Reliable projections of extremes by climate models are becoming increasingly important in
the context of climate change and associated societal impacts. Extremes are by definition …

Geostatistical models have traditionally been stationary. However, physical knowledge
about underlying spatial processes often requires models with non-stationary dependence …

The objective of the present document is to provide a handy tool for policy makers to whom
the background science may not be immediately accessible. The report starts with a …

Climate change will affect the insurance industry. We develop a Bayesian hierarchical
statistical approach to explain and predict insurance losses due to weather events at a local …

Northern latitudes are experiencing faster warming than other regions in the world, which is
partly explained by the snow albedo feedback. In Norway, mean temperatures have been …

Dynamical downscaling (DDS) is performed using regional climate models (RCMs) with
global atmospheric states as the input, but there is no consensus among researchers on …

A new statistical downscaling method was developed and applied to downscale monthly
total precipitation from 583 stations in China. Generally, there are two steps involved in …

Estimation of stationary dependence structure parameters using only a single realisation of
the spatial process, typically leads to inaccurate estimates and poorly identified parameters …

Extreme precipitation can cause flooding, result in substantial damages and have
detrimental effects on ecosystems,. Climate adaptation must therefore account for the …

This is the first study to determine the density of questing Ixodes ricinus in northern Norway.
It was performed at two sites in Brønnøy, which has been known for its tick permissive …