• Korean Journal of Agricultural and Forest Meteorology
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• v.25 no.4
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• pp.376-386
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• 2023

Due to climate changes, landslide hazards in the Republic of Korea (hereafter South Korea) continuously increase. To establish the effective landslide mitigation strategies, such as erosion control works, landslide hazard estimation in the long-term perspective should be proceeded considering the influence of climate changes. In this study, we examined the change in landslide-damaged areas in South Korea responding to climate change scenarios using the multivariate regression method. Data on landslide-damaged areas and rainfall from 1981-2010 were used as a training dataset. Sev en indices were deriv ed from rainfall data as the model's input data, corresponding to rainfall indices provided from two SSP scenarios for South Korea: SSP1-2.6 and SSP5-8.5. Prior to the multivariate regression analysis, we conducted the VIF test and the dimension analysis of regression model using PCA. Based on the result of PCA, we developed a regression model for landslide damaged area estimation with two principal components, which cov ered about 93% of total v ariance. With climate change scenarios, we simulated landslide-damaged areas in 2030-2100 using the regression model. As a result, the landslide-damaged area will be enlarged more than the double of current annual mean landslide damaged area of 1981-2010; It infers that landslide mitigation strategies should be reinforced considering the future climate condition.

• Journal of Environmental Science International
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• v.25 no.6
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• pp.897-904
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• 2016

We investigated the local climatological characteristics of the mountain adjacent the Dongyeong herb garden in Chilgok. We established one set of automatic weather system (AWS) on a hill where development of herb garden is in progress. The observations were continued for 2 years(2013. 07-2015.06). In this study, we analyzed the observed data comparing the data of Gumi meteorological observatory (GMO). The results showed that the air temperature(relative humidity) of Dongyeong herb garden were lower(higher) than those of GMO. Especially the differences are more during warm climate season. It means that the gaps of thermal environment between two points are mainly caused by the evaporation effects of forest. In addition, we analyzed the warmth indices(warmth index and coldness index) with the observed air temperature. The warmth and coldness indices indicate about 107 and -12, respectively. The values correspond to warm temperature climate.

• Journal of The Korean Society of Agricultural Engineers
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• v.58 no.5
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• pp.1-10
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• 2016

Drought is a slow-varying natural hazard that is characterized by various factors such that reliable drought forecasting along with uncertainties estimation has been a major issue. In this study, we proposed a stochastic simulation technique based scheme for providing a set of drought scenarios. More specifically, this study utilized a nonstationary Hidden markov model that allows us to include predictors such as climate state variables and global climate model's outputs. The simulated rainfall scenarios were then used to generate the well-known meteorological drought indices such as SPI, PDSI and PN for the three dam watersheds in South Korea. It was found that the proposed modeling scheme showed a capability of effectively reproducing key statistics of the observed rainfall. In addition, the simulated drought indices were generally well correlated with that of the observed.

• Korean Journal of Agricultural and Forest Meteorology
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• v.24 no.4
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• pp.201-217
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• 2022

The United States is one of the largest producers of major crops such as wheat, maize, and soybeans, and is a major exporter of these crops. Therefore, it is important to estimate the crop production of the country in advance based on reliable long- term weather forecast information for stable crops supply and demand in Korea. The purpose of this study is to improve the seasonal predictability of the agro-climatic indices over the United States by using regional-scale daily temperature. For long-term numerical weather prediction, a dynamical downscaling is performed using Weather Research and Forecasting (WRF) model, a regional climate model. As the initial and lateral boundary conditions of WRF, the global hourly prediction data obtained from the Pusan National University Coupled General Circulation Model (PNU CGCM) are used. The integration of WRF is performed for 22 years (2000-2021) for period from June to December of each year. The empirical quantile mapping, one of the bias correction methods, is applied to the timeseries of downscaled daily mean, minimum, and maximum temperature to correct the model biases. The uncorrected and corrected datasets are referred WRF_UC and WRF_C, respectively in this study. The daily minimum (maximum) temperature obtained from WRF_UC presents warm (cold) biases over most of the United States, which can be attributed to the underestimated the low (high) temperature range. The results show that WRF_C simulates closer to the observed temperature than WRF_UC, which lead to improve the long- term predictability of the temperature- based agro-climatic indices.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.29 no.1B
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• pp.23-33
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• 2009

Climate change, abnormal weather, and unprecedented extreme weather events have appeared globally. Interest in their size, frequency, and changes in spatial distribution has been heightened. However, the events do not display regional or regular patterns or cycles. Therefore, it is difficult to carry out quantified evaluation of their frequency and tendency. For more objective evaluation of extreme weather events, this study proposed a rainfall extreme weather index (STARDEX, 2005). To compare the present and future spatio-temporal distribution of extreme weather events, each index was calculated from the past data collected from 66 observation points nationwide operated by Korea Meteorological Administration (KMA). Tendencies up to now have been analyzed. Then, using SRES B2 scenario and 2045s (2031-2050) data from YONU CGCM simulation were used to compute differences among each of future extreme weather event indices and their tendencies were spatially expressed.The results shows increased rainfall tendency in the East-West inland direction during the summer. In autumn, rainfall tendency increased in some parts of Gangwon-do and the south coast. In the meanwhile, the analysis of the duration of prolonged dry period, which can be contrasted with the occurrence of rainfall or its concentration, showed that the dryness tendency was more pronounced in autumn rather than summer. Geographically, the tendency was more remarkable in Jeju-do and areas near coastal areas.

• Journal of Climate Change Research
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• v.5 no.4
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• pp.285-289
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• 2014

The extension of growing season (GS) across the Northern Hemisphere have been linked to increasing temperature, related with global warming. Therefore, in this study, The start, end, and length of GS in Suwon, Korea from 1971 to 2013 based on observed daily mean air temperature are examined using three indices. The GS starts on average after $98.598.5{\pm}1.42$ Julian days and ends after $318.7{\pm}1.08$ Julian days. The average length of GS is $220.2{\pm}2.09$ Julian days. The length of GS in Suwon from 1971 to 2013 has been extended by 6.8 days/decade with an earlier onset of the GS (-4.1 days/decade) and later end of the GS (2.7 days/decade). This change may be due to an advanced start of the GS in spring rather than later end of the GS. In further study, it is necessary to select an index carefully to find the most suitable one for Korea.

• Journal of The Korean Society of Agricultural Engineers
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• v.61 no.6
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• pp.81-92
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• 2019

The objective of this study is to evaluate hydrologic impacts of climate change according to downscaling methods using the Soil and Water Assessment Tool (SWAT) model at watershed scale. We used the APCC Integrated Modeling Solution (AIMS) for assessing various General Circulation Models (GCMs) and downscaling methods. AIMS provides three downscaling methods: 1) BCSA (Bias-Correction & Stochastic Analogue), 2) Simple Quantile Mapping (SQM), 3) SDQDM (Spatial Disaggregation and Quantile Delta Mapping). To assess future hydrologic responses of climate change, we adopted three GCMs: CESM1-BGC for flood, MIROC-ESM for drought, and HadGEM2-AO for Korea Meteorological Administration (KMA) national standard scenario. Combined nine climate change scenarios were assessed by Expert Team on Climate Change Detection and Indices (ETCCDI). SWAT model was established at the Mankyung watershed and the applicability assessment was completed by performing calibration and validation from 2008 to 2017. Historical reproducibility results from BCSA, SQM, SDQDM of three GCMs show different patterns on annual precipitation, maximum temperature, and four selected ETCCDI. BCSA and SQM showed high historical reproducibility compared with the observed data, however SDQDM was underestimated, possibly due to the uncertainty of future climate data. Future hydrologic responses presented greater variability in SQM and relatively less variability in BCSA and SDQDM. This study implies that reasonable selection of GCMs and downscaling methods considering research objective is important and necessary to minimize uncertainty of climate change scenarios.

• Korean Journal of Agricultural and Forest Meteorology
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• v.18 no.3
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• pp.109-119
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• 2016

This study was conducted to analyze the effect of yearly changes in growing degree days (GDD) on the potential distribution and growth of Quercus mongolica in Korea. Annual tree-ring growth data of Quercus mongolica collected by the $5^{th}$ National Forest Inventory were first organized to identify the range of current distribution for the species. Yearly GDD was calculated based on daily mean temperature data from 1951 to 2010 for counties with current distribution of Q. monglica. When tree-ring growth data were analyzed through cluster analysis based on similarity of climatic conditions, seven clusters were identified. Yearly GDD based on daily mean temperature data of each county were calculated for each of the cluster to predict the change of potential distribution. Temperature effect indices were estimated to predict the effect of GDD on the growth patterns. In addition, RCP 4.5 and RCP 8.5 of climate change scenarios were adopted to estimate yearly GDD and temperature effect indices from 2011 to 2100. The results indicate that the areas with low latitude and elevation exceed the upper threshold of GDD for the species due to the increase of mean temperature with climate change. It was also predicted that the steep increase of temperature will have negative influences on tree-ring growth, and will move the potential distribution of the species to areas with higher latitude or higher elevation, especially after the year of 2050. The results of this study are expected to provide valuable information necessary for estimating local growth characteristics and for predicting changes in the potential distribution of Q. mongolica caused by climate change.

• Korean Journal of Agricultural and Forest Meteorology
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• v.21 no.4
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• pp.261-268
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• 2019

Climate change and drought stress are having profound impacts on crop growth and development by altering crop physiological processes including photosynthetic activity. But finding a rapid, efficient, and non-destructive method for estimating environmental stress responses in the leaf and canopy is still a difficult issue for remote sensing research. We compared the relationships between photochemical reflectance index(PRI) and various optical and experimental indices on soybean drought stress under climate change conditions. Canopy photosynthesis trait, biomass change, chlorophyll fluorescence(Fv/Fm), stomatal conductance showed significant correlations with midday PRI value across the drought stress period under various climate conditions. In high temperature treatment, PRI were more sensitive to enhanced drought stress, demonstrating the negative effect of the high temperature on the drought stress. But high CO₂ concentration alleviated the midday depression of both photosynthesis and PRI. Although air temperature and CO₂ concentration could affect PRI interpretation and assessment of canopy radiation use efficiency(RUE), PRI was significantly correlated with canopy RUE both under climate change and drought stress conditions, indicating the applicability of PRI for tracking the drought stress responses in soybean. However, it is necessary to develop an integrated model for stress diagnosis using PRI at canopy level by minimizing the influence of physical and physiological factors on PRI and incorporating the effects of other vegetation indices.

• Korean Journal of Remote Sensing
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• v.33 no.1
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• pp.97-109
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• 2017

Green tides that developed along the coast of China in 2015 were detected and tracked using vegetation indices from GOCI and Landsat images. Green tides first appeared near the Jiangsu Province on May 14 before increasing in size and number and moving northward to the Shandong Peninsula in mid-June. Typhoon Cham-hom passed through the Yellow Sea on July 12, significantly decreasing the algal population. An algae patch moved east toward Korea and on June 18 and July 4, several masses were found between the southwestern shores of Korea and Jeju Island. The floating masses found in Korean waters were concentrated at the boundary of the open sea and the Jindo cold pool, a phenomenon also observed at the boundary of coastal and offshore waters in China. Sea surface temperatures, derived from NOAA SST data, were found to play a role in generation of the green tides.