Pyraingen: A python package for constrained continuous rainfall generation

Abstract

Continuous rainfall is often required for flood estimation and water resources assessment. However, stochastically generated continuous rainfall records are typically inconsistent with intensity-frequency-durations (IFDs) used in design, and do not simulate the rainfall behaviour we can expect in a future warmer climate. Here, we present the python package pyraingen to generate ensembles of continuous subdaily rainfalls at a single location that preserve IFD relationships. Rainfall generation can also be conditioned on a climate covariate, in this case temperature, to produce rainfall timeseries reflective of a future climate. We present an implementation at five climatologically unique sites across Australia and demonstrate its ability to produce rainfall timeseries that reflect both present day and future changes in rainfall persistence, temporal patterns, means, and extremes. This package will enable studies using continuous simulation to assess the impacts of climate change using the current guidance on changes to both IFDs and mean annual rainfalls.