This study aims to understand the characteristics of spatial distribution of snowfall and to analyze its development mechanism in Honam province in Korea. The areas of snowfall in Honan area can be divided into the seven sub-area by snowfall pattern. In the west coastal area of heavy snowfall and the southwest coastal area of heavy snowfall, snowfall develops over reason of ocean by Siberian High while in the northern inland area of heavy snowfall and the southern inland area of heavy snowfall, it develops when a strong Siberian High affects to inland. Then, much snowfall is by a forced ascending due to topography in Namwon, Imsil and Gwangju of the northwestward of the Noryung and Sobaek mountain ranges while it is weak in Jeonju and Suncheon of the low plains and the southeastward. In the mountainous area of heavy snowfall and the south coastal area of light snowfall, cyclone is also one of causes of snowfall. In the southwest coastal area, snowfall is meager than the southwest coastal area of heavy snowfall because this area is far from the west coast. It is confirmed that the snowfall difference of the coast, inland and mountainous area appears by temperature difference of sea surface and 850hPa temperature, wind speed of Siberian High.
A statistical downscaling method was adopted in order to establish the high-resolution wave prediction system in the East Sea coastal area. This system used forecast data from the Global Wave Watch (GWW) model, and the East Sea and Busan Coastal Wave Watch (CWW) model operated by the Korea Meteorological Administration (KMA). We used the CWW forecast data until three days and the GWW forecast data from three to seven days to implement the statistical downscaling method (inverse distance weight interpolation and conditional merge). The two-dimensional and station wave heights as well as sea surface wind speed from the high-resolution coastal prediction system were verified with statistical analysis, using an initial analysis field and oceanic observation with buoys carried out by the KMA and the Korea Hydrographic and Oceanographic Agency (KHOA). Similar to the predictive performance of the GWW and the CWW data, the system has a high predictive performance at the initial stages that decreased gradually with forecast time. As a result, during the entire prediction period, the correlation coefficient and root mean square error of the predicted wave heights improved from 0.46 and 0.34 m to 0.6 and 0.28 m before and after applying the statistical downscaling method.
Korean Journal of Agricultural and Forest Meteorology
/
v.23
no.3
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pp.141-148
/
2021
Agrivoltaic systems, also called solar sharing, stated from an idea that utilizes sunlight above the light saturation point of crops for power generation using solar panels. It is expected that agrivoltaic systems can realize climate smart agriculture by reducing evapotranspiration and methane emission due to the reduction of incident solar radiation and the consequent surface cooling effect and bring additional income to farms through solar power generation. In this study, to evaluate that agrivoltaic systems are suitable for realization of climate smart agriculture, we conducted agro-environmental observations (i.e., downward/upward shortwave/longwave radiations, air temperature, relative humidity, water temperature, soil temperature, and wind speed) in a rice paddy under an agrivoltaic system and compared with the environment outside the system using automated meteorological observing systems (AMOS). During the observation period, the spatially averaged incoming solar radiation under the agrivoltaic system was about 70% of that in the open paddy field, and clear differences in the soil and water temperatures between the paddy field under the agrivoltaic system and the open paddy field were confirmed, although the air temperatures were similar. It is required in the near future to confirm whether such environmental differences lead to a reduction in water consumption and greenhouse gas emissions by flux measurements.
Kim, Do-Hyun;Kim, Jin-Uk;Kim, Tae-Jun;Byon, Jae-Young;Kim, Jin-Won;Kwon, Sang-Hoon;Kim, Yeon-Hee
Atmosphere
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v.30
no.4
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pp.377-390
/
2020
Not only emissions, but also atmospheric circulation is a key factor that affects local particulate matters (PM) concentrations in Korea through ventilation effects and transboundary transports. As part of the atmospheric circulation, air stagnation especially adversely affects local air quality due to weak ventilation. This study investigates the large-scale circulation related to air stagnation over Korea during winter and projects the climate change impacts on atmospheric patterns, using observed PM data, reanalysis and regional climate projections from HadGEM3-RA with Modified Korea Particulate matter Index. Results show that the stagnation affects the PM concentration, accompanied by pressure ridge at upper troposphere and weaken zonal pressure gradient at lower troposphere. Downscaling using HadGEM3-RA is found to yield Added-Value in the simulated low tropospheric winds. For projection of future stagnation, SSP5-8.5 and SSP1-2.6 (high and low emission) scenarios are used here. It has been found that the stagnation condition occurs more frequently by 11% under SSP5-8.5 and by 5% under SSP1-2.6 than in present-day climate and is most affected by changes in surface wind speed. The increase in the stagnation conditions is related to anticyclonic circulation anomaly at upper troposphere and weaken meridional pressure gradient at lower troposphere. Considering that the present East Asian winter monsoon is mainly affected by change in zonal pressure gradient, it is worth paying attention to this change in the meridional gradient. Our results suggest that future warming condition increase the frequency of air stagnation over Korea during winter with response of atmospheric circulation and its nonlinearity.
This study examined the influence of near-surface atmospheric warming in the Arctic-East Asia region during spring (March-May) from 1991 to 2020 on the synoptic-scale meteorology of dust storm-induced dust days in Seoul, Korea, in response to the Arctic Oscillation. Increased springtime warming in the Arctic-East Asia region correlated with a reduction of six days in the occurrence of dust storm-induced dust days in Seoul, Korea, along with a decline in the intensity of these days by -1.6 ㎍ m-3yr-1 in PM10 mass concentration. The declining number of dust storm-induced dust days in Korea during the 2010s was the result of synoptic-scale meteorological analysis, which showed increased high-pressure activity as indicated by the negative potential vorticity unit. Moreover, a distinct pattern emerged in the distribution of dust storm-induced dust days in Korea based on the Arctic Oscillation Index (AOI), showing an increase in negative AOI and a decrease in positive AOI. Although the northward shift of the polar jet weakened the southerly low-pressure system activity over Mongolia and northern China, a reinforced high-pressure system formed over the Chinese continent during dust-storm-induced dust days with a negative AOI. This resulted in both a decrease in the frequency of dust-storm-induced dust days and reduction in wind speeds, facilitating their transport from source regions to Korea. Conversely, on days with positive AOIs, an extensive warm and stagnant high-pressure system dominated mainland China, accompanied by further cooling of the northern segment of the polar jet. A notable decline in wind speed in the lower troposphere across the Mongolia-northern China-Korea region diminished the occurrence of dust storm-induced dust days and also weakened their long-range transport.
The empirical/statistical models to estimate the ground Particulate Matter ($PM_{2.5}$) concentration from Geostationary Ocean Color Imager (GOCI) Aerosol Optical Depth (AOD) product were developed and analyzed for the period of 2015 in Seoul, South Korea. In the model construction of AOD-$PM_{2.5}$, two vertical correction methods using the planetary boundary layer height and the vertical ratio of aerosol, and humidity correction method using the hygroscopic growth factor were applied to respective models. The vertical correction for AOD and humidity correction for $PM_{2.5}$ concentration played an important role in improving accuracy of overall estimation. The multiple linear regression (MLR) models with additional meteorological factors (wind speed, visibility, and air temperature) affecting AOD and $PM_{2.5}$ relationships were constructed for the whole year and each season. As a result, determination coefficients of MLR models were significantly increased, compared to those of empirical models. In this study, we analyzed the seasonal, monthly and diurnal characteristics of AOD-$PM_{2.5}$model. when the MLR model is seasonally constructed, underestimation tendency in high $PM_{2.5}$ cases for the whole year were improved. The monthly and diurnal patterns of observed $PM_{2.5}$ and estimated $PM_{2.5}$ were similar. The results of this study, which estimates surface $PM_{2.5}$ concentration using geostationary satellite AOD, are expected to be applicable to the future GK-2A and GK-2B.
Kim, Jaemin;Lee, Yun Gon;Park, Jun Dong;Sohn, Eun Ha;Jang, Jae-Dong
Korean Journal of Remote Sensing
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v.34
no.3
/
pp.519-533
/
2018
The sensible heat flux (SHF)and latent heat flux (LHF) over Korean Peninsula ocean during recent 4 years were calculated using Coupled Ocean-Atmosphere Response Experiment (COARE) 3.5 bulk algorithm and satellite-based atmospheric-ocean variables. Among the four input variables (10-m wind speed; U, sea surface temperature; $T_s$, air temperature; $T_a$, and air humidity; $Q_a$) required for heat flux calculation, Ta and $Q_a$, which are not observed directly by satellites, were estimated from empirical relations developed using satellite-based columnar atmospheric water vapor (W) and $T_s$. The estimated satellite-based $T_a$ and $Q_a$ show high correlation coefficients above 0.96 with the buoy observations. The temporal and spatial variability of monthly ocean heat fluxes were analyzed for the Korean Peninsula ocean. The SHF showed low values of $20W/m^2$ over the entire areas from March to August. Particularly, in July, SHF from the atmosphere to the ocean, which is less than $0W/m^2$, has been shown in some areas. The SHF gradually increased from September and reached the maximum value in December. Similarly, The LHF showed low values of $40W/m^2$ from April to July, but it increased rapidly from autumn and was highest in December. The analysis of monthly characteristics of the meteorological variables affecting the heat fluxes revealed that the variation in differences of temperature and humidity between air and sea modulate the SHF and LHF, respectively. In addition, as the sensitivity of SHF and LHF to U increase in winter, it contributed to the highest values of ocean heat fluxes in this season.
The natural change of winter night temperature from 00:00 to 04:30 O'clock with the different height of thermal screen in a venlo type glasshouse (W59×L68×H5.9 m) was studied using computational fluid dynamics (CFD). At the early stage of CFD analysis, the room temperature decrease of glasshouse with the 5.9 m height of thermal screen were faster than it with the 4.1m height of thermal screen, but at 2 hr after analysis it was slower than in it with the 4,1m, the temperature difference was 0.6℃ after 4 hr. If we consider that turn on the heater when the temperature were decrease below 13℃ at 1hr after CFD analysis, it is good for energy saving in the glasshouse with the 4.1 m height of thermal screen rather than in it with the 5.9 m height, because of the temperature decrease were slow during 2 hrs after analysis. The airflow at the height of 2 m which were grown tomato were fast and wide in the glasshouse with the 5.9 m height thermal screen rather than in it with the 4.1 m, the speed difference was 0.034m·s-1 at 1hr after CFD analysis. The effect of temperature decrease in summer season were compared with the different height of shading screen from 12:00 to 14:30 O'clock. The height of shading screen were 5.7, 3.9 m, the gap of it were 30%. The air-inflow quantity by the fan with duct at lower part of venlo glasshouse was 0.67 ㎥·s-1 until 1hr and to increase 3 times of it from 1hr after analysis. The roof window were open 100%. Until 1hr of CFD analysis, the temperature in the 30% open of shading screen was 0.9℃ higher than in the none shading screen. From 13:00 O'clock when the air-inlet quantity to increase 3 times, the temperature in case 30% gap of shading screen were decreased compare with the none shading screen, the temperature difference was 0.5℃ at 14:30 O'clock. The temperature on the floor surface in case 30% gap of shading screen were lower with it's height increase, the temperature difference was 8℃ compare with none shading screen. The relative humidity difference were insignificant by the height and gap of shading screen.
Journal of the Korean Society for Marine Environment & Energy
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v.16
no.3
/
pp.202-210
/
2013
As incomes increase, interest in ocean leisure picks up. As a result, a lot of research and developments on hull form design and production of planing boats, mostly used for ocean leisure, are needed. Analysis in researches on resistance of planing boats shows that resistance characteristic of planing boats is different from resistance characteristic of general boats because the former is fast, and its wetted surface is very small. Using Savitsky formula widely used in the calculation of effective horse power in shipbuildingyards, and propulsion system and engine manufacturers, this study calculated total resistance of a research planing boat. Then it analyzed the flow characteristics of the planing boat through theoretical analysis and wind tunnel experiment, and computed air resistance and lift force by changes of speed and trim angle. It also compared and analyzed result of theoretical analysis and experiment of the ratio of air resistance to total resistance under variations of velocity and trim angle. When the study is used to estimate more accurate effective horse power, it is expected to remedy abuses of unnecessarily installing high-powered engine. As nature disasters due to abnormal changes of weather increase, interest in greenhouse gas grows. International Maritime Organization (IMO) legislated Energy Efficiency Design Index (EEDI) and Energy Efficiency Operational Indicator (EEOI) to reduce ship greenhouse gas emissions. But this index will be applied to over 400 tons ships, small ships, emitting more greenhouse gases than larege ships per unit power, will dodge the regulations. Thus, this study indicated a problem by calculating greenhouse gas emissions of an ocean leisure planning boat (a small ship), and suggested the need for EEDI of small ships.
The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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v.16
no.1
/
pp.1-13
/
2011
The Yellow Sea Cold Water (YSCW) is formed by cold and dry wind in the previous winter, and is known to spread southward along the central trough of the Yellow Sea in summer. Water characteristics of the YSCW and its movement in the northern East China Sea (ECS) are investigated by analyzing CTD (conductivity-Temperature-Depth) data collected from summertime hydrographic surveys between 2003 and 2009. By water mass analysis, we newly define the North Western Cold Water (NWCW) as a cold water mass observed in the study area. It is characterized by temperature below $13.2^{\circ}C$, salinity of 32.6~33.7 psu, and density (${\sigma}_t$) of 24.7~25.5. The NWCW appears to flow southward at about a speed less than 2 cm/s according to the geostrophic calculation. The newly defined NWCW shows an interannual variation in the range of temperature and occupied area, which is in close relation with the sea surface temperature (SST) over the Yellow Sea and the East China Sea in the previous winter season. The winter SST is determined by winter air temperature, which shows a high correlation with the winter-mean Arctic Oscillation (AO) index. The negative winter-mean AO causes the low winter SST over the Yellow Sea and the East China Sea, resulting in the summertime expansion and lower temperature of the NWCW in the study area. This study shows a dynamic relation among the winter-mean AO index, SST, and NWCW, which helps to predict the movement of NWCW in the northern ECS in summer.
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