• Atmosphere
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• v.32 no.1
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• pp.1-15
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• 2022

Recently, Japan's Meteorological Research Institute presented the d4PDF database (Database for Policy Decision-Making for Future Climate Change, d4PDF) through large-scale climate ensemble simulations to overcome uncertainty arising from variability when the general circulation model represents extreme-scale precipitation. In this study, the change of precipitation characteristics between the historical and future climate conditions in the Yongdam-dam basin was analyzed using the d4PDF data. The result shows that annual mean precipitation and seasonal mean precipitation increased by more than 10% in future climate conditions. This study also performed an analysis on the change of the return period rainfall. The annual maximum daily rainfall was extracted for each climatic condition, and the rainfall with each return period was estimated. In this process, we represent the extreme-scale rainfall corresponding to a very long return period without any statistical model and method as the d4PDF provides rainfall data during 3,000 years for historical climate conditions and during 5,400 years for future climate conditions. The rainfall with a 50-year return period under future climate conditions exceeded the rainfall with a 100-year return period under historical climate conditions. Consequently, in future climate conditions, the magnitude of rainfall increased at the same return period and, the return period decreased at the same magnitude of rainfall. In this study, by using the d4PDF data, it was possible to analyze the change in extreme magnitude of rainfall.

• Journal of Korea Water Resources Association
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• v.55 no.3
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• pp.177-189
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• 2022

The purpose of this study is to apply the d4PDF (Data for Policy Decision Making for Future Change) constructed from a large-scale ensemble climate simulation to estimate the probable rainfall with low frequency and high intensity. In addition, this study analyzes the uncertainty caused by the application of the frequency analysis by comparing the probable rainfall estimated using the d4PDF with that estimated using the observed data and frequency analysis at Geunsam, Imsil, Jeonju, and Jangsu stations. The d4PDF data consists of a total of 50 ensembles, and one ensemble provides climate and weather data for 60 years such as rainfall and temperature. Thus, it was possible to collect 3,000 annual maximum daily rainfall for each station. By using these characteristics, this study does not apply the frequency analysis for estimating the probability rainfall, and we estimated the probability rainfall with a return period of 10 to 1000 years by distributing 3,000 rainfall by the magnitude based on a non-parametric approach. Then, the estimated probability rainfall using d4PDF was compared with those estimated using the Gumbel or GEV distribution and the observed rainfall, and the deviation between two probability rainfall was estimated. As a result, this deviation increased as the difference between the return period and the observation period increased. Meanwhile, the d4PDF reasonably suggested the probability rainfall with a low frequency and high intensity by minimizing the uncertainty occurred by applying the frequency analysis and the observed data with the short data period.

• Atmosphere
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• v.29 no.2
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• pp.115-129
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• 2019

Surface winds over the ocean influence not only the climate change through air-sea interactions but the coastal erosion through the changes in wave height and direction. Thus, demands on a reliable projection of future changes in surface winds have been increasing in various fields. For the future projections, climate models have been widely used and, as a priori, their simulations of surface wind are required to be evaluated. In this study, we evaluate the climatological mean surface winds over the Korean Waters simulated by five regional climate models participating in Coordinated Regional Climate Downscaling Experiment (CORDEX) for East Asia (EA), an international regional climate model inter-comparison project. Compared with the ERA-interim reanalysis data, the CORDEX-EA models, except for HadGEM3-RA, produce stronger wind both in summer and winter. The HadGEM3-RA underestimates the wind speed and inadequately simulate the spatial distribution especially in summer. This summer wind error appears to be coincident with mean sea-level pressure in the North Pacific. For wind direction, all of the CORDEX-EA models simulate the well-known seasonal reversal of surface wind similar to the ERA-interim. Our results suggest that especially in summer, large-scale atmospheric circulation, downscaled by regional models with spectral nudging, significantly affect the regional surface wind on its pattern and strength.