Grant award to improve predictions of extreme rainfall

A synergy between statisticians and climate researchers

The new grant will enable close collaboration between statisticians and researchers in climate and environmental science, bringing together advanced mathematical modelling and domain-specific knowledge of climate systems.

Mathematics can reveal patterns that climate specialists may not have anticipated. Conversely, climate science helps ensure that the models reflect real-world processes in meaningful ways.

“We can develop new mathematical tools, but it is through collaboration with domain experts that we can see how they perform in practice,” says Anders Stockmarr.

“At the same time, new models inspired by other research fields can provide new insights into the phenomena that impact climate-resilient water systems” says Peter Steen Mikkelsen.

An example from the previous PhD project concerned the role of proximity to the coast. Researchers initially expected coastal location to be a key factor in explaining extreme rainfall events. However, their analyses showed that this effect for lesser thresholds for extreme rainfall was captured through the model’s representation of local weather dependencies and spatial patterns, and the effect therefore appear to manifest for heavier rainfall events only.

More data provide a clearer view

A key part of the project is to make use of a much broader range of data sources than is common today. Current approaches do not fully exploit the combination of traditional rain gauges, which collect rainfall physically in a measuring container, modern weather-station data, and private sensor networks.

In addition to official rainfall measurements, the researchers will investigate how data from local weather stations and other privately operated monitoring networks can be incorporated into their analyses. These may include rain gauges owned by private citizens, businesses, or farmers. Such data can be used to validate and improve the mathematical models.

“The more reliable observations we are able to include, the better our understanding of how rainfall varies at a local level. This can provide a much more detailed picture of where and how extreme events arise,” says Anders Stockmarr.

Models with applications far beyond Denmark

The researchers already collaborate with DMI on climate data and expect the results to contribute in the longer term to future climate services and climate scenario development.

Their ambitions extend well beyond Denmark.

“We hope that, within three years, we will have models that significantly improve our ability to support future climate adaptation decisions. We also hope to demonstrate that the methodology can be applied beyond Denmark,” says Anders Stockmarr.

In the longer term, the ambition is to scale the approach to larger parts of Northern Europe, where many of the same weather systems affect countries across national borders. This will require models that can be adapted to local conditions.

“Denmark is a relatively flat country with limited variation in elevation and comparatively modest geographical diversity. In countries such as the United Kingdom, for example, the geology, hydrology, and topography are very different, with much greater variation across the landscape. The objective is therefore not simply to transfer a Danish model directly, but to develop a methodology that can be adapted to the specific conditions of each country,” says Peter Steen Mikkelsen.

In this way, the researchers hope not only to contribute to improved climate adaptation in Denmark, but also to establish a scientific foundation that can support efforts to address future climate challenges more broadly.