Journal of Korean Society for Atmospheric Environment
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v.24
no.1
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pp.83-90
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2008
In order to clarify the urbanization intensity of Daegu Metropolitan and its characteristics, comparative study on the variation of the cooling rate of two different sites was carried out using observation data for 40 years by Korea Meteorological Adminstration. Daegu Metropolitan and Chupungnyung represent well urbanized and rural areas, respectively. In comparison with Chupungnyung, yearly mean temperature at Daegu Metropolitan increases rapidly and especially the differences of minimum temperature increasing rate during 40 years becomes greater. These differences of regional warming are caused by the different urbanization intensity between two sites. And the impact of anthropogenic heat due to urbanization should be stronger in nighttime than in daytime. Sensible heat advection by regional wind during 6 hours from 18 LST contributes to atmospheric cooling. For this reason wind speed is in proportion to cooling rate of atmosphere. However, wind after 24 LST induces the warm air advection and makes decrease the cooling rate in urban area. Although the cooling rates between Daegu Metropolitan and Chupungnyung are some different, the variation tendencies of cooling rate of two site are almost same. Therefore atmospheric cooling rate in nighttime tends to be associated with the intensity of wind speed.
Han J. S.;Kim Y. M.;Ahn J. Y.;Kong B. J.;Choi J. S.;Lee S. U.;Lee S. J.
Journal of Korean Society for Atmospheric Environment
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v.22
no.1
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pp.99-106
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2006
Aircraft measurements have been executed for the purpose of monitoring the long range transported air pollution and estimation of air pollutant in/out-flux over the Yellow sea. Total 74 missions of measurements have been done since 1997, mainly in spring and fall. The main study domain was over $124^{\circ}$E $/sim$$124^{\circ}$E, $35^{\circ}$N $/sim$$37^{\circ}$N below 3,000m. In long-term trends, mixing ratios of $SO_{2}$N were around 2 ppbv expect in summer ( < 1 ppbv). NOx exhibited 24 ppbv and have no clear annual trends over the Yellow Sea. The concentrations of 03 were 51, 58, 41 ppbv in spring, summer and fall-winter, respectively. Backward trajectory was performed for three days to investigate the source regions of the air mass. Six regions were divided around Korea peninsular centering at $36^{\circ}$N, $126^{\circ}$E. I, II, III, IV and V regions represents in sequence northeast China and Siberia, Sandong peninsula and Balhae gulf, Sanghi and southern China, the south Pacific included Jeju island and the East sea included Japan. L region correspond to the airmass from Korea peninsula. Influx of $SO_{2}$N was approximately five times higher than outflux in yearly flux variation and showed a decreasing long-term trend since 1998. NOx outflux was average 0.095 ton/km/hr and three times higher than $SO_{2}$ outflux. In/out flux of 03 showed even distribution in yearly basis except 2002 (influx 5.45 ton/km/hr). The transported amounts from I, II, III regions were much higher than those from other region. In seasonal flux variation, influx levels of gas phases were the lowest in summer and the levels gradually increased from fall toward spring. As a result, transport of pollutants begins from fall and prevails in winter and spring.
Korean Journal of Agricultural and Forest Meteorology
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v.4
no.3
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pp.164-168
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2002
Yield prediction model of rice based on the boundary line analysis of the relationships between rice yield and meteorological conditions during rice growing period was reported in the previous report (Kim et al, 2001). Using the 15-year data of the 20 locations used for the model formulation and of the 12 locations not used, the model was tested for its predictability of location to location, year to year, and variety to variety variation of rice yield. The model predicted reliably the mean yield differences among locations, the yearly yield variation in each location, and the yield variation by variety. However, the model showed relatively lower predictability for the years of cool weather injury especially in mountainous locations. In conclusion, the model using boundary line analysis could be used to predict the yield responses to meteorological conditions during rice growth period and the locational, yearly, and varietal variations of rice yield. And the predictability of the present yield prediction model might be improved by including the boundary line analysis for the other factors such as soil characteristics, fertilization levels, etc.
The present study was to develop an approach for predicting soybean yield using a crop growth simulation model at the regional level where the detailed and site-specific information on cultivation management practices is not easily accessible for model input. CROPGRO-Soybean model included in Decision Support System for Agrotechnology Transfer (DSSAT) was employed for this study, and Illinois which is a major soybean production region of USA was selected as a study region. As a first step to predict soybean yield of Illinois using CROPGRO-Soybean model, genetic coefficients representative for each soybean maturity group (MG I~VI) were estimated through sowing date experiments using domestic and foreign cultivars with diverse maturity in Seoul National University Farm ($37.27^{\circ}N$, $126.99^{\circ}E$) for two years. The model using the representative genetic coefficients simulated the developmental stages of cultivars within each maturity group fairly well. Soybean yields for the grids of $10km{\times}10km$ in Illinois state were simulated from 2,000 to 2,011 with weather data under 18 simulation conditions including the combinations of three maturity groups, three seeding dates and two irrigation regimes. Planting dates and maturity groups were assigned differently to the three sub-regions divided longitudinally. The yearly state yields that were estimated by averaging all the grid yields simulated under non-irrigated and fully-Irrigated conditions showed a big difference from the statistical yields and did not explain the annual trend of yield increase due to the improved cultivation technologies. Using the grain yield data of 9 agricultural districts in Illinois observed and estimated from the simulated grid yield under 18 simulation conditions, a multiple regression model was constructed to estimate soybean yield at agricultural district level. In this model a year variable was also added to reflect the yearly yield trend. This model explained the yearly and district yield variation fairly well with a determination coefficients of $R^2=0.61$ (n = 108). Yearly state yields which were calculated by weighting the model-estimated yearly average agricultural district yield by the cultivation area of each agricultural district showed very close correspondence ($R^2=0.80$) to the yearly statistical state yields. Furthermore, the model predicted state yield fairly well in 2012 in which data were not used for the model construction and severe yield reduction was recorded due to drought.
This study was conducted to evaluate water quality in the Keum River using multivariate analysis. The analysis data in Keum river made use of surveyed data by the ministry of environment from January 1994 to December 2001. Thirteen water quality parameter were determined on each sample. The results was summarized as follow; Water quality in the Keum River could be explained up to 71.39% by four factors which were included in loading of organic matter and nutrients by the tributaries (32.88%), seasonal variation (16.09%), loading of pathogenic bacteria by domestic sewage of Gapcheon (13.39%) and internal metabolism in estuary as lakes(9.03%). For spatial variation of factor score, four group was classified by each factor characterization. Station 1 and 2 was influenced by Daechung dam, station 3 was affected by domestic sewage of Gapcheon, station 10~12 was affected by estuary dyke and the rest station. The result of cluster analysis by station was classified into four group that has different water quality characteristics. In monthly cluster analysis, three group was classified according to seasonal characteristic. Also, in yearly cluster analysis, three group was classified. It is necessary to control the pollutant loadings by Gapcheon inflow domestic sewage in Daejeon city for the sake of water quality management of Keum river.
Seasonal and spatial variations in propagule numbers of Trichoderma species were investigated every other month for one year in deciduous and coniferous forest soils and evaluated the relationships of Trichoderma spp. populations to soil environmental factors. The total population of Trichoderma spp. increased until summer and then declined until winter. The yearly mean frequency of Trichoderma spp. exceeded 1.4% of total fungal propagules in two sites. Decreases of absolute an relative propagule numbers of Trichoderma spp. with increasing soil depth were found and variation in Trichoderma spp. propagules caused by differences in soil depth ($0{\sim}50cm$) was greater than that caused by differences in sampling time. The most common species occurring in two sites was T. viride, followed by T. polysporum, T. koningii, and T. hamatum. Individual species of Trichoderma showed diferent abundance trend in accordance with sampling time. T. viride was dorminant from spring to autumn, while T. polysporum dominated over the other speicies in winter. Variations in propagule number of Trichoderma sppp. were principally mediated by the actions of biotic environmental factors rather than by the direct effects of abiotic factors. In multiple-regression analyses, 48% of the total vaiation in Trichoderma spp. propagules in deciduous site could be accounted for by total fungal propagules and soil CMCase actvity. In coniferous site, 65% of total variation could be accounted for by total fungal and bacterial propagules, moisture content and organic carbon content.
To recognize the spatial and temporal variability of water temperature and dissolved oxygen in the Youngsan reservoir formed after dike construction, water temperature and dissolved oxygen data have been observed and analyzed from April, 2002 until March, 2003. As the results, certain stratifications were not distinctly observed in the Youngsan reservoir during summer, which was estimated due to the drainage characteristic from the Youngsan water gates. The yearly variation of water temperature in the Youngsan reservoir is shown seasonally ups and downs by the heat exchange between the atmosphere and the reservoir. On the other hand, dissolved oxygen and water temperature in the Youngsan reservoir have been shown inversed proportional correlation. As the calculation results of residence time and water exchange rate, it is considered that the feature of oxygen distribution is determined by the drainage characteristics caused the shortest residence time during summer, which also disturbed the formation of stratification in the Youngsan reservoir.
Proceedings of the Korean Society of Crop Science Conference
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2022.10a
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pp.14-14
/
2022
Greenhouse gas emissions are one of the critical factors that drive change in rice cropping systems. Within this changing system, less water irrigation and chemical fertilizer are seriously considered, as well combining precision farming technologies with irrigation control. Water and phosphorus (P) fertilizer are two of the most critical inputs in rice cultivation. Due to the lack of water availability in the system, P fertilizer is not available, especially in acidic soil conditions. Moreover, the various types of abiotic stresses, such as drought, high temperature, salinity, submergence, and limited fertilizer result in significant yield loss in the system. Even in the late stage of growth, the waves caused by diseases and insects make the field more unfruitful. Therefore, agronomists and breeders need to identify the secondary phenotypes to estimate the yield loss of when stress appears. The prediction will be clearer if we have a set of markers tagging the causal variation and the associated precise phenotype indices. Although there have been various studies for abiotic stress tolerance, we still lack functional molecular markers and phenotype indices. This is due to the underlying challenges caused by environmental factors in highly unpredictable regional and yearly environmental conditions in the field system. Pupl (phosphorus uptake 1) is still known as the first QTL associated with phosphorus uptake and have been validated in different field crops. Interestingly, some pyramiding lines of Pupl and other QTLs for other stress tolerances showed preferable phenotypes in the yield. Precise physiological studies with the help of genomics are on-going and some results will be discussed.
This study was conducted to investigate the relationships between yearly variations of climatic factors and yearly variations of productivity in Alisma plantago L. In addition, correlation coefficients among yield and yield components were estimated. The data of yield and yield components were collected from the Statistical Year Book of Seungju province, Reserach Report of Seungju Extension Station of Rural Development Administration, and farmers for 10 years from 1983 to 1992. The meteorological data gathered at the Seungju Weather Station for the same period were used to find out the relationships between climatic factors and productivity. Yearly variation of the amount of precipitation in October and the minimum temperature in November were large with coefficients of variation(C.V.) of 106.44, 144.08%, respectively, but the variation of the average temperature, maximum temperature, minimum temperature from July to September were relatively small. Fresh weight and dry weight of roots vary greatly with C. V. of 30.62, 31.85%, respectivly. Plant height and stem length show more or less small C. V. of 5.51, 6. 26%, respectively and leaf width, leaf length, number of stems and root diameter show still less variation. Correlation coefficients between maximum temperature in November and plant height, stem diamter, number of stems, root diamter and dry weight of roots are positively significant at the 5% level. There are high signficant positive correlations observed, between yield and yield components. The maximum temperature would be used as a predictive variable for the estimation of dry weight of roots and number of stems. Simple linear regression equations by the least square method are estimated for number of stems $(Y_1)$ and the maximum temperature in November(X) as $Y_1=4.7114+0.5333\;X\;(R^2=0.4410)$, and for dry weight of roots$(Y_2)$ and the maximum temperature in November(X) as $Y_2=55.0405+14.3233\;X\;(R^2=0.4511)$
In solstices during the solar minimum, the hemispheric difference of the equatorial ionization anomaly (EIA) intensity (hereafter hemispheric asymmetry) is understood as being opposite in the morning and afternoon. This phenomenon is explained by the temporal variation of the combined effects of the fountain process and interhemispheric wind. However, the mechanism applied to the observations during the solar minimum has not yet been validated with observations made during other periods of the solar cycle. We investigate the variability of the hemispheric asymmetry with local time (LT), altitude, season, and solar cycle using the electron density taken by the CHAllenging Minisatellite Payload satellite and the global total electron content (TEC) maps acquired during 2001-2008. The electron density profiles provided by the Constellation Observing System for Meteorology, Ionosphere, and Climate satellites during 2007-2008 are also used to investigate the variation of the hemispheric asymmetry with altitude during the solar minimum. During the solar minimum, the location of a stronger EIA moves from the winter hemisphere to the summer hemisphere around 1200-1400 LT. The reversal of the hemispheric asymmetry is more clearly visible in the F-peak density than in TEC or in topside plasma density. During the solar maximum, the EIA in the winter hemisphere is stronger than that in the summer hemisphere in both the morning and afternoon. When the location of a stronger EIA in the afternoon is viewed as a function of the year, the transition from the winter hemisphere to the summer hemisphere occurs near 2004 (yearly average F10.7 index = 106). We discuss the mechanisms that cause the variation of the hemispheric asymmetry with LT and solar cycle.
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