• Journal of Bio-Environment Control
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• v.11 no.2
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• pp.56-60
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• 2002

Since the transmittance of solar radiation directly affected by the structural frames of greenhouse can be changed according to the ratio of diffuse to direct radiations, it is necessary to investigate the transmittance of greenhouse at the different weather conditions. We can easily get the data of total solar radiation from the Meteorological Administration, but we have to personally measure the photosynthetic photon flux (PPF). If the relationship between total solar radiation and PPF is established, the PPF can be simply acquired from the relationship. Sol it is required to develop the equation to calculate PPF depending on weather condition. This study was conducted to determine the transmittance of PPF at canopy level in glasshouse and the correlation between total solar radiation and PPF at clear and cloudy days. The variation phase of greenhouse transmittance at clear day was very different from that at cloudy day. It was concluded that the proper transmittance, depending on the weather condition, should be adopted to calculate the accurate total solar radiation and PPF in greenhouse. The transmittance of solar radiation was the same as that of PPF in greenhouse. It was confirmed that the ratio of PPF to total radiation increased as the amount of cloud increased. The correlation between the hourly total solar radiation and PPF was derived.

• Proceedings of the Korean Society for Bio-Environment Control Conference
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• 2001.04b
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• pp.73-74
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• 2001

순환식 펄라이트 재배에서 오이의 양액흡수는 일사량 변화와 관계없이 단위 일사량당 흡수량이 80-100mgㆍMJ$^{-1}$까지 증가 후 일정하게 유지되어 양액흡수 지표는 전체 양액흡수량보다 단위일사량당 양액흡수량이 더 적합하였다(Fig. 1). 오이의 엽장$\times$엽폭 수치와 실측 엽면적과의 관계는 Y=-16.87＋0.987x＋5E-5x$^2$의 회귀식을 구할 수 있었으며 $r^2$=0.89의 높은 정의 상관을 보였다. NO$_3$$^{-}$ -N의 흡수량은 초기에 3mgㆍMJ$^{-1}$에서 후기 16mgㆍMJ$^{-1}$로 상승하였고 Ca는 초기에 3mgㆍMJ$^{-1}$에서 후기에 14mgㆍMJ$^{-1}$로, Mg는 초기에 1mgㆍMJ$^{-1}$에서 후기에 5mgㆍMJ$^{-1}$로 증가되었으나, 정식 후 62일 이후의 증가세가 둔화되었다. K는 초기에 5.0mgㆍMJ$^{-1}$에서 후기 18mgㆍMJ$^{-1}$로 증가되었으나 지속적인 증가를 보여주지 못하였는데 이것은 오이의 하엽 제거로 인한 결과로 생각되어진다. 그러나 P는 초기에 0.5mgㆍMJ$^{-1}$에서 후기에 3.2mgㆍMJ$^{-1}$로 지속적으로 증가되었다. S는 초기에 0.5mgㆍMJ$^{-1}$에서 중기에 6.5mgㆍMJ$^{-1}$까지 증가되다가 후기에 2.7mgㆍMJ$^{-1}$로 감소되었다(Fig. 2). 오이의 각각의 무기이온 흡수량과 가장 상관이 높았던 요소는 정식일수와 엽면적이었으며 이 두 요소와 단위일사량당 양액흡수량과는 $r^2$=0.92, 0.97로 높은 상관을 보였다(Table 1). 단위일사량당 양액흡수량을 이용한 각각의 무기이온 흡수량 회귀식은 $r^2$=0.8 이상으로 높은 상관관계를 보여 실용적 이용이 가능할 것으로 보였다(Fig. 3).

• Journal of the Korean earth science society
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• v.38 no.2
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• pp.129-140
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• 2017

Global solar radiation was calculated in this research using ground-base measurement data, meteorological satellite data, and GWNU (Gangneung-Wonju National University) solar radiation model. We also analyzed the accuracy of the GWNU model by comparing the observed solar radiation according to the total cloud cover. Our research was based on the global solar radiation of the GWNU radiation site in 2012, observation data such as temperature and pressure, humidity, aerosol, total ozone amount data from the Ozone Monitoring Instrument (OMI) sensor, and Skyview data used for evaluation of cloud mask and total cloud cover. On a clear day when the total cloud cover was 0 tenth, the calculated global solar radiations using the GWNU model had a high correlation coefficient of 0.98 compared with the observed solar radiation, but root mean square error (RMSE) was relatively high, i.e., $36.62Wm^{-2}$. The Skyview equipment was unable to determine the meteorological condition such as thin clouds, mist, and haze. On a cloudy day, regression equations were used for the radiation model to correct the effect of clouds. The correlation coefficient was 0.92, but the RMSE was high, i.e., $99.50Wm^{-2}$. For more accurate analysis, additional analysis of various elements including shielding of the direct radiation component and cloud optical thickness is required. The results of this study can be useful in the area where the global solar radiation is not observed by calculating the global solar radiation per minute or time.

• Proceedings of the Korea Water Resources Association Conference
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• 2017.05a
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• pp.237-240
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• 2017

지구온난화로 인해 세계 곳곳에서 기온상승이 관측되고 있으며, 이는 전지구적 기후시스템의 변화를 보여주는 대표적인 예이다. 온도를 비롯한 강수량, 풍속, 증발량 등의 기상학적, 수문학적 인자들이 각각 서로에게 영향을 주고 받으며 복잡하게 변화할 것이고, 그 변화폭도 점점 커질 것이다. 증발에 영향을 미치는 인자들은 크게 세 가지로 나뉘는데, 태양복사에너지, 온도, 바람, 기압, 습도와 같은 기상학적인자, 증발표면의 특성인자 그리고 수질인자로 분류할 수 있다. 증발에 영향을 주는 인자들은 예전부터 알려져 있지만 이들 간의 복잡한 상호작용에 대해 정확히 이해하기는 쉽지 않다. 본 연구에서는 댐유역의 증발량에 영향을 미치는 기상인자 파악을 위해 2008부터 2016년까지 관측된 낙동강수계 내 안동댐과 남강댐의 기상자료(기온, 강수량, 풍속, 상대습도, 기압, 일사량, 일조시간, 전운량)를 이용한 변화를 분석하였으며, 다변량 통계기법인요인분석을 통해 증발량과 상관성이 높은 인자들을 분류하였다. 안동댐과 남강댐 공통적으로 증발량과 기온, 기압이 같은 요인으로 분류되고 높은 상관성을 보였으며, 강수량, 일조시간, 일사량, 전운량이 같은 요인으로 분류되었다. 국내의 증발량 측정지점에 대한 추가적인 분석과 영향인자를 이용한 다변량회귀식과 인공신경망 통해 증발량 미측정 지점의 증발량 산정이 가능할 것으로 판단된다.

• KIISE Transactions on Computing Practices
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• v.23 no.11
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• pp.632-640
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• 2017

Although solar insolation is the weather factor with the greatest influence on power generation in photovoltaic systems, the Meterological Agency does not provide solar insolation data for future dates. Therefore, it is essential to research prediction methods for solar insolation to efficiently manage photovoltaic systems. In this study, we propose a Dynamic Piecewise Prediction Model that can be used to predict solar insolation values for future dates based on information from the weather forecast. To improve the predictive accuracy, we dynamically divide the entire data set based on the sun altitude and cloudiness at the time of prediction. The Dynamic Piecewise Prediction Model is developed by applying a polynomial linear regression algorithm on the divided data set. To verify the performance of our proposed model, we compared our model to previous approaches. The result of the comparison shows that the proposed model is superior to previous approaches in that it produces a lower prediction error.

• Korean Journal of Environment and Ecology
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• v.32 no.4
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• pp.413-424
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• 2018

The study analyzed the effects of topographic structures and altitude in mountainous parks in Mt. Namsan in Gyeongju on the generation of anions. The temperature was at ridge ($9.82^{\circ}C$) > valley ($8.44^{\circ}C$), the relative humidity valley (59.01 %) > ridge (58.64 %), the solar radiation ridge ($34.40W/m^2$) > valley($14.69W/m^2$), the wind speed ridge (0.63m/s) > valley(0.37m/s), and the negative ion valley($636.81ea/cm^3$) > ridge($580.04ea/cm^3$). In the valley, the correlation with altitude was verified for the temperature, relative humidity, solar radiation, and negative ion generation in the valley. The relative humidity, solar radiation, and negative ion indicated a positive correlation while the temperature had a negative correlation. In the ridge, the correlation with altitude was verified for the temperature, relative humidity, wind speed, solar radiation, and negative ion generation. The relative humidity, solar radiation, and negative ion generation indicated a positive correlation while the temperature and wind speed had a negative correlation. The regression analysis showed the prediction equation of y=-0.006x+9.663 (x=altitude, y=temperature) in the valley and y=-0.009x+11.595 (x=altitude, y=temperature) in the ridge for the temperature, y=0.027x+53.561 (x=altitude, y=relative humidity) in the valley and y=0.008x+56.646 (x=altitude, y=relative humidity) in the ridges for the relative humidity, and y=0.027x+53.561 (x=altitude, y=negative Ion generation) in the valley and y= 0.008x+56.646 (x=altitude, y=negative Ion generation) in the ridge for the negative ion generation.

• Journal of Institute of Convergence Technology
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• v.4 no.2
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• pp.27-33
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• 2014

To well design the solar energy system using solar energy, the correlation to calculate solar irradiation is basically needed. So, this study was performed to reveal the relationships between the solar irradiation and four meteorological observation data(dry bulb temperature, relative humidity, sunshine duration, and cloud cover) which are different from previous other researches. And then, we finally proposed the first order non-linear correlation from the measured solar irradiation using four meteorological observation data with MINITAB. To show the deviation of the solar irradiation between measured and calculated, this study compared using the daily total solar irradiance and the maximum peak value. From those results, the calculation error was estimated about maximum 25.4% for the daily total solar irradiance. The error of the solar irradiation between measured and calculated was made from the curve fitting error. So, solar irradiation prediction correlation with higher accuracy can be obtained using 2nd or higher order terms with four meteorological observation data.

• Journal of Bio-Environment Control
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• v.10 no.2
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• pp.125-131
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• 2001

The objective of this study was to estimate the amount of nutrient and water taken up at different growth stages by cucumber (Cucumis sativus L. cv. Eunsung Backdadagi) grown in a closed substrate culture system. The amount of nutrient solution absorbed increased in proportion to days from planting at the first stage of growth and depended on the level of radiation after the mid stage of growth. After the mid growth stage, the amount of nutrient solution absorption was maintained at 80-100 mg.MJ$^{-1}$ . Total amount of absorbed inorganic ions except S increased since the nutrient solution absorption increased with the level of radiation, although the absorption rate of each inorganic ion declined. A highly significant correlation ($R^2$>0.9) was found between amount of inorganic ions absorbed and days after planting, LAI, total dry weight and leaf dry weight, but not with CGR. Correlation coefficient between days after planting and the amount of nutrient solution absorbed per unit radiation level was 0.92. Correlation coefficient between leaf area an the amount of nutrient solution absorbed per unit radiation level was 0.97. Regression of the amount of nutrient solution absorbed per unit radiation level and nutrient ions uptake showed a high significance ($R^2$>0.9).

• Korean Journal of Remote Sensing
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• v.29 no.1
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• pp.151-160
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• 2013

Recently, although many efforts have been made to estimate insolation over Korean Peninsula based on satellite imagery, most of them have utilized overseas satellite imagery. This paper aims to estimate insolation over the Korean Peninsula based on the Korean stationary orbit satellite imagery. It utilizes level 1 data and level 2 cloud image of COMS MI, the first meteorological satellite of Korea, and OMI image of NASA as input data. And Kawamura physical model which has been known to be suitable for East Asian area is applied. Daily global horizontal insolation was estimated by using satellite images of every fifteen minutes for the period from May 2011 to April 2012, and the estimates were compared to the ground based measurements. The estimated and observed daily insolations are highly correlated as the $R^2$ value is 0.86. The error rates of monthly average insolation was under ${\pm}15%$ in most stations, and the annual average error rate of horizontal global insolation ranged from -5% to 5% except for Seoul. The experimental results show that the COMS MI based approach has good potential for estimating insolation over the Korean Peninsula.

• Journal of Korean Society of Steel Construction
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• v.9 no.3 s.32
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• pp.431-440
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• 1997

The paper describes a theoretical model for the prediction of bridge temperatures from meteorological data measured at bridge site and local meteorological center together with existing finite element heat transfer theory and solar radiation transfer theory to determine the time dependent temperature distribution of bridge. In this analytical model, the most adequate equation for the calculation of solar radiation on the bridge surface, which is dominant in day time is described based on the results of several experimental studies for the solar energy. The validity of this model is tested against field data obtained from long term experimental program on Sadang Viaduct in Seoul. Also, this paper describes the linear correlation between design variables and meteorological data to establish analytical criteria for the prediction of the average temperature, which are responsible for the longitudinal deformation of the bridges and of the vertical differential temperature profiles. which are responsible for the bending deformations from the long term experimental results.