Bridging the scale gap: obtaining high-resolution stochastic simulations of gridded daily precipitation in a future climate

Abstract

Climate change impact assessment related to floods, infrastructure networks, and water resource management applications requires realistic simulations of high-resolution gridded precipitation series under a future climate. This paper proposes to produce such simulations by combining a weather generator for high-resolution gridded daily precipitation, trained on a historical observation-based gridded data product, with coarser-scale climate change information obtained using a regional climate model. The climate change information can be added to various components of the weather generator, related to both the probability of precipitation as well as the amount of precipitation on wet days. The information is added in a transparent manner, allowing for an assessment of the plausibility of the added information. In a case study of nine hydrological catchments in central Norway with the study areas covering 1000–5500 km2, daily simulations are obtained on a 1 km grid for a period of 19 years. The method yields simulations with realistic temporal and spatial structures and outperforms empirical quantile delta mapping in terms of marginal performance.