• Title/Summary/Keyword: 기온

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Impacts of Three-dimensional Land Cover on Urban Air Temperatures (도시기온에 작용하는 입체적 토지피복의 영향)

  • Jo, Hyun-Kil;Ahn, Tae-Won
    • Journal of the Korean Institute of Landscape Architecture
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    • v.37 no.3
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    • pp.54-60
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    • 2009
  • The purpose of this study is to analyze the impacts of three-dimensional land cover on changing urban air temperatures and to explore some strategies of urban landscaping towards mitigation of heat build-up. This study located study spaces within a diameter of 300m around 24 Automatic Weather Stations(AWS) in Seoul, and collected data of diverse variables which could affect summer energy budgets and air temperatures. The study also selected reflecting study objectives 6 smaller-scale spaces with a diameter of 30m in Chuncheon, and measured summer air temperatures and three-dimensional land cover to compare their relationships with results from Seoul's AWS. Linear regression models derived from data of Seoul's AWS revealed that vegetation volume, greenspace area, building volume, building area, population density, and pavement area contributed to a statistically significant change in summer air temperatures. Of these variables, vegetation and building volume indicated the highest accountability for total variability of changes in the air temperatures. Multiple regression models derived from combinations of the significant variables also showed that both vegetation and building volume generated a model with the best fitness. Based on this multiple regression model, a 10% increase of vegetation volume decreased the air temperatures by approximately 0.14%, while a 10% increase of building volume raised them by 0.26%. Relationships between Chuncheon's summer air temperatures and land cover distribution for the smaller-scale spaces also disclosed that the air temperatures were negatively correlated to vegetation volume and greenspace area, while they were positively correlated to hardscape area. Similarly to the case of Seoul's AWS, the air temperatures for the smaller-scale spaces decreased by 0.32% ($0.08^{\circ}C$) as vegetation volume increased by 10%, based on the most appropriate linear model. Thus, urban landscaping for the reduction of summer air temperatures requires strategies to improve vegetation volume and simultaneously to decrease building volume. For Seoul's AWS, the impact of building volume on changing the air temperatures was about 2 times greater than that of vegetation volume. Wall and rooftop greening for shading and evapotranspiration is suggested to control atmospheric heating by three-dimensional building surfaces, enlarging vegetation volume through multilayered plantings on soil surfaces.

Water Temperature Variation of a Stream Entering Soyang Reservoir (소양호 유입지천의 수온변화)

  • Yi, Yong-Kon;Kang, Min-Gu;Lee, Hyun-Seok;Kim, Jin-Young
    • Proceedings of the Korea Water Resources Association Conference
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    • 2006.05a
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    • pp.1063-1067
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    • 2006
  • 소양호의 유입지천 중의 하나인 인북천의 원통수위관측소에 현장용 수온계를 설치하여 수온변화를 분석하고 수온 추정을 위하여 다중회귀분석을 수행하였다. 인북천 원통수위유량관측소지점의 유량이 작은 경우, 수온은 기온의 최고점부근에서 변화하고, 이슬점은 기온의 최저점부근에서 변화하는 것으로 나타났으며, 일일 주기로 변화하는 양상을 보이고, 일교차는 각각 약 $5^{\circ}C,\;15^{\circ}C$$5^{\circ}C$정도로 나타났다. 최대수온과 최대기온은 차이가 거의 없지만 최저수온은 최저기온보다 약 $10^{\circ}C$정도 높은 것으로 나타났다. 인북천 원통수위유량관측소 지점의 유량이 증가하는 경우에는 수온과 기온이 급감하는 것으로 나타났다. 수온추정시 유량이 작은 구간과 큰 경우구간에 대하여 각각 다중회귀분석을 수행하는 것이 추정오차를 낮추는 것으로 나타났다.

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Analyzing Spatio-temporal Variability of Temperature and Precipitation in Seoul (서울시 기온 및 강수량의 시공간변이성 분석)

  • Choi, Hyun-Ah;Song, Chul-Chul;Lee, Woo-Kyun;Kwak, Han-Bin
    • Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
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    • 2008.06a
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    • pp.455-460
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    • 2008
  • 본 연구에서는 1997년 1월부터 2006년 12월까지의 기상청에서 제공하는 31개 자동기상관측망(AWS: Automatic Weather Stations)에 의한 지표 근처 기온($^{\circ}C$) 및 강수(mm) 자료를 이용하여 서울 지역 기상인자의 시 공간 구조 분석 및 변화경향과 변이성을 도출하였다. 미관측지점의 값을 추정하기 위하여 주변 관측지점들을 고려하여, 그 영향은 거리에 반비례함을 반영하는 공간통계학적 방법 중 IDSW(Inverse Distance Squared Weighing:거리자승역산가중)를 적용하여 보관하였다. 그 결과 서울시의 기온과 강수량 모두 1997년에 비해 2006년의 기온이 약 $1.03^{\circ}C$, 강수량이 약 483mm 증가한 것으로 나타났다. 기후변이성의 특성은 과거 10년 동안 기온의 경우 산림지역에서는 변화의 폭이 높게 나타났으며, 시간이 지나면서 감소하는 경향을 보였다. 주거 지역의 경우 변화이 폭이 낮게 나타났으며, 시간이 지나면서 증가하는 경향을 보였다. 그러나 강수량의 경우 산림지역과 주거지역의 변이성의 차이가 나타나지 않았다.

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Snowmelt Effect in Hancheon watershed, Jeju Island (제주 한천유역에 대한 시공간적인 융설 영향 평가)

  • Lee, Jeong Eun;Kim, Nam Won
    • Proceedings of the Korea Water Resources Association Conference
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    • 2015.05a
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    • pp.468-468
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    • 2015
  • 일반적으로 겨울철 강수는 기온에 따라 강우와 강설로 분류된다. 특히 기온이 임계온도보다 낮을 경우, 강수는 강설의 형태로 지표면에 도달하여 적설되어진다. 겨울철 산간에 적설된 눈은 봄철이 되어 기온이 상승함에 따라 융설(snowmelt)이 발생하여 유역의 유출에 기여한다. 이러한 융설은 기온이 영하로 내려가는 11-4월에 해당하는 갈수기에 유출량 등의 수문성분에 영향을 미치고 있다. 특히 제주유역의 경우, 고도에 따른 강수량, 기온의 차이가 매우 크므로 강설, 융설 현상의 시공간적인 발생에 대한 연구가 더욱 요구된다. 따라서, 본 연구에서는 제주유역의 강설, 융설 발생의 시공간적인 평가를 위해서 융설모의가 가능한 SWAT-K를 한천유역에 적용하여, 그 결과를 분석하였다. 융설모의 이론을 검토하고, 실제 대상유역에 융설을 고려하기 위한 매개변수를 설정하고, 월별, 소유역별로 강설, 융설 발생현황을 평가하였다.

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An Analysis on the Electricity Demand for Air Conditioning with Non-Linear Models (비선형모형을 이용한 냉방전력 수요행태 분석)

  • Kim, Jongseon
    • Environmental and Resource Economics Review
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    • v.16 no.4
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    • pp.901-922
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    • 2007
  • To see how the electricity demand for air-conditioning responds to weather condition and what kind of weather condition works better in forecasting maximum daily electricity demand, four different regression models, which are linear, exponential, power and S-curve, are adopted. The regression outcome turns out that the electricity demand for air-conditioning is inclined to rely on the exponential model. Another major discovery of this study is that the electricity demand for air-conditioning responds more sensitively to the weather condition year after year along with the higher non-air-conditioning electricity demand. In addition, it has also been found that the discomfort index explains the electricity demand for air-conditioning better than the highest temperature.

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An Application of Satellite Image Analysis to Visualize the Effects of Urban Green Areas on Temperature (위성영상을 이용한 도시녹지의 기온저감 효과 분석)

  • Yoon, Min-Ho;Ahn, Tong-Mahn
    • Journal of the Korean Institute of Landscape Architecture
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    • v.37 no.3
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    • pp.46-53
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    • 2009
  • Urbanization brings several changes to the natural environment. Its consequences can have a direct effect on climatic features, as in the Urban Heat Island Effect. One factor that directly affects the urban climate is the green area. In urban areas, vegetation is suppressed in order to accommodate manmade buildings and streets. In this paper we analyze the effect of green areas on the urban temperature in Seoul. The period selected for analysis was July 30th, 2007. The ground temperature was measured using Landsat TM satellite imagery. Land cover was calculated in terms of city area, water, bare soil, wet lands, grass lands, forest, and farmland. We extracted the surface temperature using the Linear Regression Model. Then, we did a regression analysis between air temperature at the Automatic Weather Station and surface temperature. Finally, we calculated the temperature decrease area and the population benefits from the green areas. Consequently, we determined that a green area with a radius of 500m will have a temperature reduction area of $67.33km^2$, in terms of urban area. This is 11.12% of Seoul's metropolitan area and 18.09% of the Seoul urban area. We can assume that about 1,892,000 people would be affected by this green area's temperature reduction. Also, we randomly chose 50 places to analysis a cross section of temperature reduction area. Temperature differences between the boundaries of green and urban areas are an average of $0.78^{\circ}C$. The highest temperature difference is $1.7^{\circ}C$, and the lowest temperature difference is $0.3^{\circ}C$. This study has demonstrated that we can understand how green areas truly affect air temperature.

Using Synoptic Data to Predict Air Temperature within Rice Canopies across Geographic Areas (종관자료를 이용한 벼 재배지대별 군락 내 기온 예측)

  • 윤영관;윤진일
    • Korean Journal of Agricultural and Forest Meteorology
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    • v.3 no.4
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    • pp.199-205
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    • 2001
  • This study was conducted to figure out temperature profiles of a partially developed paddy rice canopy, which are necessary to run plant disease forecasting models. Air temperature over and within the developing rice canopy was monitored from one month after transplanting (June 29) to just before heading (August 24) in 1999 and 2001. During the study period, the temporal march of the within-canopy profile was analyzed and an empirical formula was developed for simulating the profile. A partially developed rice canopy temperature seemed to be controlled mainly by the ambient temperature above the canopy and the water temperature beneath the canopy, and to some extent by the solar altitude, resulting in alternating isothermal and inversion structures. On sunny days, air temperature at the height of maximum leafages was increased at the same rate as the ambient temperature above the canopy after sunrise. Below the height, the temperature increase was delayed until the solar noon. Air temperature near the water surface varied much less than those of the outer- and the upper-canopy, which kept increasing by the time of daily maximum temperature observed at the nearby synoptic station. After sunset, cooling rate is much less at the lower canopy, resulting in an isothermal profile at around the midnight. A fairly consistent drop in temperature at rice paddies compared with the nearby synoptic weather stations across geographic areas and time of day was found. According to this result, a cooling by 0.6 to 1.2$^{\circ}C$ is expected over paddy rice fields compared with the officially reported temperature during the summer months. An empirical equation for simulating the temperature profile was formulated from the field observations. Given the temperature estimates at 150 cm above the canopy and the maximum deviation at the lowest layer, air temperature at any height within the canopy can be predicted by this equation. As an application, temperature surfaces at several heights within rice fields were produced over the southwestern plains in Korea at a 1 km by 1km grid spacing, where rice paddies were identified by a satellite image analysis. The outer canopy temperature was prepared by a lapse rate corrected spatial interpolation of the synoptic temperature observations combined with the hourly cooling rate over the rice paddies.

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Distribution of Evergreen Broad-leaved Plants and Climatic Factors (한반도 상록활엽수의 지리적 분포와 기후요소)

  • 구경아;공우석;김종규
    • Journal of the Korean Geographical Society
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    • v.36 no.3
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    • pp.247-257
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    • 2001
  • The relationships between the distribution of 132 species, 61 genera evergreen broad-leaved trees and shrubs(EBTS) and climatic factors have discussed. The distributional patterns of EBTS were categorized into seven groups on the basis of the number of distributing sites, distributional attitudes and latitudes. Out of seven group. the cold-tolerant EBTS were common at groups I and II, along tilth Empetrum nigrum var. japonicum. Diapensia lapponics subsp. obovata of group III. However, the warmth-tolerant EBTS were rich at groups III. IV V, and VI The lower distributional limits of cold-tolerant EBTS in the groups I and UU decreased as one moves toward south. The upper distributional limit of warmth-tolerant EBTS in the groups III, IV and V decreased with increasing latitude. However. no clear distributional tendency is noticed in the groups VI and VII. The range of warmth-tolerant EBTS appear to show close relationship with the January mean temperature -4 $\^{C}$ and January mean minimum temperature -9$\^{C}$ than others. On the other hand, that of the cold-tolerant EBTS seem to respond well to the August mean temperature 19$\^{C}$ and August mean maximum temperature 26$\^{C}$ than others.

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Error Analysis of the Local Water Temperature Estimated by the Global Air Temperature Data (광역 기온자료를 이용한 국지 수온 추정오차 비교 분석)

  • Lee, Khil-Ha;Cho, Hong-Yeon
    • Journal of Korea Water Resources Association
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    • v.44 no.4
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    • pp.275-283
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    • 2011
  • A local or site-specific water temperature is downscaled from the nation-wide air temperature that represents simulation by General Circulation Model (GCM). Both two-step and one-step method are tested and compared in three sites: Masan Bay, Lake Sihwa, and Nakdong River Estuary. Two-step method uses a linear regression model as the first step that converts nation-wide air temperature into local air temperature, and the corresponding coefficient of determination is in the range of 0.98~0.99. The second step that converts air temperature into water temperature uses a nonlinear curve, so called S-curve, and the corresponding root mean squared error (RMSE) is 2.07 for rising limb in Masan Bay, 1.93 for falling limb in Masan Bay, 2.59 for Lake Sihwa, and 1.58 for Nakdong River Estuary. In a similar way, one-step method is performed to directly convert nation-wade air temperature into local water temperature, and the corresponding RMSE is 2.28 for rising limb in Masan Bay, 1.89 for falling limb in Masan Bay, 2.55 for Lake Sihwa, and 1.52 for Nakdong River Estuary. Consequently both methods show a similar level of performance, and one-step method is recommendable in that it is simple and practical in relative terms.

Investigation and Greenhouse Heat Loss based on Areas and Weather Information (온실 열손실 분석용 기상정보 및 온실방위 조사 분석)

  • Kim, Young Hwa;Kang, Sukwon;Paek, Yee;Jang, Jae Kyung;Sung, Je Hoon;Kang, Yeon Koo
    • Journal of Bio-Environment Control
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    • v.27 no.1
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    • pp.64-70
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    • 2018
  • In this study, eleven major coastal areas were selected and the climate environment and the greenhouse direction were analyzed. This research investigates the greenhouse heat loss according to the wind environment at target areas. The target areas were selected based on heated greenhouse cultivation area and wind environment standard. Temperature, wind speed, and wind direction among weather data for 30 years were collected and analyzed. The data were divided into the minimum, average, and maximum temperatures and the Meteorological Agency criteria applied to the weather and wind direction criteria. Data were collected in the range of $0{\sim}180^{\circ}$ considering the symmetry of the shape of the greenhouse. In addition, the wind direction is different for each region and the applied wind direction can be different when referring to the longitudinal direction of the greenhouse and the data are collected in the range of $0{\sim}90^{\circ}$. The results of this study are expected to be used to calculate the heating load of greenhouse installed in places wind speed high.