have either been largely deterministic or deterministic with ex-post sensitivity analysis. The conclusions...

We present a novel approach for practically tackling uncertainty in preference elicitation and predictive modeling to support complex multi-criteria decisions based on multi-attribute utility theory (MAUT). A simplified two-step elicitation procedure consisting of an online survey and...

A generic algorithmic framework for nonlinear ensemble filtering based on Gaussian mixtures and fuzzy clustering techniques is introduced. The framework generalizes the ensemble Kalman filter and relaxes the assumption of a Gaussian prediction distribution. A theoretical analysis of the proposed...

type="main" xml:id="rssb12061-abs-0001" <title type="main">Summary</title> <p>Increasingly larger data sets of processes in space and time ask for statistical models and methods that can cope with such data. We show that the solution of a stochastic advection–diffusion partial differential equation provides a flexible...</p>

Paleoclimate evidence and climate models indicate that certain elements of the climate system may exhibit thresholds, with small changes in greenhouse gas emissions resulting in non-linear and potentially irreversible regime shifts with serious consequences for socio-economic systems. Such...

We study the dependence on initial conditions of two recursive filters for cleaning a contaminated time series from additive outliers. We show that the function in the recursive equation is in general not contractive, but nevertheless there exists a stationary solution and two iterates with...