Climate Downscaling as a Source of Uncertainty in Projecting Local Climate Change Impacts

Abstract

This study assessed the sensitivity of the simulated future impact on forage yield over Japan to the precipitation change in growing season derived from the multiple downscaling models, taking the regional climate projection ensemble dataset for Japan as an example. Three regional climate models (RCMs: NHRCM, NRAMS, and TWRF), and one statistical model (CDFDM) provided the fine-resolution (20-km) climate data over Japan from the climate projection performed by a global climate model (GCM: MIROCHI) under A1B scenario. With the common boundaries for the RCMs (and predictor for the statistical model), there is a consistency for the increased summer precipitation. However, discrepancies were found for the degree of precipitation increase and change in the mean summer maximum number of consecutive dry days. These discrepancies caused the spread of the simulated future change in forage yield over Japan by 3.3-11.4% (2081-2100), relative to the present-day one (1981-2000). These results showed that the direction (increase or decrease) and amplitude of the simulated future impact differ between the climate scenarios from the downscaling models and those from the parent GCM, indicating that climate downscaling is a source of uncertainty in simulating future impact.