167 citations · 386 across the 9 of their papers we have counts for
9 papers
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…
Exabel's Factor Model
Øyvind Grotmol, Michael Scheuerer, Kjersti Aas +1
Factor models have become a common and valued tool for understanding the risks associated with an investing strategy. In this report we describe Exabel's factor model, we quantify…
Performance evaluation of volatility estimation methods for Exabel
Øyvind Grotmol, Martin Jullum, Kjersti Aas +1
Quantifying both historic and future volatility is key in portfolio risk management. This note presents and compares estimation strategies for volatility estimation in an estimatio…
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…
Probabilistic wind speed forecasting on a grid based on ensemble model output statistics
Michael Scheuerer, David Möller
Probabilistic forecasts of wind speed are important for a wide range of applications, ranging from operational decision making in connection with wind power generation to storm war…
Spatial postprocessing of ensemble forecasts for temperature using nonhomogeneous Gaussian regression
Kira Feldmann, Michael Scheuerer, Thordis L. Thorarinsdottir
Statistical postprocessing techniques are commonly used to improve the skill of ensembles of numerical weather forecasts. This paper considers spatial extensions of the well-establ…
Assessing the calibration of high-dimensional ensemble forecasts using rank histograms
Thordis L. Thorarinsdottir, Michael Scheuerer, Christopher Heinz
Any decision making process that relies on a probabilistic forecast of future events necessarily requires a calibrated forecast. This paper proposes new methods for empirically ass…
Probabilistic Quantitative Precipitation Forecasting Using Ensemble Model Output Statistics
Michael Scheuerer
Statistical post-processing of dynamical forecast ensembles is an essential component of weather forecasting. In this article, we present a post-processing method that generates fu…
Spatially adaptive post-processing of ensemble forecasts for temperature
Michael Scheuerer, Luca Büermann
We propose an extension of the non-homogeneous Gaussian regression (NGR) model by Gneiting et al. (2005) that yields locally calibrated probabilistic forecasts of tem- perature, ba…