• Korean Journal of Agricultural and Forest Meteorology
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• v.17 no.4
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• pp.281-289
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• 2015

Information on sunshine duration and solar radiation are indispensable to the understanding of crop growth and development. Yet, relevant variables are not available in the Korea Meteorological Administration's (KMA) digital forecast. We proposed the methods of estimating sunshine duration and solar radiation based on the 'sky condition' of digital forecast products and validated using the observed data. The sky condition values (1 for clear, 2 for partly cloudy, 3 for cloudy, and 4 for overcast) were collected from 22 weather stations at 3-hourly intervals from August 2013 to July 2015. According to the observed relationship, these data were converted to the corresponding amount of clouds on the 0 to 10 scale (0 for clear, 4 for partly cloudy, 7 for cloudy, and 10 for overcast). An equation for the cloud amount-sunshine duration conversion was derived from the 3-year observation data at three weather stations with the highest clear day sunshine ratio (i.e., Daegwallyeong, Bukgangneung, and Busan). Then, the estimated sunshine hour data were used to run the Angstrom-Prescott model which was parameterized with the long-term KMA observations, resulting in daily solar radiation for the three weather stations. Comparison of the estimated sunshine duration and solar radiation with the observed at those three stations showed that the root mean square error ranged from 1.5 to 1.7 hours for sunshine duration and from 2.5 to $3.0MJ\;m^{-2}\;day^{-1}$ for solar radiation, respectively.

• Proceedings of the Korea Water Resources Association Conference
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• 2018.05a
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• pp.351-354
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• 2018

본 연구에서는 일 증발접시 증발량 모델링을 위한 다변량 적응 회귀 스플라인 (multivariate adaptive regression splines, MARS) 모델의 성능을 평가하였다. 모델 입력변수 집합은 부산 관측소 (기상청)로부터 수집된 기상자료를 활용하여 증발접시 증발량과의 상관성이 높은 변수들의 조합으로 구성되었으며, 일사량, 일조시간, 평균지상온도, 최대기온의 조합으로 구성된 세 가지 입력집합이 결정되었다. MARS 모델의 성능은 네 가지의 모델성능평가지표를 활용하여 정량적으로 산출되었으며, 그 결과를 인공신경망 (artificial neural network, ANN) 모델과 비교하였다. 입력변수로서 일사량 및 일조시간을 가지는 Set 1의 경우 MARS1 모델이 ANN1 모델보다 우수한 성능을 나타내었으며, Set 2 (일사량, 일조시간, 평균지상온도)의 경우 ANN2 모델, Set 3 (일사량, 일조시간, 평균지상온도, 최대기온)의 경우 MARS3 모델이 상대적으로 우수한 모델 성능을 나타내었다. 모든 분석 모델들을 비교하였을 때, MARS3, ANN2, ANN3, MARS2, MARS1, ANN1 모델의 순서로 우수한 모델 성능을 나타내었으며, 특히 MARS3 모델은 CE = 0.790, $r^2=0.800$, RMSE = 0.762, MAE = 0.587로서 가장 우수한 일 증발접시 증발량 모델링 성능을 나타내었다. 따라서 본 연구에서 적용한 MARS 모델은 지상관측 기상자료를 활용한 일 증발접시 증발량 모델링에서 효과적인 대안이 될 수 있을 것으로 판단된다.

• Korean Journal of Agricultural and Forest Meteorology
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• v.25 no.1
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• pp.28-36
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• 2023

Solar radiation that is measured at relatively small number of weather stations is one of key inputs to crop models for estimation of crop productivity. Solar radiation products derived from GK-2A and Himawari 8 satellite data have become available, which would allow for preparation of input data to crop models, especially for assessment of crop productivity under an agrivoltaic system where crop and power can be produced at the same time. The objective of this study was to compare the degree of agreement between the solar radiation products obtained from those satellite data. The sub hourly products for solar radiation were collected to prepare their daily summary for the period from May to October in 2020 during which both satellite products for solar radiation were available. Root mean square error (RMSE) and its normalized error (NRMSE) were determined for daily sum of solar radiation. The cumulative values of solar radiation for the study period were also compared to represent the impact of the errors for those products on crop growth simulations. It was found that the data product from the Himawari 8 satellite tended to have smaller values of RMSE and NRMSE than that from the GK-2A satellite. The Himawari 8 satellite product had smaller errors at a large number of weather stations when the cumulative solar radiation was compared with the measurements. This suggests that the use of Himawari 8 satellite products would cause less uncertainty than that of GK2-A products for estimation of crop yield. This merits further studies to apply the Himawari 8 satellites to estimation of solar power generation as well as crop yield under an agrivoltaic system.

• Korean Journal of Agricultural and Forest Meteorology
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• v.18 no.4
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• pp.221-232
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• 2016

Models to estimate solar radiation have been used because solar radiation is measured at a smaller number of weather stations than other variables including temperature and rainfall. For example, solar radiation has been estimated using the Angstrom-Prescott (AP) model that depends on two coefficients obtained empirically at a specific site ($AP_{Choi}$) or for a climate zone ($AP_{Frere}$). The objective of this study was to identify the coefficients of the AP model for reliable estimation of solar radiation under a wide range of spatial and temporal conditions. A global optimization was performed for a range of AP coefficients to identify the values of $AP_{max}$ that resulted in the greatest degree of agreement at each of 20 sites for a given month during 30 years. The degree of agreement was assessed using the value of Concordance Correlation Coefficient (CCC). When $AP_{Frere}$ was used to estimate solar radiation, the values of CCC were relatively high for conditions under which crop growth simulation would be performed, e.g., at rural sites during summer. The statistics for $AP_{Frere}$ were greater than those for $AP_{Choi}$ although $AP_{Frere}$ had the smaller statistics than $AP_{max}$ did. The variation of CCC values was small over a wide range of AP coefficients when those statistics were summarized by site. $AP_{Frere}$ was included in each range of AP coefficients that resulted in reasonable accuracy of solar radiation estimates by site, year, and month. These results suggested that $AP_{Frere}$ would be useful to provide estimates of solar radiation as an input to crop models in Korea. Further studies would be merited to examine feasibility of using $AP_{Frere}$ to obtain gridded estimates of solar radiation at a high spatial resolution under a complex terrain in Korea.

• Korean Journal of Agricultural and Forest Meteorology
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• v.12 no.4
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• pp.232-237
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• 2010

While global solar radiation is an essential input variable in crop models, the observation stations are relatively sparse compared with other meteorological elements. Instead of using measured solar radiation, the Angstrom-Prescott model estimates have been widely used. Monthly data for solar radiation and sunshine duration are a convenient basis for deriving Angstrom-Prescott coefficients (a, b), but it is uncertain whether daily solar radiation could be estimated with a sufficient accuracy by the monthly data - derived coefficients. We derived the Angstrom-Prescott coefficients from the 25 years observed global solar radiation and sunshine duration data at 18 locations across South Korea. In order to figure out any improvements in estimating daily solar radiation by replacing monthly data with daily data, the coefficients (a, b) for each month were derived separately from daily data and monthly data. Local coefficients for eight validation sites were extracted from the spatially interpolated maps of the coefficients and used to estimate daily solar radiation from September 2008 to August 2009 when, pyranometers were operated at the same sites for validation purpose. Comparison with the measured radiation showed a better performance of the daily data - derived coefficients in estimating daily global solar radiation than the monthly data - derived coefficients, showing 9.3% decrease in the root mean square error (RMSE).

• Korean Journal of Remote Sensing
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• v.29 no.1
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• pp.123-135
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• 2013

The reflectance observed in the visible channels of a geostationary meteorological satellite can be used to calculate the amount of cloud by comparing the reflectance with the observed solar radiation data at the ground. Using this, the solar radiation arriving at the surface can be estimated. This study used the Meteorological Imager (MI) reflectance observed at a wavelength of 675 nm and the Geostationary Ocean Color Imager (GOCI) reflectance observed at similar wavelengths of 660 and 680 nm. Cloudy days during a typhoon and sunny days with little cloud cover were compared using observation data from the geostationary satellite. Pixels that had more than 40% reflectance in the satellite images showed less than 0.3 of the cloud index and blocked more than 70% of the solar energy. Pixels that showed less than 15% reflectance showed more than 0.9 of the cloud index and let through more than 90% of the solar energy to the surface. The calculated daily accumulated solar radiation was compared with the observed daily accumulated solar radiation in 22 observatories of the Korean Meteorological Administration. The values calculated for the COMS and MTSAT MI sensors were smaller than the observation and showed low correlations of 0.94 and 0.93, respectively, which were smaller than the 0.96 correlation coefficient calculated for the GOCI sensor. The RMSEs of MTSAT, COMS MI and GOCI calculation results showed 2.21, 2.09, 2.02 MJ/$m^2$ in order. Comparison of the calculated daily accumulated results from the GOCI sensor with the observed data on the ground gave correlations and RMSEs for cloudy and sunny days of 0.96 and 0.86, and 1.82 MJ/$m^2$ and 2.27 MJ/$m^2$, respectively, indicating a slightly higher correlation for cloudy days. Compared to the meteorological imager, the geostationary ocean color imager in the COMS satellite has limited observation time and observation is not continuous. However, it has the advantage of providing high resolution so that it too can be useful for solar energy analysis.

• Korean Journal of Agricultural and Forest Meteorology
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• v.23 no.2
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• pp.134-140
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• 2021

Global solar radiation consists of direct and diffuse radiations. Both components are necessary for not only atmospheric science and solar energy domains but also agricultural applications. In this study, the data of direct and diffuse radiations are uploaded to Github. It was observed in Naju during May 2019 to November 2020. Using this data, the previous empirical equations using the relation between clearness index and diffuse ratio were validated. All coefficients of determination (R²) and RMSE were similar as 0.79~0.80 and 0.13~0.15. However, to get the lower RMSE, other non-linear approaches will be required with more observation data.

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.457-457
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• 2022

최근 기후변화로 인한 위기가 인류의 생존을 위협하면서 전 지구적으로 기후변화에 대응하기 위한 탄소 중립 대책을 모색하고 있으며, 지속가능한 신재생에너지에 대해 주목하고 있다. 산업통상자원부는 2034년까지 총 발전량 중 신재생에너지의 비율을 25.8%까지 증가시키는 것을 목표로 신재생에너지의 발전 비율을 증가시키기 위한 다양한 노력을 기울이고 있다. 특히, 신재생에너지 중 가장 많은 비중을 차지하고 있는 태양광 발전은 비교적 광범위한 부지를 필요로 하고 있으며, 환경 및 지형적 영향이 크게 작용하는 만큼 발전 시설 부지 선정 및 운용 계획을 위한 면밀한 분석이 필수적이다. 그러나, 태양광 발전 활용 계획을 수립하기 위해 고려할 수 있는 지상 관측 일사량 및 일조량 데이터는 상당히 제한적이며 관측 밀도가 조밀하지 않다는 한계점이 있다. 본 연구에서는 천리안위성의 후속으로 발사된 천리안2위성의 산출물인 일사량 데이터를 활용하여 한반도 영역에서의 일사량에 대한 시·공간적 분석을 수행하였으며, 이를 기반으로 각 지역적 특성을 파악하고, 토지 피복 유형에 따른 태양광 발전의 효율 정도를 분석·평가하였다. 본 연구의 결과는 계측 지역 및 미계측 지역에서의 시공간적인 태양광 에너지의 효율성에 대한 정보를 제공함에 따라 태양광 발전을 위한 관련 시설물들의 최적 설치 위치 및 규모 등에 대한 설계 기준 마련에 활용될 수 있을 것으로 판단된다.

• Korean Journal of Agricultural and Forest Meteorology
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• v.20 no.4
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• pp.366-375
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• 2018

Evapotranspiration (ET) information is needed for many applications in agricultural and environmental resource management because crop yields, plant growth and physiological characteristics are primarily water limited. This study was conducted to evaluate the diurnal change of ET using electronic weighing lysimeter and to determine whether the ET of Cnidium officinale Makino could be manipulated through meteorological factors such as solar radiation, windy conditions and air temperature etc., Pot has a diameter of 35 cm and an height of 38 cm. A disturbed soil of sandy loam (coarse, mixed, mesic family of Dystric Fluventic Eutroudepts) within lysimeter has a mass of approximately 40.0 kg. In 2017, 10-minute recordings of data were used for measuring actual ET, and also evaluating a relationship between ET and meteorological factors during from 2 Aug. to 6 Aug. The maximum daily ET of Cnidium officinale was $44.04{\pm}3.949g$ per hour in lysimetric measurements. Diurnal changes of ET was highly correlated with solar radiation ($r^2=0.7778$) and followed by wind speed ($r^2=0.6400$). But on the other hand, air temperature was not consistent with ET ($r^2=0.2260$). This results imply that ET of Cnidium officinaele seems to be mainly governed by radiation energy in clear days, and approximately 40% of solar radiation is likely to be converted into ET. Therefore, weighing lysimeter can be used to accurately estimate actual ET and is expected to attract a great deal of attention to reliable application of water management in agriculture.

• Korean Journal of Agricultural and Forest Meteorology
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• v.20 no.4
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• pp.376-385
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• 2018

To estimate the hourly temperature distribution due to solar radiation during the day, on slope in complex terrain, an empirical formula was developed including the hourly deviation in the observed temperature following solar radiation deviation, at weather stations on the east-facing and west-facing slopes. The solar radiation effect was simulated using the empirical formula to estimate hourly temperature at 11 weather observation sites in mountainous agricultural areas, and the result was verified for the period from January 2015 to December 2017. When the estimated temperature was compared with the control, only considering temperature lapse rate, it was found that the tendency to underestimate the temperature from 9 am to 3 pm was reduced with the use of an empirical formula in the form of linear expression; consequently, the estimation error was reduced as well. However, for the time from 5 pm to 6 pm, the estimation error was smaller when a hyperbolic equation drawn from the deviation in solar radiation on the slope, which was calculated based on geometric conditions, was used instead of observed values. The reliability of estimating the daytime temperature at 3 pm was compared with existing estimation model proposed in other studies; the estimation error could be mitigated up to an ME (mean error) of $-0.28^{\circ}C$ and RMSE (root mean square error) of $1.29^{\circ}C$ compared to the estimation error in previous models (ME $-1.20^{\circ}C$, RMSE $2.01^{\circ}C$).