• Journal of the Korean earth science society
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• v.43 no.3
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• pp.367-385
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• 2022

This study evaluates the temperature and precipitation results in East Asia simulated from the Hadley Centre Global Environmental Model version 3 regional climate model (HadGEM3-RA) developed by the UK Met Office. The HadGEM3-RA is conducted in the Coordinated Regional climate Downscaling Experiment-East Asia (CORDEX-EA) Phase II domain for 15 year (2000-2014). The spatial distribution of rainbands produced from the HadGEM3-RA by the summer monsoon is in good agreement with the Asian Precipitation Highly Resolved Observational Data Integration Towards Evaluation of water resources (APRODITE) data over the East Asia. But, precipitation amount is overestimated in Southeast Asia and underestimated over the Korean Peninsula. In particular, the simulated summer rainfall and APRODITE data show the least correlation coefficient and the maximum value of root mean square error in South Korea. Prediction of temperature in Southeast Asia shows underestimation with a maximum error during winter season, while it appears the largest underestimation in South Korea during spring season. In order to evaluate local predictability, the time series of temperature and precipitation compared to the ASOS data of the Seoul Meteorological Station is similar to the spatial average verification results in which the summer precipitation and winter temperature underestimate. Especially, the underestimation of the rainfall increases when the amounts of precipitation increase in summer. The winter temperature tends to underestimate at low temperature, while it overestimates at high temperature. The results of the extreme climate index comparison show that heat wave is overestimated and heavy rainfall is underestimated. The HadGEM3-RA simulated with a horizontal resolution of 25 km shows limitations in the prediction of mesoscale convective system and topographic precipitation. This study indicates that improvement of initial data, horizontal resolution, and physical process are necessary to improve predictability of regional climate model.

• Journal of Korean Society of Forest Science
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• v.112 no.4
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• pp.472-489
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• 2023

This study was conducted to derive the optimal estimation equations for deriving the green and dry weights of Larix kaempferi (Japanese larch) and Pinus rigida (Rigida pine), which are major coniferous tree species in South Korea. The equations were then used to develop weight tables. Table development began with the sampling of 150 L. kaempferi and 90 P. rigida trees distributed throughout the national scale, after which green weights were measured on-site. Samples from each stand were then collected, and their dry weights were measured in a laboratory. The equation used to calculate green and dry weights was divided into a one-variable formula that uses only the diameter at breast height (DBH) and a two-variable equation that employs DBH and height. The equations used to estimate the green and dry weights of logs were divided into one- and two-variable equations using DBH. Statistical data, such as the fitness index (FI), root mean square error, standard error of estimation, and residual diagram, were used to verify the suitability of the estimation equations. Applicability was examined by calculating weights using the derived optimal equations. The equation W = bD+cD² was used in measurements involving only DBH, whereas the equation W = aD^bH^c was employed in cases involving both diameter and height at breast height. The FI of W = bD+cD² was 0.91, while that of W = aD^bH^c was 0.95, both of which are high values. With these estimation formulas, weight tables for the green and dry weights of L. kaempferi and P. rigida were prepared and compared with weight tables created 20 years ago. The green and dry weight tables of both species were larger.

• Korean Journal of Agricultural and Forest Meteorology
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• v.11 no.2
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• pp.61-71
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• 2009

Most deciduous trees in temperate zone are dormant during the winter to overcome cold and dry environment. Dormancy of deciduous fruit trees is usually separated into a period of rest by physiological conditions and a period of quiescence by unfavorable environmental conditions. Inconsistent and fewer budburst in pear orchards has been reported recently in South Korea and Japan and the insufficient chilling due to warmer winters is suspected to play a role. An accurate prediction of the flowering time under the climate change scenarios may be critical to the planning of adaptation strategy for the pear industry in the future. However, existing methods for the prediction of budburst depend on the spring temperature, neglecting potential effects of warmer winters on the rest release and subsequent budburst. We adapted a dormancy clock model which uses daily temperature data to calculate the thermal time for simulating winter phenology of deciduous trees and tested the feasibility of this model in predicting budburst and flowering of Niitaka pear, one of the favorite cultivars in Korea. In order to derive the model parameter values suitable for Niitaka, the mean time for the rest release was estimated by observing budburst of field collected twigs in a controlled environment. The thermal time (in chill-days) was calculated and accumulated by a predefined temperature range from fall harvest until the chilling requirement (maximum accumulated chill-days in a negative number) is met. The chilling requirement is then offset by anti-chill days (in positive numbers) until the accumulated chill-days become null, which is assumed to be the budburst date. Calculations were repeated with arbitrary threshold temperatures from $4^{\circ}C$ to $10^{\circ}C$ (at an interval of 0.1), and a set of threshold temperature and chilling requirement was selected when the estimated budburst date coincides with the field observation. A heating requirement (in accumulation of anti-chill days since budburst) for flowering was also determined from an experiment based on historical observations. The dormancy clock model optimized with the selected parameter values was used to predict flowering of Niitaka pear grown in Suwon for the recent 9 years. The predicted dates for full bloom were within the range of the observed dates with 1.9 days of root mean square error.

• Korean Journal of Remote Sensing
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• v.34 no.2_1
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• pp.301-306
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• 2018

Urbanization causes urban floods and urban heat island in the summer, so it is necessary to understanding the changes of the thermal environment through urban climate and energy balance. This can be explained by the energy balance, but in urban areas, unlike the typical energy balance, the storage heat flux saved in the building or artificial land cover should be considered. Since the environment of each city is different, there is a difficulty in applying the method of retrieving the storage heat flux of the previous research. Especially, most of the previous studies are focused on the overseas cities, so it is necessary to study the storage heat retrieval suitable for various land cover and building characteristics of the urban areas in Korea. Therefore, the object of this study, it is to derive the regression formula which can quantitatively retrieve the storage heat using the data of the area where various surface types exist. To this end, nonlinear regression analysis was performed using net radiation and surface temperature data as independent variables and flux tower based storage heat estimates as dependent variables. The retrieved regression coefficients were applied to each independent variable to derive the storage heat retrieval regression formula. As a result of time series analysis with flux tower based storage heat estimates, it was well simulated high peak at day time and the value at night. Moreover storage heat retrieved in this study was possible continuous retrieval than flux tower based storage heat estimates. As a result of scatter plot analysis, accuracy of retrieved storage heat was found to be significant at $50.14Wm^{-2}$ and bias $-0.94Wm^{-2}$.

• Korean Journal of Agricultural and Forest Meteorology
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• v.8 no.4
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• pp.209-221
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• 2006

The purpose of this study is to analyze the effects of climate change on the nonpoint source pollution in a small watershed using a mid-range model. The study area is a basin in a rural area that covers 384 ha with a composition of 50% forest and 19% paddy. The hydrologic and water quality data were monitored from 1996 to 2004, and the feasibility of the GWLF (Generalized Watershed Loading function) model was examined in the agricultural small watershed using the data obtained from the study area. As one of the studies on climate change, KEI (Korea Environment Institute) has presented the monthly variation ratio of rainfall in Korea based on the climate change scenario for rainfall and temperature. These values and observed daily rainfall data of forty-one years from 1964 to 2004 in Suwon were used to generate daily weather data using the stochastic weather generator model (WGEN). Stream runoff was calibrated by the data of $1996{\sim}1999$ and was verified in $2002{\sim}2004$. The results were determination coeff, ($R^2$) of $0.70{\sim}0.91$ and root mean square error (RMSE) of $2.11{\sim}5.71$. Water quality simulation for SS, TN and TP showed $R^2$ values of 0.58, 0.47 and 0.62, respectively, The results for the impact of climate change on nonpoint source pollution show that if the factors of watershed are maintained as in the present circumstances, pollutant TN loads and TP would be expected to increase remarkably for the rainy season in the next fifty years.

• Journal of Korea Water Resources Association
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• v.34 no.6
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• pp.659-672
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• 2001

Generally, design flood for a hydraulic structure is estimated using statistical analysis of runoff data. However, due to the lack of runoff data, it is difficult that the statistical method is applied for estimation of design flood. In this case, the synthetic unit hydrograph method is used generally and the models such as NYMO method, Snyder method, SCS method, and HYMO method have been widely used in Korea. In this study, these methods and KICT method, which is developed in year 2000, are compared and analyzed in 10 study areas. Firstly, peak flow and peak time of representative unit hydrograph and synthetic unit hydrograph in study area are compared, and secondly, the shape of unit hydrograph is compared using a root mean square error(RMSE). In Nakayasu method developed in Japan, synthetic unit hydrograph is very different from peak flow, peak time, and the shape of representative unit hydrograph, and KICT method(2000) is superior to others. Also, KICT method(2000) is superior to others in the aspects of using hydrologic and topographical data. Therefore, Nakayasu method is not a proper in hydrological practice. Moreover, it is considered that KICT model is a better method for the estimation of design flood. However, if other model, i.e. SCS method, Nakayasu method, and HYMO method, is used, parameters or regression equations must be adjusted by analysis of real data in Korea.

• Journal of the Korean earth science society
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• v.36 no.1
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• pp.90-108
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• 2015

The WRF-Chem model was applied to simulate the Asian dust event affecting the Korean Peninsula from 11 to 13 November 2010. GOCART dust emission schemes, RADM2 chemical mechanism, and MADE/SORGAM aerosol scheme were adopted within the WRF-Chem model to predict dust aerosol concentrations. The results in the model simulations were identified by comparing with the weather maps, satellite images, monitoring data of $PM_{10}$ concentration, and LIDAR images. The model results showed a good agreement with the long-range transport from the dust source area such as Northeastern China and Mongolia to the Korean Peninsula. Comparison of the time series of $PM_{10}$ concentration measured at Backnungdo showed that the correlation coefficient was 0.736, and the root mean square error was $192.73{\mu}g/m^3$. The spatial distribution of $PM_{10}$ concentration using the WRF-Chem model was similar to that of the $PM_{2.5}$ which were about a half of $PM_{10}$. Also, they were much alike in those of the UM-ADAM model simulated by the Korean Meteorological Administration. Meanwhile, the spatial distributions of $PM_{10}$ concentrations during the Asian dust events had relevance to those of both the wind speed of u component ($ms^{-1}$) and the PBL height (m). We performed a regressive analysis between $PM_{10}$ concentrations and two meteorological variables (u component and PBL) in the strong dust event in autumn (CASE 1, on 11 to 23 March 2010) and the weak dust event in spring (CASE 2, on 19 to 20 March 2011), respectively.

• Investigative Magnetic Resonance Imaging
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• v.12 no.2
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• pp.123-130
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• 2008

Purpose : Motion effects in parallel magnetic resonance imaging (MRI) are investigated. Parallel MRI is known to be robust to motion due to its reduced acquisition time. However, if there are some involuntary motions such as heart or respiratory motions involved during the acquisition of the parallel MRI, motion artifacts would be even worse than those in conventional (non-parallel) MRI. In this paper, we defined several types of motions, and their effects in parallel MRI are investigated in comparisons with conventional MRI. Materials and Methods : In order to investigate motion effects in parallel MRI, 5 types of motions are considered. Type-1 and 2 are periodic motions with different amplitudes and periods. Type-3 and 4 are segment-based linear motions, where they are stationary during the segment. Type-5 is a uniform random motion. For the simulation, Cartesian and spiral grid based parallel and non-parallel (conventional) MRI are used. Results : Based on the motions defined, moving artifacts in the parallel and non-parallel MRI are investigated. From the simulation, non-parallel MRI shows smaller root mean square error (RMSE) values than the parallel MRI for the periodic (type-1 and 2) motions. Parallel MRI shows less motion artifacts for linear(type-3 and 4) motions where motions are reduced with shorter acquisition time. Similar motion artifacts are observed for the random motion (type-5). Conclusion : In this paper, we simulate the motion effects in parallel MRI. Parallel MRI is effective in the reduction of motion artifacts when motion is reduced by the shorter acquisition time. However, conventional MRI shows better image quality than the parallel MRI when fast periodic motions are involved.

• Journal of the Korean Society of Food Science and Nutrition
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• v.43 no.6
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• pp.884-892
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• 2014

The purpose of this study was to investigate the drying characteristics and drying models of Ainsliaea acerifolia Sch. Bip. using far-infrared thin layer drying. Far-infrared thin layer drying test on Ainsliaea acerifolia Sch. Bip. was conducted at two air velocities of 0.6 and 0.8 m/sec, as well as three drying temperatures of 40, 45, and $50^{\circ}C$ respectively. The drying models were estimated using coefficient of determination and root mean square error. Drying characteristics were analyzed based on factors such as drying rate, leaf color changes, antioxidant activity, and contents of polyphenolics and flavonoids. The results revealed that increases in drying temperature and air velocity caused a reduction in drying time. The Thompson model was considered suitable for thin layer drying using far-infrared radiation for Ainsliaea accerifolia Sch. Bip. Greenness and yellowness values decreased and lightness values increased after far-infrared thin layer drying, and the color difference (${\Delta}E$) values at $40^{\circ}C$ were higher than those at $45^{\circ}C$ and $50^{\circ}C$. The antioxidant properties of Ainsliaea acerifolia Sch. Bip. decreased under all far-infrared thin layer drying conditions, and the highest polyphenolic content (37.9 mg/g), flavonoid content (22.7 mg/g), DPPH radical scavenging activity (32.5), and ABTS radical scavenging activity (31.1) were observed at a drying temperature of $40^{\circ}C$ with an air velocity of 0.8 m/sec.

• Journal of Korean Society of Environmental Engineers
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• v.28 no.3
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• pp.308-315
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• 2006

Since sewage characteristics are the most important factors that can affect the biological reactions in wastewater treatment plants, a detailed understanding on the characteristics and on-line measurement techniques of the influent sewage would play an important role in determining the appropriate control strategies. In this study, samples were taken at two hour intervals during 51 days from $1^{st}$ October to $21^{st}$ November 2005 from the influent gate of sewage treatment plant. Then the characteristics of sewage were investigated. It was found that the daily values of flow rate and concentrations of sewage components showed a defined profile. The highest and lowest peak values were observed during $11:00{\sim}13:00$ hours and $05:00{\sim}07:00$ hours, respectively. Also, it was shown that the concentrations of sewage components were strongly correlated with the absorbance measured at 300 nm of UV. Therefore, the objective of the paper is to develop on-line estimation technique of the concentration of each component in the sewage using accumulated profiles of sewage, absorbance, and flow rate which can be measured in real time. As a first step, regression analysis was performed using the absorbance and component concentration data. Then a neural network trained with the input of influent flow rate, absorbance, and inflow duration was used. Both methods showed remarkable accuracy in predicting the resulting concentrations of the individual components of the sewage. In case of using the neural network, the predicted value md of the measurement were 19.3 and 14.4 for TSS, 26.7 and 25.1 for TCOD, 5.4 and 4.1 for TN, and for TP, 0.45 to 0.39, respectively.