stagg:: A data pre-processing R package for climate impacts analysis

The increasing availability of high-resolution climate data has greatly expanded the study of how the climate impacts humans and society. However, the processing of these multi-dimensional datasets poses significant challenges for researchers in this growing field, most of whom are social scientists. This paper introduces stagg , or “space-time aggregator”, a new R package that streamlines three critical components of climate data processing for impacts analysis: nonlinear transformation, spatial and temporal aggregation, and spatial weighting by social or economic variables. The package consolidates the data processing pipeline into a few lines of code, lowering barriers to entry for researchers and facilitating a larger and more diverse research community. The paper provides an overview of stagg 's functions, followed by an applied example demonstrating the package's utility in climate impacts research. stagg has the potential to be a valuable tool in generating evidence-based estimates of the likely impacts of future climate change. • Open-source R package stagg streamlines data processing for climate impact analysis. • Includes nonlinear transformation and spatial/temporal aggregation of climate data. • Option to weight transformed data by additional social or economic variables. • Efficient and flexible, consolidates data processing into a few simple lines of code. • Enables evidence-based estimates of environmental impacts.