2 citations · 5 across the 6 of their papers we have counts for
6 papers
Combining predictive distributions for time-to-event outcomes in meteorology
Céline Cunen, Thea Roksvåg, Claudio Heinrich-Mertsching +1
Combining forecasts from multiple numerical weather prediction (NWP) models have shown substantial benefit over the use of individual forecast products. Although combination, in a…
Applications of machine learning to predict seasonal precipitation for East Africa
Michael Scheuerer, Claudio Heinrich-Mertsching, Titike K. Bahaga +2
Seasonal climate forecasts are commonly based on model runs from fully coupled forecasting systems that use Earth system models to represent interactions between the atmosphere, oc…
Probabilistic prediction of the time to hard freeze using seasonal weather forecasts and survival time methods
Thea Roksvåg, Alex Lenkoski, Michael Scheuerer +2
Agricultural food production and natural ecological systems depend on a range of seasonal climate indicators that describe seasonal patterns in climatological conditions. This pape…
Assessing present and future risk of water damage using building attributes, meteorology and topography
Claudio Heinrich-Mertsching, Jens Christian Wahl, Alba Ordonez +4
Weather-related risk makes the insurance industry inevitably concerned with climate and climate change. Buildings hit by pluvial flooding is a key manifestation of this risk, givin…
Validation of point process predictions with proper scoring rules
Claudio Heinrich-Mertsching, Thordis L. Thorarinsdottir, Peter Guttorp +1
We introduce a class of proper scoring rules for evaluating spatial point process forecasts based on summary statistics. These scoring rules rely on Monte-Carlo approximations of e…
Is the mode elicitable relative to unimodal distributions?
Claudio Heinrich-Mertsching, Tobias Fissler
Statistical functionals are called elicitable if there exists a loss or scoring function under which the functional is the optimal point forecast in expectation. While the mean and…