• Korean Journal of Ecology and Environment
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• v.48 no.4
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• pp.229-237
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• 2015

This study aims to offer basic data to effectively preserve and manage pine forests using more precise pine forests' distribution status. In this regard, this study predicts the geographical distribution change of pine forests growing in South Korea, due to climate change, and evaluates the spatial distribution characteristics of pine forests by age. To this end, this study predicts the potential distribution change of pine forests by applying the MaxEnt model useful for species distribution change to the present and future climate change scenarios, and analyzes the effects of bioclimatic variables on the distribution area and change by age. Concerning the potential distribution regions of pine forests, the pine forests, aged 10 to 30 years in South Korea, relatively decreased more. As the area of the region suitable for pine forest by age was bigger, the decreased regions tend to become bigger, and the expanded regions tend to become smaller. Such phenomena is conjectured to be derived from changing of the interaction of pine forests by age from mutual promotional relations to competitive relations in the similar climate environment, while the regions suitable for pine forests' growth are mostly overlap regions. This study has found that precipitation affects more on the distribution of pine forests, compared to temperature change, and that pine trees' geographical distribution change is more affected by climate's extremities including precipitation of driest season and temperature of the coldest season than average climate characteristics. Especially, the effects of precipitation during the driest season on the distribution change of pine forests are irrelevant of pine forest's age class. Such results are expected to result in a reduction of the pine forest as the regions with the increase of moisture deficiency, where climate environment influencing growth and physiological responses related with drought is shaped, gradually increase according to future temperature rise. The findings in this study can be applied as a useful method for the prediction of geographical change according to climate change by using various biological resources information already accumulated. In addition, those findings are expected to be utilized as basic data for the establishment of climate change adaptation policies related to forest vegetation preservation in the natural ecosystem field.

• Journal of the Korean Wood Science and Technology
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• v.44 no.3
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• pp.370-380
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• 2016

The black pine logs damaged by pine wilt disease in Jeju-do were heat-treated to extend the utilization of domestic trees damaged by pine wilt disease. The heat-treatment of wood requires wood to be heated to $56^{\circ}C$ for 30 min at the core. The average moisture content and top-diameter of the black pine logs were ranged from 46% to 141% and from 180 mm to 500 mm, respectively. And the basic specific gravity and oven-dry specific gravity of the black pine logs were 0.47 and 0.52, respectively. The time required for heat-treatment at $105^{\circ}C$ temperature was ranged from 7.7 h to 44.2 h, depending on moisture content and top-diameter. The temperature distribution was used to predict the time required for heat-treatment of black pine log with various moisture contents and top-diameters using finite difference method. The thermal properties of wood including the thermal conductivity and specific heat in accordance with moisture content were calculated. Heat transfer coefficient for mixed convection in form of adding natural convection and forced convection was used for heat transfer analysis. The error between the measured and predicted values ranged from 3% to 45%. The predicted times required for heat-treatment of black pine log with 50% moisture content and 200 mm, 300 mm, and 400 mm top-diameter were 10.9 h, 18.3 h, and 27.0 h, respectively. If the initial moisture content of black pine log is 75%, heat treatment times of 13.6 h, 22.5 h, and 32.8 h were predicted in accordance with top-diameter. And if the initial moisture content of black pine log is 100%, heat treatment times of 16.2 h, 26.5 h, and 38.2 h were predicted in accordance with top-diameter. When the physical properties of logs damaged by pine wilt disease are presented, these results can be applicable to the heat-treatment of red pine and Korean pine logs as well.

• Korean Journal of Plant Taxonomy
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• v.52 no.3
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• pp.184-195
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• 2022

The invasive alien species Brassica tournefortii Gouan (Brassicaceae) is herein reported for the first time in Korea, from Gunsan-si, Gochang-gun, and Jeju-si. Brassica tournefortii can easily be distinguished from B. juncea and B. napus by its dense stiff hairs at the base of the stem and leaves, basally and distally branched stems, partially dehiscent fruits, and seeds that become mucilaginous in the presence of moisture. Although some taxonomists have classified this species as belonging to Coincya Rouy based on its fruit and seed characteristics, the existence of one vein on the fruit valves and our maximum likelihood analysis using internal transcribed spacer sequences placed it in Brassica. Distribution data, photographs, and a description of B. tournefortii are presented herein. Moreover, potential changes in the distribution of B. tournefortii were predicted under different climate scenarios, but our analysis showed that the probability of the spreading of this species is low. Nevertheless, continuous monitoring is necessary for an accurate assessment. The results of the present study can be used to conduct an invasion risk assessment and can assist with the effective management of this invasive alien species.

• Atmosphere
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• v.22 no.1
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• pp.13-28
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• 2012

The $PM_{10}$ concentration data is useful for indentifying intensity and a transport way of Asian dust. However, it is difficult to identify them properly due to the limited spatial resolution and coverage. Therefore, a methodology to estimate $PM_{10}$ concentration using visibility data obtained from synoptic observation was developed. To derive the converting function, correlation between visibility and $PM_{10}$ concentration is investigated using visibility and $PM_{10}$ concentration data observed at 20 stations in Korea from 2005 to 2009. To minimize bias due to atmospheric moisture, data with higher relative humidity over a critical value were eliminated while deriving $PM_{10}$-visibility relationship. As a result, an exponentially decreasing function of visibility is obtained under the condition that relative humidity is less than 82%. Verification of the visibility converting function to $PM_{10}$ concentration was carried out for the dust cases in 2010. It was found that spatial distributions of $PM_{10}$ calculated by visibility are in good agreement with the observed $PM_{10}$ distribution, especially for the strong dust cases in 2010. And correlation between the derived and observed $PM_{10}$ concentration was 0.63. We applied the function to obtain distributions of $PM_{10}$ concentration over North Korea, in which concentration data are not available, and compared them with satellite derived dust index, IODI distributions for dust cases in 2010. It is shown that the visibility function estimates quite similar patterns of dust concentration with IODI image, which suggests that it can contribute for prediction by indentifying transport route of Asian dust.

• Journal of Cadastre & Land InformatiX
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• v.47 no.2
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• pp.107-120
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• 2017

There are many wildfire risk indices worldwide, but objective comparisons between such various wildfire risk indices and surface dryness indices have not been conducted for the wildfire cases in Korea. This paper describes a sensitivity analysis on the wildfire risk indices and surface dryness indices for Korea using LDAPS(Local Analysis and Prediction System) meteorological dataset on a 1.5-km grid and MODIS(Moderate-resolution Imaging Spectroradiometer) satellite images on a 1-km grid. We analyzed the meteorology-based wildfire risk indices such as the Australian FFDI(forest fire danger index), the Canadian FFMC(fine fuel moisture code), the American HI(Haines index), and the academically presented MNI(modified Nesterov index). Also we examined the satellite-based surface dryness indices such as NDDI(normalized difference drought index) and TVDI(temperature vegetation dryness index). As a result of the comparisons between the six indices regarding 120 wildfire cases with the area damaged over 1ha during the period between January 2013 and May 2017, we found that the FFDI and FFMC showed a good predictability for most wildfire cases but the MNI and TVDI were not suitable for Korea. The NDDI can be used as a proxy parameter for wildfire risk because its average CDF(cumulative distribution function) scores were stably high irrespective of fire size. The indices tested in this paper should be carefully chosen and used in an integrated way so that they can contribute to wildfire forecasting in Korea.

• Korean Journal of Soil Science and Fertilizer
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• v.43 no.4
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• pp.407-414
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• 2010

Until now, the pore size distribution, PSD, of soil profile has been calculated from soil moisture characteristic data by water release method or mercury porosimetry using the capillary rise equation. But the current methods are often difficult to use and time consuming. Thus, in this work, theoretical framework for an easy and fast technique was suggested to estimate the PSD from unsaturated hydraulic conductivity data in an undisturbed field soil profile. In this study, unsaturated hydraulic conductivity data were collected and simulated by the variation of soil parameters in the given boundary conditions (Brooks and Corey soil parameters, ${\alpha}_{BC}=1-5L^{-1}$, b = 1 - 10; van Genuchten soil parameters, ${\alpha}_{VG}=0.001-1.0L^{-1}$, m = 0.1 - 0.9). Then, $K_s$ (1.0 cm $h^{-1})$ was used as the fixed input parameter for the simulation of each models. The PSDs were estimated from the collected K(h) data by model simulation. In the simulation of Brooks-Corey parameter, the saturated hydraulic conductivity, $K_s$, played a role of scaling factor for unsaturated hydraulic conductivity, K(h) Changes of parameter b explained the shape of PSD curve of soil intimately, and a ${\alpha}_{BC}$ affected on the sensitivity of PSD curve. In the case of van Genuchten model, $K_s$ and ${\alpha}_{VG}$ played the role of scaling factor for a vertical axis and a horizontal axis, respectively. Parameter m described the shape of PSD curve and K(h) systematically. This study suggests that the new theoretical technique can be applied to the in situ prediction of PSD in undisturbed field soil.

• Atmosphere
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• v.32 no.2
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• pp.87-101
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• 2022

In this paper, the performance improvement for the new KMA's Climate Prediction System (GloSea6), which has been built and tested in 2021, is presented by assessing the bias distribution of basic variables from 24 years of GloSea6 hindcasts. Along with the upgrade from GloSea5 to GloSea6, the performance of GloSea6 can be regarded as notable in many respects: improvements in (i) negative bias of geopotential height over the tropical and mid-latitude troposphere and over polar stratosphere in boreal summer; (ii) cold bias of tropospheric temperature; (iii) underestimation of mid-latitude jets; (iv) dry bias in the lower troposphere; (v) cold tongue bias in the equatorial SST and the warm bias of Southern Ocean, suggesting the potential of improvements to the major climate variability in GloSea6. The warm surface temperature in the northern hemisphere continent in summer is eliminated by using CDF-matched soil-moisture initials. However, the cold bias in high latitude snow-covered area in winter still needs to be improved in the future. The intensification of the westerly winds of the summer Asian monsoon and the weakening of the northwest Pacific high, which are considered to be major errors in the GloSea system, had not been significantly improved. However, both the use of increased number of ensembles and the initial conditions at the closest initial dates reveals possibility to improve these biases. It is also noted that the effect of ensemble expansion mainly contributes to the improvement of annual variability over high latitudes and polar regions.