Overview of Case Studies#
The PhD students who participate in the Uncertainty Quantification project write articles about their current research topics. Due to the wide range of topics and relations with UQ, we have assembled these articles into case studies. Each such case study sheds light on sources and impacts of UQ on the particular field, presents field-specific methods for dealing with UQ and provides link to further readings. The following list consists of a brief description of every case study and the link to its main article:
Uncertainty in seismic tomography is often a result of ill-posed inverse problems, which oppose reliable inference about the Earth’s structure.
The vision of sustainable, reliable, and affordable energy system of the future is subject to major uncertainties with respect to renewable energy generation.
Efficient Monte Carlo methods are a promising deal to solve the exponential costs of uncertainty quantification in global climate models.
Data assimilation may help do grasp the underlying phenomena behind parameter uncertainty in biogeochemical (BGC) models.
Studies in degradation models are monetary and labor-wise costly, which underpins the value of computational feasible methods for uncertainty quanitification.
Biological communities experience high natural variability and are difficult to sample, leading to large uncertainties (affecting, e.g. measurements) in the nature and magnitude of biodiversity change.
Our ability to study even single biological cells seems promising to understand disease progressions and find appropriate treatments if we can account for the multitude of uncertainties and complexity of RNA data.
Subjective cognitive perception in geoscientific methods introduces uncertainty to the sampled information which can be addressed by information fusion of technically sampled and partially subjective maps.
UQ in weather prediction involves addressing the inherent uncertainties in atmospheric models, data assimilation processes, and complex interactions, enhancing the accuracy and reliability of weather forecasts.The main sources of uncertainty are discussed in the article UQ in Weather Prediction.