• Korean Journal of Remote Sensing
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• v.32 no.3
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• pp.307-321
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• 2016

Planetary Boundary Layer Height (PBLH) is a major input parameter for weather forecasting and atmosphere diffusion models. In order to estimate the sub-grid scale variability of PBLH, we need to monitor PBLH data with high spatio-temporal resolution. Accordingly, we introduce a LIdar observation VEhicle (LIVE), and analyze PBLH derived from the lidar loaded in LIVE. PBLH estimated from LIVE shows high correlations with those estimated from both WRF model ($R^2=0.68$) and radiosonde ($R^2=0.72$). However, PBLH from lidar tend to be overestimated in comparison with those from both WRF and radiosonde because lidar appears to detect height of Residual Layer (RL) as PBLH which is overall below near the overlap height (< 300 m). PBLH from lidar with 10 min time resolution shows typical diurnal variation since it grows up after sunrise and reaches the maximum after 2 hours of sun culmination. The average growth rate of PBLH during the analysis period (2014/06/26 ~ 30) is 1.79 (-2.9 ~ 5.7) m $min^{-1}$. In addition, the lidar signal measured from moving LIVE shows that there is very low noise in comparison with that from the stationary observation. The PBLH from LIVE is 1065 m, similar to the value (1150 m) derived from the radiosonde launched at Sokcho. This study suggests that LIVE can observe continuous and reliable PBLH with high resolution in both stationary and mobile systems.

• Korean Journal of Agricultural and Forest Meteorology
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• v.17 no.2
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• pp.108-125
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• 2015

The agro-climatic index is one of the ways to assess the climate resources of particular agricultural areas on the prospect of agricultural production; it can be a key indicator of agricultural productivity by providing the basic information required for the implementation of different and various farming techniques and practicalities to estimate the growth and yield of crops from the climate resources such as air temperature, solar radiation, and precipitation. However, the agro-climate index can always be changed since the index is not the absolute. Recently, many studies which consider uncertainty of future climate change have been actively conducted using multi-model ensemble (MME) approach by developing and improving dynamic and statistical downscaling of Global Climate Model (GCM) output. In this study, the agro-climatic index of Korean Peninsula, such as growing degree day based on $5^{\circ}C$, plant period based on $5^{\circ}C$, crop period based on $10^{\circ}C$, and frost free day were calculated for assessment of the spatio-temporal variations and uncertainties of the indices according to climate change; the downscaled historical (1976-2005) and near future (2011-2040) RCP climate sceneries of AR5 were applied to the calculation of the index. The result showed four agro-climatic indices calculated by nine individual GCMs as well as MME agreed with agro-climatic indices which were calculated by the observed data. It was confirmed that MME, as well as each individual GCM emulated well on past climate in the four major Rivers of South Korea (Han, Nakdong, Geum, and Seumjin and Yeoungsan). However, spatial downscaling still needs further improvement since the agro-climatic indices of some individual GCMs showed different variations with the observed indices at the change of spatial distribution of the four Rivers. The four agro-climatic indices of the Korean Peninsula were expected to increase in nine individual GCMs and MME in future climate scenarios. The differences and uncertainties of the agro-climatic indices have not been reduced on the unlimited coupling of multi-model ensembles. Further research is still required although the differences started to improve when combining of three or four individual GCMs in the study. The agro-climatic indices which were derived and evaluated in the study will be the baseline for the assessment of agro-climatic abnormal indices and agro-productivity indices of the next research work.

• Korean Journal of Environmental Biology
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• v.24 no.4
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• pp.392-407
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• 2006

This study was seasonally undertaken to investigate the benthic polychaetous community along the South-eastern coast of Geoje Is., in February 2004 to November. The macrobenthic fauna showed mean density of 953 md. $m^{-2}$ in February, 1,193 ind. $m^{-2}$ in May, 1,130 ind. $m^{-2}$ in September and 991 ind. $m^{-2}$ in November. Major faunal groups are polychaetes, crustaceans and mollusks, corresponding to 81.6%, 7.9%, 7.0% in total mean density during the sampling seasons, respectively. There was significant difference (two-way ANOVA, p<0.001) among stations in densities of polychaetes. But no significant relationship could be found between the densities of polychaetes and sampling seasons (two-way ANOVA, p>0.05). The density and the species number of polychaetes were high in the coastal area near the Jisepo port, independent of sampling seasons. Several indicator species for the organically enriched environments such as Lumbrineris longifolia, Tharyx sp., Heteromastus filiformis showed high densities during all study periods. Also Magelona japonica included in Ecolgical group I was the most abundant in the whole study period except for February. Cluster analysis on the basis of the species composition showed that the study area could be divided into 3 regions. The density of benthic polychaetes in the coastal area near Jisepo was higher than that in the other assemblages of the study area, due to some predominant opportunistic species, such as Lumbrineris longifolia, Tharyx sp. and Heteromastus filiformis. In addition, the two-way ANOVA showed significant differences among the distribution of AMBI (AZTI's Marine Biotic Index) values, both in sampling stations (p<0.001) and seasons (p<0.01). According to the classification proposed by Borja et at. (2000), the study area was slightly disturbed site.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.28 no.4
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• pp.475-488
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• 1995

In order to see the seasonal variation of nutrients and the limiting factors to the primary production in Deukryang Bay, both dissolved inorganic nutrients and salinity were measured in the surface waters during the periods from July 1992 to March 1993. The mean value of salinity was the lowest in ?all and the highest in early spring. Dissolved inorganic nitrogen (DIN) was the highest in winter and the lowest in summer. However, both phosphate and silicate were the highest in summer and the lowest in fall. Salinity was generally higher in the outer region than in the inner region of the bay.DIN content was nearly depleted (less than $2{\mu}M$) in summer. From fall to spring, DIN content was nearly depleted in the inner region and relatively high in the outer region of the Day. Phosphate was the highest in summer showing an opposite distribution pattern to salinity, and it was nearly depleted (less than $0.1{\mu}M$) in fall and winter. In spring, however, phosphate content was slightly high in the outer region. Silicate content showed an opposite distribution pattern to salinity in summer. in other seasons, However, the distribution pattern of silicate was similar to the salinity. DIN seemed to be a limiting factor for the primary production at all area of the bay in summer and at the inner region in other season. However, phosphate seemed to be a limiting factor at all area of the bay in fall and winter and at the inner region in spring. Silicate may limit the production of diatoms at the inner region of the bay in winter and spying. Both phosphate and silicate showed a good inverse relationship with salinity in summer, which indicates inputs of these nutrients from the freshwater runoff. In the other seasons, both nitrate and silicate showed a positive linear relationship with salinity in the outer region of the bay, suggesting that these two nutrients were mainly supplied by the inflow of the offshore costal water which had high nitrate content associated with vertical mixing.

• Journal of Korean Society for Atmospheric Environment
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• v.34 no.2
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• pp.306-320
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• 2018

Emission inventory is the essential component for improving the performance of air quality forecasting system. This study evaluated the simulated daily mean $PM_{2.5}$ concentrations in South Korea and China for 1-year period (Sept. 2016~Aug. 2017) using air quality forecasting system which was applied by the emission inventory of E2015 (predicted CAPSS 2015 for South Korea and KORUS 2015 v1 for the other regions). To identify the impacts of emissions on the simulated $PM_{2.5}$, the emission inventory replaced by E2010 (CAPSS 2010 and MIX 2010) were also applied under the same forecasting conditions. These results showed that simulated daily mean $PM_{2.5}$ concentrations had generally suitable performance with both emission data-sets for China (IOA>0.87, R>0.87) and South Korea (IOA>0.84, R>0.76). The impacts of the changes in emission inventories on simulated daily mean $PM_{2.5}$ concentrations were quantitatively estimated. In China, normalized mean bias (NMB) showed 5.5% and 26.8% under E2010 and E2015, respectively. The tendency of overestimated concentrations was larger in North Central and Southeast China than other regions under both E2010 and E2015. Seasonal differences of NMB were higher in non-winter season (28.3% (E2010)~39.3% (E2015)) than winter season (-0.5% (E2010)~8.0% (E2015)). In South Korea, NMB showed -5.4% and 2.8% for all days, but -15.2% and -11.2% for days below $40{\mu}g/m^3$ to minimize the impacts of long-range transport under E2010 and E2015, respectively. For all days, simulated $PM_{2.5}$ concentrations were overestimated in Seoul, Incheon, Southern part of Gyeonggi and Daejeon, and underestimated in other regions such as Jeonbuk, Ulsan, Busan and Gyeongnam, regardless of what emission inventories were applied. Our results suggest that the updated emission inventory, which reflects current status of emission amounts and spatio-temporal allocations, is needed for improving the performance of air quality forecasting.

• Journal of the Korean Geographical Society
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• v.42 no.5
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• pp.808-834
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• 2007

This study attempts to elucidate manifold dimensions of gendered accessibility experiences. How gender roles(household responsibilities) differentiate accessibility experiences between women and men is explored through the comparison of married dual-earner couples' parental status, using the US Portland activity-travel diary dataset with GIS-based geocomputation results of(time-geography based) space-time accessibility. First, this study shows how gender division of labor within the household still permeates current society, despite the widespread belief of the social change toward a gender-egalitarian society. Then, the study pays special attention to the way gender roles structure individual accessibility experiences of women and men differently, and, in turn, the way such accessibility experiences take a form of gendered spatiality. Gendered spatiality is examined through the analysis of accessibility space as well as activity space in order to ascertain women's home-attached and spatially entrapped characteristics. More household responsibilities throughout a day and, even more, the time constraint of picking up children at the daycare centers after work lead women's possible activity space to be more home-centered. The analysis of the spatio-temporal context of accessibility space makes gendered spatiality visible. However, the findings suggest that behavioral outcomes should be understood with an explicit awareness of constraints individuals face. It is because the revealed activity spaces can be not only an outcome of constraint but also an outcome of choice. Behavioral outcomes should not be treated as a straightforward expression of the level of constraints. It is problematic to expect that behavioral outcomes directly mirror the level of constraints. It is also problematic to suppose that the level of constraints can be straightforwardly elicited from revealed behavioral outcomes.

• Spatial Information Research
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• v.22 no.1
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• pp.55-63
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• 2014

Near surface air temperature data which are one of the essential factors in hydrology, meteorology and climatology, have drawn a substantial amount of attention from various academic domains and societies. Meteorological observations, however, have high spatio-temporal constraints with the limits in the number and distribution over the earth surface. To overcome such limits, many studies have sought to estimate the near surface air temperature from satellite image data at a regional or continental scale with simple regression methods. Alternatively, we applied various Kriging methods such as ordinary Kriging, universal Kriging, Cokriging, Regression Kriging in search of an optimal estimation method based on near surface air temperature data observed from automatic weather stations (AWS) in South Korea throughout 2010 (365 days) and MODIS land surface temperature (LST) data (MOD11A1, 365 images). Due to high spatial heterogeneity, auxiliary data have been also analyzed such as land cover, DEM (digital elevation model) to consider factors that can affect near surface air temperature. Prior to the main estimation, we calculated root mean square error (RMSE) of temperature differences from the 365-days LST and AWS data by season and landcover. The results show that the coefficient of variation (CV) of RMSE by season is 0.86, but the equivalent value of CV by landcover is 0.00746. Seasonal differences between LST and AWS data were greater than that those by landcover. Seasonal RMSE was the lowest in winter (3.72). The results from a linear regression analysis for examining the relationship among AWS, LST, and auxiliary data show that the coefficient of determination was the highest in winter (0.818) but the lowest in summer (0.078), thereby indicating a significant level of seasonal variation. Based on these results, we utilized a variety of Kriging techniques to estimate the surface temperature. The results of cross-validation in each Kriging model show that the measure of model accuracy was 1.71, 1.71, 1.848, and 1.630 for universal Kriging, ordinary Kriging, cokriging, and regression Kriging, respectively. The estimates from regression Kriging thus proved to be the most accurate among the Kriging methods compared.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.26 no.4
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• pp.197-206
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• 2014

The purpose of this study is to evaluate coastal erosion due to a sea-level rise. The shoreline retreat rate was calculated due to future sea-level rise. Shoreline retreat rates were quantified with the cross-sectional data of 23 sandy coasts (12 sites from east coast, 5 sites from south coast, and 6 sites of west coast) and 3 cross-sectional profiles from each side of the coasts in Korea. The theory of equilibrium beach profile was employed in this study to evaluate the applicability of the theory into the coast of Korea and was tested with 15 cross-sectional beach profiles. Four scenarios of future sea level rise such as 38 cm, 59 cm, 75 cm, and 100 cm were adopted to estimate the shoreline retreat rates. Overall shoreline retreat rates for the coasts in Korea were predicted as 43.7% for 38 cm, 60.3% for 59 cm, 69.2% for 75 cm, and 80.1% for 100 cm sea level rises, respectively. Retreat rates in the east coast (29.6% for 38 cm, 45.1% for 59 cm, 56.0% for 75 cm, and 69.9% for 100 cm) showed relatively low compared to the south coast (51.9%, 67.6%, 77.2%, 87.3%) and the west coast (53.8%, 71.0%, 78.5%, 86.4%). However, all sandy coasts in Korea were assessed to be vulnerable with increasing sea-level rise. There are uncertainties in the assessment of this study, which include the limitation of the assessment model and the lack of the spatio-temporal data of the beach profiles. Therefore, this study shows that it is very important to spend integrated efforts to respond coastal erosion including comprehensive observations(monitoring) and the development of scientific understanding on the field.

• Economic and Environmental Geology
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• v.48 no.1
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• pp.51-63
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• 2015

I produced a secular variation model of geomagnetic field by using the magnetic component data from four geomagnetic observatories located in Northeast Asia during the years between 1997 and 2011. The Earth's magnetic field varies with time and location due to the dynamics of fluid outer core and the magnetic observatories on the surface measure in time series. To adequately represent the magnetic field or secular variations of the Earth, a spatio-temporal model is required. In making a global model, satellite observations as well as limited observatory data are necessary to cover the regions and time intervals. However, you need a considerable work and time to process a huge amount of the dataset with complicated signal separation procedures. When you update the model, the same amount of chores is demanded. Besides, the global model might be affected by the measurement errors of each observatory that are biased and the processing errors in satellite data so that the accuracy of the model would be degraded. In this study, as considered these problems, I introduced a localized method in modeling secular variation of the Earth's magnetic field over Northeast Asia region. Secular variation data from three Japanese observatories and one Chinese observatory that are all in the INTERMAGNET are implemented in the model valid between 1997 to 2011 with the interval of 6 months. With the resulting model, I compared with the global model called CHAOS-4, which includes the main, secular variation and secular acceleration models between 1997 to 2013 by using the three satellites' databases and INTERMAGNET observatory data. Also, the geomagnetic 'jerk' which is known as a sudden change in the time derivatives of the main field of the Earth, was discussed from the localized secular acceleration coefficients derived from spline models.

• Korean Journal of Environmental Biology
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• v.22 no.1
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• pp.57-65
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• 2004

In order to determine the effect of fresh water inflow from the Heongsan river on the changes of water quality in the Yeongil Bay (Korea), the seasonal changes of water temperature, salinity, chemical oxygen demand (COD), dissolved inorganic nitrogen(DIN) and phosphate phosphorus ($PO_4$-P) concentrations were examined using the data set obtained five fixed points of Yeongil Bay from 1998 to 2000. The distributions and changes of COD and concentrations of total inorganic phosphorous (TIP) and nitrogen (TIN) at three points Heongsan river, were also compared with those of Yeongil Bay. Based on the correlations of DIN and $PO_4$-P, it was found that the inflow of freshwater affected on the water quality of Yeongil Bay. Such a complicacy was confirmed by the prominent differences in n few water quality measures between Site 1(the innermost area) and Site 5 (the mouth of the bay). The negative correlations in $\Delta N/\Delta P $ at sites 1, 2 and 3 of the inner-part of the bay also indicated a large effect of freshwater inflow on the water quality of the bay. The extremely low atomic ratio of an average of 6.4 in $\Delta N/\Delta P $ compared to the Redfild ratio suggested that the DIN was depleted in the overall bay system. In contrast, it was inferred that the excessive PO$_4$-P concentration was due to the inflow of freshwater from the Heongsan river.