Jeongeun Won (Korea, Republic of) 1; Okjeong Lee (Korea, Republic of) 1; Jeonghyeon Choi (Korea, Republic of) 1; Kyungmin Kim (Korea, Republic of) 1; Inkyeong Sim (Korea, Republic of) 1; Sangdan Kim (Korea, Republic of) 2
1 - Division of Earth Environmental System Science (Major of Environmental Engineering), Pukyong National University; 2 - Department of Environment Engineering, Pukyong National University
Climatic change has caused frequent adverse weather phenomena. In particular, the damage caused by abnormal local storms in patterns different from the past is increasing rapidly. In order to anticipate and counteract these damages, researches have been actively conducted to produce a large rainfall scenario based on the maximum possible rainfall (PMP) and to prepare a countermeasure against such a scenario. In this study, we tried to reproduce the heavy rainfall event that occurred in the Imjin River basin of Korea as a preliminary study to produce the maximum rainfall scenarios considering climate change.
To do this, numerical simulation of rainfall events in 1999 was carried out using WRF, one of the regional climate models. WRF initial conditions and boundary conditions were generated using reanalysis data with 6-hour time resolution and 0.75° spatial resolution provided by ERA-Interim to construct the basic input data for WRF simulation. A total of 54 numerical experiments were carried out by combining the microphysics scheme, the cumulus parameterization scheme and the planetary boundary layer physical options, which have a great effect on simulation of rainfall events.
The final selected optimal physical option combinations are SBU-YLin, Kain-Fritsch, and Yonsei University scheme, respectively. Comparing the simulated rainfall event with the observed rainfall data using the optimal combination of physical options, the WRF can be seen that the observed rainfall event is well reproduced spatio-temporally. This study is expected to contribute to future studies to produce the maximum rainfall scenarios considering climate change.
Acknowledgement: This work is supported by the Korea Environmental Industry & Technology Institute (KEITI) grant funded by the Ministry of Environment (RE201901073).