Attributing Local Precipitation Variability to Climate and Circulation Dynamics

Precipitation has become an increasingly critical issue, particularly in the wake of events such as severe pluvial flooding and the subsequent emergence of fluvial flooding concerns during recent anomalously wet winters in many places in Europe. Observational data indicate a steady increase in precipitation over recent decades in many regions. While this trend is believed to be linked to global warming, it does not exhibit a simple linear relationship with rising temperatures. Instead, it likely results from a combination of factors, including indirect effects such as alterations in atmospheric circulation, which are influenced by both climate change and natural variability. This study seeks to quantify the relative contributions of these drivers to observed changes in precipitation.

The analysis begins with a dataset comprising of key drivers of regional precipitation variability - in this case the focus is Denmark. The reanalysis data used includes pressure, temperature and sea surface temperature (SST), along with indices for the North Atlantic Oscillation (NAO), global warming and latitudinal position of the polar front, all on monthly timescales. SST patterns are clustered using dynamical time warping, the clusters to be included in the analysis are based on their correlation to regional precipitation. Multilinear regressions are applied pointwise, with the target variable being monthly average of total precipitation. This produces a spatial extent of the relative importance of the different drivers. The importance ranking is also verified using permutation importance and mediation and suppression. The temporal evolution of the different drivers is also examined by taking field means over select areas and looking at how the drivers covary with precipitation.

Attribution of the observed precipitation changes is based on the weights derived from multilinear regressions, supported by validation tests and the temporal evolution of the identified drivers. The results provide insights into the dynamics underpinning precipitation changes, highlighting the interplay of thermodynamical and dynamical influences.

This study contributes to a deeper understanding of how precipitation patterns may evolve under global warming scenarios and offers a clearer perspective on the circulation changes driving these trends. Although the current focus is on a specific region, the methodology is generalizable to other areas, provided appropriate domain knowledge is incorporated. Future applications could expand the analysis to Northern Europe or similar climatological contexts with suitable datasets.