• Atmosphere
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• v.15 no.2
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• pp.75-90
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• 2005

This study examines the impacts of land cover changes on the East Asia summer monsoon with the National Center for Atmospheric Research Regional Climate Model (NCAR RegCM2), coupled with Biosphere Atmosphere Transfer Scheme (BATS). To assess the goals, two types of land cover maps were used in the simulation of summer climate. One type was NCAR land cover map (CTL) and the other was current land cover map derived from satellite data (land cover: LCV). Warm and cold surface temperature biases of $1-3^{\circ}C$ occurred over central China and Mongolia in CTL. The model produced excessive precipitation over northern land area but less over southern ocean of the model domain. Changes of biophysical parameters, such as albedo, minimum stomatal resistance and roughness length, due to the land cover changes resulted in the alteration of land-atmosphere interactions. Latent heat flux and wind speed in LCV increased noticeably over central China where deciduous broad leaf trees have been replaced by mixed farm and irrigated crop. As a result, the systematic warm biases over central China were greatly reduced in LCV. Strong cooling of central China decreased pressure gradient between East Asian continent and Pacific Ocean. The decreased pressure gradient suppressed the northward transport of moisture from south China and South China Sea. These changes reduced not only the excessive precipitation over north China and Mongolia but also less precipitation over south China. However, the land cover changes increased the precipitation over the Korean Peninsula and the Japan Islands, especially in July and August.

• Korean Journal of Agricultural and Forest Meteorology
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• v.12 no.3
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• pp.183-196
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• 2010

Increasing human activity due to rapid economic growth and land use change alters the patterns of the Asian monsoon, which is key to crop yields in Asia. In this study, we tested the performance of regional climate model (RegCM3) by simulating important components of Indian summer monsoon, including land-ocean contrast, low level jet (LLJ), Tibetan high and upper level Easterly Jet. Three contrasting rain years (1994: excess year, 2001: normal year, 2002: deficient year) were selected and RegCM3 was integrated at 60 km horizontal resolution from April 1 to October 1 each year. The simulated fields of circulations and precipitation were validated against the observation from the NCEP/NCAR reanalysis products and Global Precipitation Climatology Centre (GPCC), respectively. The important results of RegCM3 simulations are (a) LLJ was slightly stronger and split into two branches during excess rain year over the Arabian Sea while there was no splitting during normal and deficient rain years, (b) huge anticyclone with single cell was noted during excess rain year while weak and broken into two cells in deficient rain year, (c) the simulated spatial distribution of precipitation was comparable to the corresponding observed precipitation of GPCC over large parts of India, and (d) the sensitivity experiment using NIMBUS-7 SMMR snow data indicated that precipitation was reduced mainly over the northeast and south Peninsular India with the introduction of 0.1 m of snow over the Tibetan region in April.

• Journal of the Korean Society of Marine Environment & Safety
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• v.24 no.2
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• pp.288-293
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• 2018

This study was conducted to understand the characteristics of the seasonal and regional distribution of phytoplankton communities in the Fisheries Resources Protection Area of Korea (FRPA). We investigated the phytoplankton composition, abundance and dominant species collected from five different regions (Cheonsu, Tongyeong-I, Tongyeong-II, Hansan, and Jindong) in 2016. According to the results, most environmental parameters, such as temperature, salinity and nutrients, showed statistically significant seasonal differences. Suspended particulate material (SPM) only showed a statistically significant regional difference. The mean abundance of phytoplankton ranged from 13 to $4,062cells{\cdot}ml^{-1}$, with large spatio-temporal fluctuations. In particular, the bloom of phytoplankton (>$10^3cells{\cdot}ml^{-1}$) in Cheonsu Bay occurred in April and October with Skeletonema spp. and Chaetoceros socialis being the dominant species during these two seasons, respectively. The dominant species in the FRPA were diatoms (Pseudo-nitzschia spp., Skeletonema spp., and Chaetoceros pseudocriniuts) and dinoflagellates (Scrippsiella trochoidea and Tripos furca). The seasonal distribution of phytoplankton communities showed typical characteristics of coastal waters, i.e., that diatoms usually dominated in winter and autumn, while dinoflagellates tended to dominate in spring and summer. Meanwhile, the dominance rate of diatoms in the phytoplankton community in Cheonsu Bay, which is located in a high-turbidity region, was 9~27 % greater than that of diatoms in the phytoplankton community found in the south coastal waters, which is a low turbidity region.

• Journal of Wetlands Research
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• v.16 no.2
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• pp.173-185
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• 2014

Climate change has caused detrimental phenomena such as heavy rainfall which could aggravate soil erosion. Accordingly, it is needed to evaluate the groundwater recharge, baseflow, and soil erosion for the efficient management of water resources and quality. In this study, future climate change scenarios were applied to the H aean-myeon watershed which is a steep sloping watershed in South Korea to analyze groundwater recharge, baseflow, sediment. Also, the variation of groundwater recharge, baseflow, sediment was analyzed according to the change of slope (5 %). Simulated periods were divided into three terms (2013 ~ 2040 years, 2041 ~ 2070 years, 2071 ~ 2100 years). As a result of this study, average groundwater recharge and baseflow increased by 50 %, 42 %, and sediment decreased by 72 %, respectively. In these regards, the suggested method will positively contribute to hydro-ecosystem and reduction of muddy water at a steep sloping watershed.

• Environmental and Resource Economics Review
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• v.26 no.2
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• pp.229-255
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• 2017

This study empirically estimates the impacts of climate change on forest composition in Korea using a fractional data regression model, and forecasts the change in forest composition in the 2040s and 2090s based on the IPCC climate change scenarios. Unlike the forest science studies that incorporate mostly only ecological variables as the determinants of forest composition, we take into account regional level socio-economic and forest management variables as well. Our estimation results found that not only environmental factors but also socio-economic and forest management related factors strongly affect the composition of Korean forest. Based on the estimation results and IPCC scenarios on climate change, we predict that the share of currently dominant coniferous forest will decline in the future under all scenarios. About 10% of total forest area is likely to be converted from coniferous forest into broadleaved forest until 2090s under the scenario RCP 8.5. It is also predicted that there will be a substantial regional variation in the effects of climate change on forest composition, and the coniferous forests in the inland regions will decline more dramatically.

• Journal of the Korean Society of Hazard Mitigation
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• v.11 no.3
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• pp.29-35
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• 2011

This research proposes the suitable method for estimating the future probable rainfall based in 2100 on the observed rainfall data from main climate observation stations in Korea and the rainfall data from the A1B climate change scenario in the Korea Meteorological Administration. For all those, the frequency probable rainfall in 2100 was estimated by the relationship between average values of 24-hours annual maximum rainfalls and related parameters. Three methods to estimate it were introduced; First one is the regressive analysis method by parameters of probable distribution estimated by observed rainfall data. In the second method, parameters of probable distribution were estimated with the observed rainfall data. Also the rainfall data till 2100 were estimated by the A1B scenario of the Korea Meteorological Administration. Last method was that parameters of probable distribution and probable rainfall were estimated by the A1B scenario of the Korea Meteorological Administration. The estimated probable rainfall by the A1B scenario was smaller than the observed rainfall data, so it is required that the estimated probable rainfall was calibrated by the quantile mapping method. After that calibration, estimated probable rainfall data was averagely became approximate 2.3 to 3.0 times. When future probable rainfall was the estimated by only observed rainfall, estimated probable rainfall was overestimated. When future probable rainfall was estimated by the A1B scenario, although it was estimated by similar pattern with observed rainfall data, it frequently does not consider the regional characteristics. Comparing with average increased rate of 24-hours annual maximum rainfall and increased rate of probable rainfall estimated by three methods, optimal method of estimated future probable rainfall would be selected for considering climate change.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.43 no.3
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• pp.309-319
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• 2023

Recently, the frequency and intensity of meteorological disasters have increased due to climate change. In South Korea, there are regional differences in vulnerability and response capability to cope with climate change because of regional climate characteristics. In particular, drought results from various factors and is linked to extensive meteorological, hydrological, and agricultural impacts. Therefore, in order to effectively cope with drought, it is necessary to use a composite drought index that can take into account various factors, and to evaluate future droughts comprehensively considering climate change. This study evaluated hydrologic risk(${\bar{R}}$) of future drought in the Nakdong River basin based on the Dynamic Naive Bayesian Classification (DNBC)-based composite drought index, which was calculated by applying Standardized Precipitation Index (SPI), Streamflow Drought Index (SDI), Evaporate Stress Index (ESI) and Water Supply Capacity Index (WSCI) to the DNBC. The indices used in the DNBC were calculated using observation data and climate scenario data. A bivariate frequency analysis was performed for the severity and duration of the composite drought. Then using the estimated bivariate return periods, hydrologic risks of drought were calculated for observation and future periods. The overall results indicated that there were the highest risks during the future period (2021-2040) (${\bar{R}}$=0.572), and Miryang River (#2021) had the highest risk (${\bar{R}}$=0.940) on average. The hydrologic risk of the Nakdong River basin will increase highly in the near future (2021-2040). During the far future (2041-2099), the hydrologic risk decreased in the northern basins, and increased in the southern basins.

• Ocean and Polar Research
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• v.41 no.3
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• pp.121-133
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• 2019

Natural variability associated with a variety of large-scale climate modes causes regional differences in sea level rise (SLR), which is particularly remarkable in the Pacific Ocean. Because the superposition of the natural variability and the background anthropogenic trend in sea level can potentially threaten to inundate low-lying and heavily populated coastal regions, it is important to quantify sea level variability associated with internal climate variability and understand their interaction when projecting future SLR impacts. This study seeks to identify the dominant modes of sea level variability in the tropical Pacific and quantify how these modes contribute to regional sea level changes, particularly on the two strong El $Ni{\tilde{n}}o$ events that occurred in the winter of 1997/1998 and 2015/2016. To do so, an adaptive data analysis approach, Ensemble Empirical Mode Decomposition (EEMD), was undertaken with regard to two datasets of altimetry-based and in situ-based steric sea levels. Using this EEMD analysis, we identified distinct internal modes associated with El $Ni{\tilde{n}}o$-Southern Oscillation (ENSO) varying from 1.5 to 7 years and low-frequency variability with a period of ~12 years that were clearly distinct from the secular trend. The ENSO-scale frequencies strongly impact on an east-west dipole of sea levels across the tropical Pacific, while the low-frequency (i.e., decadal) mode is predominant in the North Pacific with a horseshoe shape connecting tropical and extratropical sea levels. Of particular interest is that the low-frequency mode resulted in different responses in regional SLR to ENSO events. The low-frequency mode contributed to a sharp increase (decrease) of sea level in the eastern (western) tropical Pacific in the 2015/2016 El $Ni{\tilde{n}}o$ but made a negative contribution to the sea level signals in the 1997/1998 El $Ni{\tilde{n}}o$. This indicates that the SLR signals of the ENSO can be amplified or depressed at times of transition in the low-frequency mode in the tropical Pacific.

• 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.

• Journal of Soil and Groundwater Environment
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• v.17 no.2
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• pp.62-70
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• 2012

Rainfall, on Jeju Island varies regionally in relation to Mt. Halla with higher rainfall within southern area and lower in western area, and its variability is expected to expand according to the climate change scenario. Non-parametric trend analysis for rainfall, using both historic (1971-2010) and simulated (2011-2100) data assuming the A1B emissions scenario, shows regionally increasing trends with time. In perspective of agricultural land use, area for market garden including various crop types with high water demand is increasing over the Island, especially in the western area with lower rainfall compared to southern area. On the other hand, area for fruit including mandarin and kiwi with low water demand is widely distributed over southern and northern part having higher rainfall. These regional disparity of water demand/supply may be more affected by extreme events such as drought and heavy rainfall that has not yet been considered. Therefore, it is necessary to make policies for water resource management considering both demand and supply in different regions with climate change impacts over Jeju Island.