Estimation of Future Probable Maximum Precipitation in Korea Using Multiple Regional Climate Models

Abstract

Abstract:In this study, future probable maximum precipitations (PMPs) based on future meteorological variables produced from three regional climate models (RCMs) of 50-km spatial resolution provided by Coordinated Regional Climate Downscaling Experiment (CORDEX) are projected. In order to estimate future PMPs, the hydro-meteorological method is applied. The key future meteorological variable used to analyze the rate of change of future PMPs is the dew-point temperature. Future 12-h persistence 100-year return period extreme dew-point temperatures obtained from future daily dew-point temperature time series by using the scale-invariance method are applied to estimate future PMPs. As a result of estimating future PMPs using several RCMs and representative concentration pathways (RCPs) scenarios, the spatial distribution of future PMPs is expected to be similar to that of the present, but PMPs tend to increase in the future. In addition, it can be seen that the difference in PMPs estimated from various RCMs and RCP scenarios is getting bigger in the future. Especially after 2070, the difference has increased even more. In the short term, it is proposed to establish climate change adaptation policies with an 18% increase in PMPs, which is the ensemble average in the future year 2050.

Stochastic Parsimonious Hydrologic Partitioning Model under East Asia Monsoon Climate and Its Application to Climate Change

“…It can be seen that the soil water was almost saturated at the time of typhoon occurrence, and the lowest Horton index was recorded in the simulated period . On the other hand, the bar in Figure 7 represents the relative frequency of simulated daily soil water for 38 years, and the solid line with circles is PDF derived from Equation (26). It can be seen that the PDF derived using five meteorological variable statistics relatively well reproduced the statistical characteristics of numerically simulated soil water.…”

“…In particular, since more than two-thirds of annual precipitation occurs in summer, securing available water resources in summer is a very important social issue [25]. However, the projected future precipitation in the EAMC region is very difficult to attain credibility because it shows very large variability depending on what climate model is applied [26]. In fact, even when a model to reproduce typhoon-induced rainfall in the past is constructed, very different rainfall simulations are often obtained depending on how the physical options of the regional climate model are combined under the same initial conditions and boundary conditions [27,28].…”

Estimating Daily Dew Point Temperature Using Machine Learning Algorithms

“…After obtaining the optimal separator plate, the vector of the coefficients w obtained as Equation (9).…”

“…After performing the computations for different input combinations, the accuracy of the considered models was determined in the testing phase based on the statistical criteria (Equations (9) and (10)) and Taylor diagrams. The obtained results are presented in Table 4.…”

“…However, data-driven methods such as Gene Expression Programming (GEP) and Neuro-Fuzzy Inference System (ANFIS) have been developed to identify optimal functions and modeling for complex phenomena. In this regard, several studies have been carried out on the application of the mentioned methods in meteorological studies [4][5][6][7][8][9][10][11][12][13]. Shiri [2] compared the capabilities of the artificial neural network (ANN) and GEP to estimate the DPT using meteorological parameters at Seoul and Inchon stations, located in South Korea.…”