• 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.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.14 no.11
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• pp.6008-6014
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• 2013

This study aimed to understand seasonal variation of physico-chemical factors and biomass of size-fractionated phytoplankton at Ulsan seaport during the period from February 2007 to November 2009. Water temperature, salinity, dissolved oxygen (DO), pH, chemical oxygen demand (COD) and total suspended solid (TSS) varied in the range of 8.94-$24.26^{\circ}C$, 25.06-34.54 psu, 4.30-10.73 mg/L, 7.97-8.53, 0.66-40.70 mg/L and 57.4-103.3 mg/L, respectively. These factors showed no clear spatial variation unlike spatial pattern of inorganic nutrients and total chlorophyll-a (chl-a) concentration as biomass. Concentration of phosphate, nitrate and silicate ranged from 0.01 to 3.03 ${\mu}M$, 0.05 to 21.62 ${\mu}M$, and 0.01 to 27.82 ${\mu}M$, respectively, with 2 times higher concentration at inner stations than that at outer stations during the study period. Within the range of total chl-a concentration (0.36-7.11 ${\mu}gL^{-1}$), higher concentration (avg. 1.88 ${\mu}gL^{-1}$) of total chl-a were observed at inner stations compared to that (avg. 0.90 ${\mu}gL^{-1}$) at outer stations. Micro-sized phytoplankton dominated total biomass of phytoplankton in spring (34.0-81.2%), summer (35.1-65.6%) and winter (3.9-62.0%). Nano- and pico-sized phytoplankton contributed 58.2-74.5% and 22.4-38.2% to total biomass of phytoplankton in autumn, respectively. However, contribution in biomass of size-fractionated phytoplankton to total phytoplankton biomass showed no clear difference between inner and outer stations. Consequently, these results indicated that spatio-temporal distribution of phytoplankton biomass at Ulsan seaport was dominated by micro-phytoplankton (avg. 52.3%) during the study period except autumn, which was closely dependent on the concentration of inorganic nutrients (p<0.05).

• Korean Journal of Fisheries and Aquatic Sciences
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• v.29 no.1
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• pp.84-91
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• 1996

Heat flux of the East China Sea was estimated with the bulk method, the East China mount based on the marine meteorological data and cloud amount data observed by a satellite. Solar radiation is maximum in May and minimum in December. Its amount decreases gradually southward during the winter half year (from October to March), and increases northward during the summer half year (from April to September) due to the influence of Changma (Baiu) front. The spatial difference of long-wave radiation is relatively small, but its temporal difference is quite large, i.e., the value in February is about two times greater than that in July. The spatial patterns of sensible and latent heat fluxes reflect well the effect of current distribution in this region. The heat loss from the ocean surface is more than $830Wm^{-2}$ in winter, which is five times greater than the net radiation amount during the same period, The annual net heat flux is negative, which means heat loss from the sea surface, in the whole region over the East China Sea. The region with the largest loss of more than $400Wm^{-2}$ in January is observed over the southwestern Kyushu. The annual mean value of solar radiation, long-wave radiation, sensible and latent heat fluxes are estimated $187Wm^{-2},\;-52Wm^{-2},\;-30Wm^{-2}\;and\;-137Wm^{-2}$, respectively, consequently the East China Sea losses the energy of $32Wm^{-2}(2.48\times10^{13}W)$. Through the heat exchange between the air and the sea, the heat energy of $0.4\times10^{13}W$ is supplied from the air to the sea in A region (the Yellow Sea), $2.1\times10^{13}W$ in B region (the East China Sea) and $1.7\times10^{13}W$ in C region (the Kuroshio part), respectively.

• Korean Journal of Remote Sensing
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• v.37 no.5_1
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• pp.959-974
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• 2021

Forel-Ule Index (FUI) is an index which classifies the colors of inland and seawater exist in nature into 21 gradesranging from indigo blue to cola brown. FUI has been analyzed in connection with the eutrophication, water quality, and light characteristics of water systems in many studies, and the possibility as a new water quality index which simultaneously contains optical information of water quality parameters has been suggested. In thisstudy, Ocean Colour-Climate Change Initiative (OC-CCI) based 4 km FUI was spatially downscaled to the resolution of 500 m using the Geostationary Ocean Color Imager (GOCI) data and Random Forest (RF) machine learning. Then, the RF-derived FUI was examined in terms of its correlation with various water quality parameters measured in coastal areas and its spatial distribution and seasonal characteristics. The results showed that the RF-derived FUI resulted in higher accuracy (Coefficient of Determination (R²)=0.81, Root Mean Square Error (RMSE)=0.7784) than GOCI-derived FUI estimated by Pitarch's OC-CCI FUI algorithm (R²=0.72, RMSE=0.9708). RF-derived FUI showed a high correlation with five water quality parameters including Total Nitrogen, Total Phosphorus, Chlorophyll-a, Total Suspended Solids, Transparency with the correlation coefficients of 0.87, 0.88, 0.97, 0.65, and -0.98, respectively. The temporal pattern of the RF-derived FUI well reflected the physical relationship with various water quality parameters with a strong seasonality. The research findingssuggested the potential of the high resolution FUI in coastal water quality management in the Korean Peninsula.

• Korean Journal of Ecology and Environment
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• v.39 no.3 s.117
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• pp.378-389
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• 2006

Seasonal changes of biomass and cell size of bacteria and protozoa, and factors affecting their distribution in Lake Paldang and Kyungan Stream were analyzed from April to December, 2005. Bacterial abundance at Paldang Dam and Kyungan Stream was similar, but it did not much increase during hot summer period. Protozoan carbon biomass was much greater at Kyungan Stream compared to Paldang Dam. HNAN generally accounted for the majority of total protozoan biomass, but ciliates made up the highest proportion in April and November at Paldang Dam and June at both sites. PNAN showed low biomass at both sites, but it was high during spring and fall season. Small-sized HNAN ($3{\sim}7\;{\mu}m$) numerically predominated the protozoan community at both sites. Average cell size of HNAN was bigger at Kyungan Stream where nutrients concentration was much higher than Paldang Dam. Average cell size of ciliates varied seasonally; it was relatively small during the summer. HNAN biomass significantly correlated with Chl-a concentration and ciliates biomass at Paldang Dam, indicating that HNAN increase might link to the ciliates increase. At Kyungan Stream, HNAN biomass showed a significant relationship with PNAN biomass, and Chl-a concentration was closely related with both of HNAN and PNAN biomass. Ciliate biomass showed significant relationship with nutrient (TN, TP) and particulate matter (SS) only at Kyungan Stream. At both sites, protozoan biomass was significantly correlated with bacterial biomass, and ciliates were additionally related flagellates. High biomass of microbial components and the close relationships among them suggest that the energy transfer through the microbial loop may important in the plankton food web of Lake Paldang ecosystem.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.29 no.4
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• pp.206-216
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• 2017

The temporal distribution of the turbulence kinetic energy (TKE) and the vertical component of Reynolds stresses ($-{\bar{u^{\prime}w^{\prime}}}$) was measured during one wave period under high wave energy conditions. The wave data were obtained at Hujeong Beach in the east coast of Korea at January 14~18 of 2017 when an extratropical cyclone was developed in the East Sea. Among the whole thousands of waves measured during the period, hundreds of regular waves that had with similar pattern were selected for the analysis in order to give three representing mean wave patterns using the ensemble average technique. The turbulence properties were then estimated based on the selected wave data. It is interesting to find out that $-{\bar{u^{\prime}w^{\prime}}}$ has one clear peak near the time of flow reversal while TKE has two peaks at the corresponding times of maximum cross-shore velocity magnitudes. The distinguished pattern of Reynolds stress indicates that vertical fluxes of such properties as suspended sediments may be enhanced at the time when the horizontal flow direction is reversed to disturb the flows, supporting the turbulence convection process proposed by Nielsen (1992). The characteristic patterns of turbulence properties are examined using the CADMAS-SURF Reynolds-Averaged Navier-Stokes (RANS) model. Although the model can reasonably simulate the distribution of TKE pattern, it fails to produce the $-{\bar{u^{\prime}w^{\prime}}}$ peak at the time of flow reversal, which indicates that the application of RANS model is limited in the prediction of some turbulence properties such as Reynolds stresses.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.7 no.1
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• pp.20-31
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• 2002

This study was carried out to investigate the composition and the distribution of the benthic polychaetous communities in Deugryang Bay, semi-enclosed bays, on the southern coast of Korea and to deduce temporal changes in community with the comparison of the past studies. In Deugryang Bay, benthic polychaetous community structure was investigated on the base of the samples from 98 stations in 1996 and 1997. The main facies of surface sediment was clayey silt. The overall benthic macrofaunal density was 871 ind./m$^{2}$. The density was highest in the middle part of the bay because Musculus senhousia (Bivalvia) and cumaceans (Crustacea) had their highest densities in some stations. Benthic polychaetes were comprised of 100 species with a mean density of 138 ind./m$^{2}$. Their abundances were higher in the inner bay, in the middle bay, and in the mouth of bay, but poor community structures were established in the whole bay. The dominant species over 1.0 percentage were composed of the total 21 species, and they occupied 78.3% of the total abundance of the benthic polychaetes. The most dominant species was Lumbrineris longifolia (9.3%), followed by Eteone longa (7.3%), Heteromastus filifomis (7.1%), Sternaspis scutata (6.1%). From the cluster analysis, the study area could be divided into three station groups. Station group AI was located in the inner bay and in the shallow coastal region, and its most dominant species was Heteromastus filiformis. At the station group AII in the mouth of bay and in some channel region, its most dominant species were Lumbrineris longifolia and Eteone longa. And at the station group B located in middle part of the bay, the most dominant specis was Sternaspis scutata. In comparison with previous studies, the benthic polychaetous community experienced great change in the view of species number, density and dominant species. The dominant species were Sternaspis scutata and Eteone longa, but their densities declined greatly. Instead of these species, Lumbrineris longifolia and Heteromastus filiformis, known as the potential organic enrichment indicator species, appeared to the new dominant species even if their low densities. These facts mean that Deugryang Bay was maintained yet as little organic enriched area compared to other bays on the coast of Korea, but needed some caution of marine environmental management.

• Korean Journal of Remote Sensing
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• v.39 no.6_2
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• pp.1635-1650
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• 2023

Under global warming, the steadily increasing sea surface temperature (SST) severely impacts marine ecosystems,such as the productivity decrease and change in marine species distribution. Recently, the catch of Todarodes Pacificus, one of South Korea's primary marine resources, has dramatically decreased. In this study, we analyze the marine environment that affects the formation of fishing grounds of Todarodes Pacificus and develop seasonal habitat suitability index (HSI) models based on various satellite data including Geostationary Ocean Color Imager (GOCI) data to continuously manage fisheries resources over Korean exclusive economic zone. About 83% of catches are found within the range of SST of 14.11-26.16℃,sea level height of 0.56-0.82 m, chlorophyll-a concentration of 0.31-1.52 mg m^-3, and primary production of 580.96-1574.13 mg C m^-2 day^-1. The seasonal HSI models are developed using the Arithmetic Mean Model, which showed the best performance. Comparing the developed HSI value with the 2019 catch data, it is confirmed that the HSI model is valid because the fishing grounds are formed in different sea regions by season (East Sea in winter and Yellow Sea in summer) and the high HSI (> 0.6) concurrences to areas with the high catch. In addition, we identified the significant increasing trend in SST over study regions, which is highly related to the formation of fishing grounds of Todarodes Pacificus. We can expect the fishing grounds will be changed by accelerating ocean warming in the future. Continuous HSI monitoring is necessary to manage fisheries' spatial and temporal distribution.

• Korean Journal of Remote Sensing
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• v.39 no.5_3
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• pp.933-948
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• 2023

Atmospheric aerosols not only have adverse effects on human health but also exert direct and indirect impacts on the climate system. Consequently, it is imperative to comprehend the characteristics and spatiotemporal distribution of aerosols. Numerous research endeavors have been undertaken to monitor aerosols, predominantly through the retrieval of aerosol optical depth (AOD) via satellite-based observations. Nonetheless, this approach primarily relies on a look-up table-based inversion algorithm, characterized by computationally intensive operations and associated uncertainties. In this study, a novel high-resolution AOD direct retrieval algorithm, leveraging machine learning, was developed using top-of-atmosphere reflectance data derived from the Geostationary Ocean Color Imager-II (GOCI-II), in conjunction with their differences from the past 30-day minimum reflectance, and meteorological variables from numerical models. The Light Gradient Boosting Machine (LGBM) technique was harnessed, and the resultant estimates underwent rigorous validation encompassing random, temporal, and spatial N-fold cross-validation (CV) using ground-based observation data from Aerosol Robotic Network (AERONET) AOD. The three CV results consistently demonstrated robust performance, yielding R²=0.70-0.80, RMSE=0.08-0.09, and within the expected error (EE) of 75.2-85.1%. The Shapley Additive exPlanations(SHAP) analysis confirmed the substantial influence of reflectance-related variables on AOD estimation. A comprehensive examination of the spatiotemporal distribution of AOD in Seoul and Ulsan revealed that the developed LGBM model yielded results that are in close concordance with AERONET AOD over time, thereby confirming its suitability for AOD retrieval at high spatiotemporal resolution (i.e., hourly, 250 m). Furthermore, upon comparing data coverage, it was ascertained that the LGBM model enhanced data retrieval frequency by approximately 8.8% in comparison to the GOCI-II L2 AOD products, ameliorating issues associated with excessive masking over very illuminated surfaces that are often encountered in physics-based AOD retrieval processes.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.17 no.4
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• pp.292-302
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• 2012

This paper reviews comparison analysis of current and latest application for stock identification methods of Todarodes pacificus, and the pros and cons of each method and consideration of how to compensate for each other. Todarodes pacificus which migrates wide areas in western North Pacific is important fishery resource ecologically and commercially. Todarodes pacificus is also considered as 'biological indicator' of ocean environmental changes. And changes in its short and long term catch and distribution area occur along with environmental changes. For example, while the catch of pollack, a cold water fish, has dramatically decreased until today after the climate regime shift in 1987/1988, the catch of Todarodes pacificus has been dramatically increased. Regarding the decrease in pollack catch, overfishing and climate changes were considered as the main causes, but there has been no definite reason until today. One of the reasons why there is no definite answer is related with no proper analysis about ecological and environmental aspects based on stock identification. Subpopulation is a group sharing the same gene pool through sexual reproduction process within limited boundaries having similar ecological characteristics. Each individual with same stock might be affected by different environment in temporal and spatial during the process of spawning, recruitment and then reproduction. Thereby, accurate stock analysis about the species can play an efficient alternative to comply with effective resource management and rapid changes. Four main stock analysis were applied to Todarodes pacificus: Morphologic Method, Ecological Method, Tagging Method, Genetic Method. Ecological method is studies for analysis of differences in spawning grounds by analysing the individual ecological change, distribution, migration status, parasitic state of parasite, kinds of parasite and parasite infection rate etc. Currently the method has been studying lively can identify the group in the similar environment. However It is difficult to know to identify the same genetic group in each other. Tagging Method is direct method. It can analyse cohort's migration, distribution and location of spawning, but it is very difficult to recapture tagged squids and hard to tag juveniles. Genetic method, which is for useful fishery resource stock analysis has provided the basic information regarding resource management study. Genetic method for stock analysis is determined according to markers' sensitivity and need to select high multiform of genetic markers. For stock identification, isozyme multiform has been used for genetic markers. Recently there is increase in use of makers with high range variability among DNA sequencing like mitochondria, microsatellite. Even the current morphologic method, tagging method and ecological method played important rolls through finding Todarodes pacificus' life cycle, migration route and changes in spawning grounds, it is still difficult to analyze the stock of Todarodes pacificus as those are distributed in difference seas. Lately, by taking advantages of each stock analysis method, more complicated method is being applied. If based on such analysis and genetic method for improvement are played, there will be much advance in management system for the resource fluctuation of Todarodes pacificus.