• Atmosphere
• /
• v.15 no.2
• /
• pp.75-90
• /
• 2005

This study examines the impacts of land cover changes on the East Asia summer monsoon with the National Center for Atmospheric Research Regional Climate Model (NCAR RegCM2), coupled with Biosphere Atmosphere Transfer Scheme (BATS). To assess the goals, two types of land cover maps were used in the simulation of summer climate. One type was NCAR land cover map (CTL) and the other was current land cover map derived from satellite data (land cover: LCV). Warm and cold surface temperature biases of $1-3^{\circ}C$ occurred over central China and Mongolia in CTL. The model produced excessive precipitation over northern land area but less over southern ocean of the model domain. Changes of biophysical parameters, such as albedo, minimum stomatal resistance and roughness length, due to the land cover changes resulted in the alteration of land-atmosphere interactions. Latent heat flux and wind speed in LCV increased noticeably over central China where deciduous broad leaf trees have been replaced by mixed farm and irrigated crop. As a result, the systematic warm biases over central China were greatly reduced in LCV. Strong cooling of central China decreased pressure gradient between East Asian continent and Pacific Ocean. The decreased pressure gradient suppressed the northward transport of moisture from south China and South China Sea. These changes reduced not only the excessive precipitation over north China and Mongolia but also less precipitation over south China. However, the land cover changes increased the precipitation over the Korean Peninsula and the Japan Islands, especially in July and August.

• 한국태양에너지학회:학술대회논문집
• /
• 2008.11a
• /
• pp.202-207
• /
• 2008

Measures for coping with energy shortage are being sought all over the world. Following such a phenomenon, effort to use less energy in the design of buildings and equipment are being conducted. In particular, a program to evaluate the performance of a building comes into the spotlight. However. indispensable standard wether data to estimate the exact energy consumption of a building is currently unprepared. Thus, after appling standard weather data for four weather factors which were used in previous researches to Visual DOE 4.0, we compared it with the result of the existing data and evaluated them. For the monthly cooling and heating load of our target building, we used revised data for June, July, August, and September during which cooling load is applied. When not the existing data but the revised data was used, the research shows that an average of 14.9% increased in June, August, and September except for July. Also, in a case of heating load, the result by the revised data shows a reduction of an average of 11.9% from October to April during which heating load is applied. In particular, the heating loads of all months for which the revised data was used were more low than those of the existing data. In the maximum cooling and heating load according to load factors, the loads by residents and illumination for which the revised data was used were the same as those of the existing data, but the maximum cooling loads used by the two data have a difference in structures such as walls and roofs. Through the above results, the research cannot clearly grasp which weather data influences the cooling and heating load of a building. However, in the maximum loads by the change of weather data in four factors (dry-bulb temperature, web-bulb temperature, cloud amount, and wind speed) among 14 weather factors, the research shows that 5.95% in cooling load and 27.56% in heating load increased, and these results cannot be ignored. In order to make weather data for Performing energy performance evaluation for future buildings, the flow of weather data for the Present and past should be obviously grasped.

• Journal of the Korean earth science society
• /
• v.41 no.5
• /
• pp.447-458
• /
• 2020

This study presents the K-means clustering analysis-based classification of the meteorological patterns affecting the occurrence of high PM₁₀ concentration in the southeastern region of the Korean peninsula for the last five years (2014-2018). Regional differences in Busan, Ulsan, and Gyeongnam related to high PM₁₀ episodes, were clarified through the statistical comparison study using synoptic scale meteorological elements using NCEP (National Centers for Environmental Prediction/FNL (Final Operational Global Analysis) re-analysis meteorological data. Meteorological patterns were classified into a total of five categories (C1-C5). The incidence of each cluster was 24.8% (C1), 21.3% (C2), 20.4% (C3), 17.3% (C4), and 16.2% (C5), respectively. The high PM₁₀ concentration in the southeastern region resulted from long and short range transports (C1, C3, C5) from outside of the region, and the emissions (C2, C4) inside the region. In the high PM₁₀ episodes in Busan, Ulsan, and Gyeongnam regions, meteorological characteristics such as different geopotential height and wind speed at 500 hPa in each cluster and the change in the location of high pressure over Korean Peninsula is strongly associated with the dispersion of PM₁₀ around inventories in the region and the tendency of long-range transportation of PM₁₀ emitted from outside of region.

• Journal of the Korean Institute of Landscape Architecture
• /
• v.33 no.6 s.113
• /
• pp.98-108
• /
• 2006

The climate of urban area is an unstable type with considerable seasonal variation in precipitation wind speed, and temperature and it grows worse. Besides, ozone is a serious air pollutant in most of large cities. So worldwide, some of large cities are investing in forestry options to offset their climate problems, but lack of information has hindered comparisons of urban un cost effectiveness to other options. This research intends to study the economic benefits of tree shading of 19 parking lots in UCD campus. The economic benefits of tree shading are air conditioning savings, air quality, stormwater run-off, and other benefits. Especially, this study focuses how much the economic benefit of parking lot shading has been increased from 1995 to 2003 year by aerophoto. Some data on dimensions of parking lots and the number, size, tree species, and location of trees around each parking lot was inventoried. Two aerophotos(1995,2003) were used in order to analyze the increasement of tree canopy in 19 parking lots for 8 years. However, increasing coverage of trees and managing them for healthy growth would not be sufficient for avoiding adverse impacts by future climate change. Additional measures should be followed such as an increase of energy use efficiency and development of substitute energy. For example, coverage of trees help to save cooling energy by blocking solar radiation reaching parking cars and building structures through shading, and creating cool micro-climates through evapotranspiration. They also reduce heating demand by decreasing air infiltration and heat conduction out of the interior of buildings. Proper arrangement of vegetation over the parking lots can reduce cooling and heating costs. So proper planting design around hard space paving including species selection and location can significantly save cooling and heating energy. And a reduction in car and building's heating and cooling costs results in the reduction in energy demand which causes to emissions of air pollutants. Total increased tree canopy from 1995 to 2003 is $8,470.45m^2$ and the economic benefits is US$ 5,282.10. The economic benefit of one tree has been US$ 7.21 for 8 years. And an annually increased benefit is US$ 0.9 per a tree. If this kind of study is applied to studying the economic benefits of tree canopy in parking lots of Korea, it could result in guidelines of tree planting of parking lots. Because the trees selected for planting in parking lots were not suitable for an environment, the guidelines should contain a recommended list of trees. The guidelines should propose the shading percentage of parking lot when we plan a parking lot and contain the maintenance of trees in order to maximize the economic benefits of tree canopy.

• Journal of Korean Society of Coastal and Ocean Engineers
• /
• v.22 no.5
• /
• pp.295-305
• /
• 2010

Although the rubble mound breakwaters in Korea have been damaged by typhoons almost every year, quantification of erosion of armor block have seldomly been made. In this paper, the damage of armor units is standardized by the relative damage. In the case where the number of damaged units is reported, it is divided by the total number of units to calculate the relative damage. In the case where the rehabilitation cost is reported, the relative damage is calculated by using its relationship with the present value of the past rehabilitation cost. The relative damage is shown to have strong correlations with the typhoon parameters such as nearest central air pressure and maximum wind speed at each site. On the other hand, the existing numerical methods for calculating the cumulative damage are compared with hydraulic model tests. The method of Melby and Kobayashi (1998) is shown to give a reasonable result, and it is used to calculate the relative damage, which is compared with the measured damage. A good agreement is shown for the East Breakwater of Yeosu Harbor, while poor agreement is shown for other breakwaters. The poor agreement may be because waves of larger height than the design height occurred due to strong typhoons associated with climate change so that the relative damage increased during the last several decades.

• Journal of Animal Environmental Science
• /
• v.13 no.3
• /
• pp.187-194
• /
• 2007

Six pig farms were surveyed to measure the odor concentrations and characteristics of ammonia and sulfide corollary compounds in piggery. They were depended on the scale of piggery, weather conditions such as temperature, humidity, wind speed and direction, scales and types of pig breeding, and manure treatment methods. The highest ammonia concentrations in piggery were measured during the winter, since the tight sealed insulation in piggery made less amount of generated ammonia discharged from piggery. The objective of this study was to measure concentrations of odor in the piggery by season and growing, and to measure concentrations of odor at boundary area. So, we investigated the raising managements, manure managements, and methods of reducing odor according to farm scale. We found that concentration of ammonia gas in the swine fattening piggery in winter was the highest. This result is consistent with the lower ventilation rate to maintain Indoor temperature. In this result, there was no connection between farm scale and ventilating system. Concentration of ammonia gas was 1.64 ppm at one boundary area in the middle scale. $H_2S$, $CH_3SH$, $(CH_3)_2S$, and $(CH_3)_2S_2$ were below the standard of protection odor policy.

• Journal of the Korean Association of Geographic Information Studies
• /
• v.18 no.1
• /
• pp.90-104
• /
• 2015

The purpose of this paper is to build a spatio-temporal evapotranspiration(ET) estimation model using Terra MODIS satellite image and by calibrating with the flux tower ET data from watershed. The fundamentals of spatial ET model, Surface Energy Balance Algorithm for Land(SEBAL) was adopted and modified to estimate the daily ET of Yongdam Dam watershed in South Korea. The daily Normalized Distribution Vegetation Index(NDVI), Albedo, and Land Surface Temperature(LST) from MODIS and the ground measured wind speed and solar radiation data were prepared for 2 years(2012-2013). The SEBAL was calibrated with the forest ET measured by Deokyusan flux tower in the study watershed. Among the model parameters, the important parameters were surface albedo, NDVI and surface roughness in order for momentum transport during calculation of sensible heat flux. As a result of the final calibration, the monthly averaged albedo and NDVI were used because the daily values showed big deviation with unrealistic change. The determination coefficient($R^2$) between SEBAL and flux data was 0.45. The spatial ET reflected the geographical characteristics showing the ET of lowland areas was higher than the highland ET.

• Korean Journal of Agricultural and Forest Meteorology
• /
• v.24 no.4
• /
• pp.346-352
• /
• 2022

Mountain meteorology in South Korea that is covered mountains with complex terrain is important for understanding and managing the forest disaster and forest ecosystems. In particular, recent changes in dryness and/or rainfall intensity due to climate change may cause an increase in the possibility of forest disasters. Therefore, accurate monitoring of mountain meteorology is needed for efficient forest management. Korea Forest Service (KFS) is establishing the Automatic Mountain Meteorology Observation Stations (AMOS) in the mountain regions since 2012. 464 AMOSs are observing various meteorological variables such as air temperature, relative humidity, wind speed and direction, precipitation, soil temperature, and air pressure for every minute, which is conducted the quality control (QC) to retain data reliability. QC process includes the physical limit test, step test, internal consistency test, persistence test, climate range test, and median filter test. All of AMOS observations are open to use, which can be found from the Korean Mountain Meteorology Information System (KoMIS, http://mtweather.nifos.go.kr/) of the National Institute of Forest Science and the Public Data Portal (https://public.go.kr/). AMOS observations with guaranteed quality can be used in various forest fields including the public safety, forest recreation, forest leisure activities, etc., and can contribute to the advancement of forest science and technology. In this paper, a series of processes are introduced to collect and use the AMOS dataset in the mountain region in South Korea.

• Journal of Korea Water Resources Association
• /
• v.55 no.12
• /
• pp.1077-1089
• /
• 2022

With the construction of Seoul National University (SNU), the Mt. Gwanak watershed has undergone some urbanization. As with other campus catchments, data related to the water cycle is extremely limited. Therefore, this study began by collecting hydrological and meteorological data using Atmos-41, a complex meteorological observation instrument. The observation results of Atmos-41 were validated by analyzing the statistical characteristics and confidence intervals based on the monthly variability of data from the Korea Meteorological Administration. Results of the previous research were used to validate the simulated surface runoff and infiltration using the Storm Water Management Model (SWMM). The potential evapotranspiration (PET) simulated by the SWMM was rectified by comparing it to the Atmos-41 observation data. Multiple regression analysis was employed to adjust for the fluctuations in precipitation, relative humidity, and wind speed because the calculated SWMM PET tends to be underestimated during periods of low temperatures. R² increased from 0.54 to 0.80 when compared to the Atmos-41 PET. The rate of change in the water cycle as a consequence of the SNU's construction resulted in a 15.7% increase in surface runoff, a 14.2% decrease in infiltration rate, and a 1.6% decrease in evaporation.

• Korean Journal of Agricultural and Forest Meteorology
• /
• v.20 no.4
• /
• pp.348-356
• /
• 2018

Most of fires were human-caused fires in Korea, but meteorological factors are also big contributors to fire behavior and its spread. Thus, meteorological factors as well as topographical and forest factors were considered in the fire danger rating systems. This study aims to develop an advanced national integrated daily weather index(DWI) using weather data in the spring and fall to support forest fire prevention strategy in South Korea. DWI represents the meteorological characteristics, such as humidity (relative and effective), temperature and wind speed, and we integrated nine logistic regression models of the past into one national model. One national integrated model of the spring and fall is respectively $[1+{\exp}\{-(2.706+(0.088^*T_{mean})-(0.055^*Rh)-(0.023^*Eh)-(0.014^*W_{mean}))\}^{-1}]^{-1}$, $[1+{\exp}\{-(1.099+(0.117^*T_{mean})-(0.069^*Rh)-(0.182^*W_{mean}))\}^{-1}]^{-1}$ and all weather variables significantly (p<0.01) affected the probability of forest fire occurrence in the overall regions. The accuracy of the model in the spring and fall is respectively 71.7% and 86.9%. One integrated national model showed 10% higher accuracy than nine logistic regression models when it is applied weather data with 66 random sampling in forest fire event days. These findings would be necessary for the policy makers in the Republic of Korea for the prevention of forest fires.