• Korean Journal of Soil Science and Fertilizer
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• v.37 no.3
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• pp.131-135
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• 2004

This study was carried out for the analysis of temperature characteristics on soil surface using soil heat flux which is one of the important parameters forming soil temperature. Soil surface temperature was estimated by using the soil temperature measured at 10 cm soil depth and the soil heat flux measured by flux plate at 5 cm soil depth. There was time lag of two hours between soil temperature and soil heat flux. Temperature changes over time showed a positive correlation with soil heat flux. Soil surface temperature was estimated by the equation using variable separation method for soil surface temperature. Arithmetic mean using temperatures measured at soil surface and 10 cm depth, and soil temperature measured at 5 cm depth were compared for accuracy of the value. To validate the regression model through this comparison, F-validation was used. Usefulness of deductive regression model was admitted because intended F-value was smaller than 0.001 and the determination coefficient was 0.968. It can be concluded that the estimated surface soil temperatures obtained by variable separation method were almost equal to the measured surface soil temperature.

• Journal of the Korean association of regional geographers
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• v.23 no.1
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• pp.151-167
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• 2017

The main objective of this study was to investigate the climatic impact of $PM_{10}$ concentration on the temperature change pattern in Busan Metropolitan City(BMC), Korea during 2001~2015. Mean $PM_{10}$ concentration of BMC has gradually declined over the past 15 years. While the highest $PM_{10}$ concentration was observed in spring followed by winter, summer, and fall on average, the seasonal variations of $PM_{10}$ concentration differed from place to place within the city. Frequency analysis showed that the most frequently observed $PM_{10}$ concentration ranged from $20{\mu}g/m^3$ to $60{\mu}g/m^3$, which accounted for 64.6% of all daily observations. Overall, the west-high and east-low pattern of $PM_{10}$ concentration was relatively strong during the winter when the effect of yellow-dust events on the air quality was weak. Comparative analyses between $PM_{10}$ concentration and monthly temperature slope derived from generalized temperature curves indicated that the decreasing trend of $PM_{10}$ concentration was associated with increases of annual temperature range, and $PM_{10}$ concentration had a negative relationship with the temperature slope of warming months. Overall, $PM_{10}$ concentration had a weak correlation with the annual mean temperature, but it had a significant, positive correlation with the winter season, which had a dominant influence on the annual mean temperature. In terms of energy budget, it has been known that the change in $PM_{10}$ concentration contributes to the warming or cooling effect by affecting the radiative forcing due to the reflection and absorption of radiant energy. The correlation between $PM_{10}$ concentration and temperature changes in the study area was not seasonally and spatially consistent, and its significance was statistically limited partly due to the number of observations and the lack of potential socioeconomic factors relevant to urban air quality.

• Journal of Bio-Environment Control
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• v.6 no.3
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• pp.205-215
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• 1997

An accurate transpiration model for greenhouse tomato crop, which is liable to transpiration depression and yield loss because of low solar radiation and high humidity, could be an efficient tool for the optimum control of greenhouse climate and for the optimization of Irrigation scheduling. The purpose of this study was to develop transpiration model of greenhouse tomato and to carry out the experimental verification. The formulas to calculate the canopy transpiration and temperature simultaneously were derived from the energy balance of canopy. Transpiration and microclimate variables such as net radiation, solar radiation, humidity, canopy and air temperature, etc. were simultaneously measured to estimate parameters of model equations and to verify the suggested model. Leaf boundary layer resistance was calculated as a function of Nusselt number and stomatal diffusive resistance was parameterized by solar radiation and leaf-air vapor pressure deficit. The equation for stomatal diffusive resistance could explain more than 80％ of its variation and the calculated stomatal diffusive resistance showed good agreements with the measured values in situations independent of which the constants of the equation were estimated. The canopy net radiation calculated by Stanghellini's model with slight modification agreed well with the measured values. The present transpiration model, into which afore-mentioned component equations were assembled, was found to predict the canopy temperature, instantaneous and daily transpiration with considerable accuracy in greenhouse climates.

• Journal of Korea Water Resources Association
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• v.49 no.11
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• pp.903-912
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• 2016

Accurate understanding and estimating Evapotranspiration (ET) is essential for understanding the mechanism of water cycle and water budget. ET has been analyzed by many researchers in worldwide while Ground-based ET has limiation in analyzing the spatio-temporal pattrens of ET. Thus, many researches have been conducted to represent the spatio-temporal variation of ET by using hydrometeorological variables estimated from remote sensing datasets. Previous remote sensing based ET algorithms, however, have disadvantage in that various hydrometeological input datasets were required. In this study, actual ET was estimated by MODIS-based Rn and MS-PT algorithm requiring relatively less input data than previous method. The result confirmed that the observed $R_N$ and latent heat flux from the eddy-covariance based fluxtowers located at CFK and SMK showed high correlation with the estimated $R_N$ and ET. The average determination coefficients ($R^2$) of ET estimated from satellite dataset over study periods were 0.77 (0.72-0.81) in Cheongmi (CFK) and 0.70 (0.67-0.78) in Sulma (SMK), respectively. Comparing with the actual ET of two flux tower sites, however, SMK showed more overestimated patterns than CFK due to the vegetation and radiation related errors.

• Korean Journal of Agricultural and Forest Meteorology
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• v.22 no.3
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• pp.107-116
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• 2020

In this data paper, we share the dataset obtained during 2019 from the test-bed to develop soil moisture estimation technology for upland fields, which was built in Seosan and Taean, South Korea on May 3. T his dataset includes various eco-hydro-meteorological variables such as soil moisture, evapotranspiration, precipitation, radiation, temperature, humidity, and vegetation indices from the test-bed nearby the Automated Agricultural Observing System (AAOS) in Seosan operated by the Korea Meteorological Administration. T here are three remarkable points of the dataset: (1) It can be utilized to develop and evaluate spatial scaling technology of soil moisture because the areal measurement with wide spatial representativeness using a COSMIC-ray neutron sensor as well as the point measurement using frequency/time domain reflectometry (FDR/TDR) sensors were conducted simultaneously, (2) it can be used to enhance understanding of how soil moisture and crop growth interact with each other because crop growth was also monitored using the Smart Surface Sensing System (4S), and (3) it is possible to evaluate the surface water balance by measuring evapotranspiration using an eddy covariance system.

• Korean Journal of Agricultural and Forest Meteorology
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• v.1 no.2
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• pp.119-126
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• 1999

A numerical model using soil surface energy balance and soil heat flow equations to estimate mulched soil temperature was developed. The required inputs data include weather data, such as global solar radiation, air temperature, wind speed, atmospheric water vapor pressure, the optical properties of mulching material, and soil physical properties. The observed average soil temperature at 50 cm depth was used as the initial value of soil temperature at each depth. Soil temperature was simulated starting at 0 hour at an interval of 10 minutes. The model reliably described the variation of soil temperature with time progress and soil depth. The correlation between the estimated and measured temperature yielded coefficient values of 0.961, 0.966 for 5cm and 10cm depth of the bare soil, respectively, 0.969, 0.965 for the paper mulched soil, and 0.915, 0.938 for the black polyethylene film mulched soil. The percentages of absolute differences less than 2$^{\circ}$C between soil temperatures measured and simulated at 10 minute interval were 97.4% and 98.5% for 5 cm and 10cm for the bare soil, respectively, and 95.8% and 97.4% for the paper mulched soil, and 70.1% and 92.5% for the polyethylene film mulched soil. The results indicated that the model was able to predict the soil temperature fairly well under mulched condition. However, in the night time, the model performance was a little poor as compared with day time due to the difficulty of accurate determination of the atmospheric long wave radiation.