Comparison of regional climate scenario data by a spatial resolution for the impact assessment of the uncertainty associated with meteorological inputs data on crop yield simulations in Korea

Abstract

Uncertainty of crop yield simulation would be affected by weather input data prepared from different sources of climate datasets. Although regional climate data at a high spatial resolution would be useful for the impact assessment of climate change on crop production, little effort has been made to characterize the uncertainty associated with such climate data in terms of crop yield simulations. The objectives of this study were to compare climate scenario data products obtained from a series of downscaling processes and to identify an overall pattern of uncertainty in these climate data in terms of crop yield simulation. Regional climate scenario data from 2011 to 2014 had a spatiotemporal pattern of uncertainty, which differed by meteorological variables and spatial resolution. Overall, the uncertainty of daily minimum temperature was greater than that of maximum temperature. Daily minimum temperature also had relatively greater uncertainty in an early season of crop production, which could result in the cumulative impact on the uncertainty of crop yield simulations. For the uncertainty of climate data at different spatial resolution, climate data at higher spatial resolution, e.g. 1 km, tended to have lower uncertainty than data at resolution of 12.5 km did. Still, the uncertainty of regional climate data was relatively similar between data at resolution of 12.5 km and 1 km in major rice production areas in Korea except in areas near Seosan. This merits further studies to examine actual differences in projected crop yields using regional climate scenario data in the future and to assess the impact of uncertainty associated with regional climate data on crop yield simulation.