• Journal of the Korean Solar Energy Society
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• v.35 no.3
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• pp.65-71
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• 2015

A solar thermal simulator is suitable for indoor experiments of solar receivers and reactors when solar insolation and weather conditions are not favorable. Moreover, due to the easy control of electric power input, the solar thermal simulator allows the adjustment of power input incident on solar receivers and reactors and thus the implementation of accurate experiments. We manufactured a solar simulator, which is comprised of three sets of a xenon lamp and an elliptical reflector. In order to serve as a test facility, optical characterization of the solar simulator via radiation heat flux measurement is a critical prerequisite. We applied the flux mapping method to measuring the heat flux distribution of the three lamps. We presented the measurement results in terms of the heat flux distribution, the peak heat flux, the power distribution, the maximum power, and the efficiency for electric power conversion into radiation power. Characterization results show that our solar simulator provides the peak heat flux of $3,019kW/m^2$, the maximum power of 16.9 kW, and the conversion efficiency of 45%, additionally with a 10% operation margin for output increase.

• Journal of the Korean Solar Energy Society
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• v.24 no.4
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• pp.11-18
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• 2004

A solar concentrator, named KIERDISH II, was built at KIER in order to investigate the feasibility of high temperature solar energy application system. The constructed concentrator is a dish type solar concentrator with a focal length of 4.68m and a diameter of 7.9m. To successfully operate KIERDISH II, optimal design of the absorber is very important and flux density distribution has to be known. The focal flux density distribution on the receiver was measured. We have observed the shape and size of flux images and evaluated percent power within radius. Flux density distribution is usually measured by a CCD(charge coupled device) camera and a radiometer. In this paper we present a flux mapping method to estimate the characteristic features of the flux density distribution in the focal region of solar concentrator. The minimum radius of receiver is found to be 0.15m and approximately 90% of the incident radiation is intercepted by receiver aperture.

• 한국태양에너지학회:학술대회논문집
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• 2011.11a
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• pp.74-79
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• 2011

Concentration characteristics of the KIER solar furnace are analyzed with a heat flux measurement technique. Total heat capacity of 40kW was confirmed within 1.04% average error, and the normalized maximum heat flux of 3,452 $kW/m^2$ was proved. Non-Gaussian flux distribution in the vertical direction implies that reflectors should not be random rather inclined downwards. Moreover, we characterized flux distribution variations with furnace blind opening ratio, distance from the focal plane, and misalignment of the measurement system. Based on the results, the heat flux distribution can be simply estimated once reflectivity and direct normal insolation values are known. This study will be helpful to the design and the performance evaluation of receivers or chemical reactors.

• Korean Journal of Agricultural and Forest Meteorology
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• v.11 no.1
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• pp.13-18
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• 2009

Accurate solar radiation data are critical to evaluate major physiological responses of plants. For most upland crops and orchard plants growing in complex terrain, however, it is not easy for farmers or agronomists to access solar irradiance data. Here we suggest a simple method using a sun-slope geometry based topographical coefficient to estimate daily solar irradiance on any sloping surfaces from global solar radiation measured at a nearby weather station. An hourly solar irradiance ratio ($W_i$) between sloping and horizontal surface is defined as multiplication of the relative solar intensity($k_i$) and the slope irradiance ratio($r_i$) at an hourly interval. The $k_i$ is the ratio of hourly solar radiation to the 24 hour cumulative radiation on a horizontal surface under clear sky conditions. The $r_i$ is the ratio of clear sky radiation on a given slope to that on a horizontal reference. Daily coefficient for slope correction is simply the sum of $W_i$ on each date. We calculated daily solar irradiance at 8 side slope locations circumventing a cone-shaped parasitic volcano(c.a., 570m diameter for the bottom circle and 90m bottom-to-top height) by multiplying these coefficients to the global solar radiation measured horizontally. Comparison with the measured slope irradiance from April 2007 to March 2008 resulted in the root mean square error(RMSE) of $1.61MJ\;m^{-2}$ for the whole period but the RMSE for April to October(i.e., major cropping season in Korea) was much lower and satisfied the 5% error tolerance for radiation measurement. The RMSE was smallest in October regardless of slope aspect, and the aspect dependent variation of RMSE was greatest in November. Annual variation in RMSE was greatest on north and south facing slopes, followed by southwest, southeast, and northwest slopes in decreasing order. Once the coefficients are prepared, global solar radiation data from nearby stations can be easily converted to the solar irradiance map at landscape scales with the operational reliability in cropping season.

• Korean Journal of Remote Sensing
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• v.22 no.5
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• pp.403-406
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• 2006

An algorithm for detection of yellow sand aerosols has been developed with infrared bands. This algorithm is a hybrid algorithm that has used two methods combined. The first method used the differential absorption in brightness temperature difference between $11{\mu}m\;and\;12{\mu}m\;(BTD1)$. The radiation at $11{\mu}m$ is absorbed more than at $12{\mu}m$ when yellow sand is loaded in the atmosphere, whereas it will be the other way around when cloud is present. The second method uses the brightness temperature difference between $3.7{\mu}m\;and\;11{\mu}m(BTD2)$. This technique is sensitive to dust loading, which the BTD2 is enhanced by reflection of $3.7{\mu}m$ solar radiation. First the Principle Component Analysis (PCA), a form of eigenvector statistical analysis from the two methods, is performed and the aerosol pixel with the lowest 10% of the eigenvalue is eliminated. Then the aerosol index (AI) from the combination of BTD 1 and 2 is derived. We applied this method to Multi-functional Transport Satellite-l Replacement (MTSAT-1R) data and obtained that the derived AI showed remarkably good agreements with Ozone Mapping Instrument (OMI) AI and Moderate Resolution Imaging Spectroradiometer (MODIS) aerosol optical depth.

• Proceedings of the KSRS Conference
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• 1999.11a
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• pp.148-153
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• 1999

Baikdu-san was a very active volcano during the Cenozoic era and is believed to be formed in late Cenozoic era. Recently it was also reported that there was a major eruption in or around 1002 A.D. and there are evidences which indicate that it is still an active volcano and a potential volcanic hazard. Remote sensing techniques have been widely used to monitor various natural hazards, including volcanic hazards. However, during an active volcanic eruption, volcanic ash can basically cover the sky and often blocks the solar radiation preventing any use of optical sensors. Synthetic aperture radar(SAR) is an ideal tool to monitor the volcanic activities and lava flows, because the wavelength of the microwave signal is considerably longer that the average volcanic ash particle size. In this study we have utilized several sets of SAR data to evaluate the utility of the space-borne SAR system. The data sets include JERS-1(L-band) SAR, and RADARSAT(C-band) data which included both standard mode and the ScanSAR mode data sets. We also utilized several sets of auxiliary data such as local geological maps and JERS-1 OPS data. The routine preprocessing and image processing steps were applied to these data sets before any attempts of classifying and mapping surface geological features. Although we computed sigma nought ($\sigma$$^{0}$) values far the standard mode RADARSAT data, the utility of sigma nought image was minimal in this study. Application of various types of classification algorithms to identify and map several stages of volcanic flows was not very successful. Although this research is still in progress, the following preliminary conclusions could be made: (1) sigma nought (RADARSAT standard mode data) and DN (JERS-1 SAR and RADARSAT ScanSAR data) have limited usefulness for distinguishing early basalt lava flows from late trachyte flows or later trachyte flows from the old basement granitic rocks around Baikdu-san volcano, (2) surface geological structure features such as several faults and volcanic lava flow channels can easily be identified and mapped, and (3) routine application of unsupervised classification methods cannot be used for mapping any types of surface lava flow patterns.

• Korean Journal of Remote Sensing
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• v.33 no.3
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• pp.301-311
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• 2017

Aerosol optical properties as well as vertical location of layer can alter the radiative balance of the Earth by reflecting and absorbing solar radiation. In this study, radiative transfer model (RTM) and satellite-based analysis have been used to quantify the top-of-atmosphere (TOA) radiative effect of aerosol layers in the cloudy atmosphere of the northeast Asia. RTM simulation results show that the atmospheric warming effect of aerosols increases with their height in the presence of underlying cloud layer. This relationship is higher for stronger absorbing aerosols and higher surface albedo condition. Over study region ($20-50^{\circ}N$, $110-140^{\circ}E$) and aerosol event cases, it is possible to qualitatively identify absorbing aerosol effects in the presence of clouds by combining the UV Absorbing Aerosol Index (AAI) derived from Total Ozone Mapping Spectrometer (TOMS), cloud parameters derived from the Moderate Resolution Imaging Spectro-radiometer (MODIS), with TOA Upward Shortwave Flux (USF) from the Clouds and the Earth's Radiant Energy System (CERES). As the regional-mean radiative effect of aerosols, 6 - 26 % lower the USF between aerosols and cloud cover is taken into account. These results demonstrate the importance of estimation for the accurate quantification of aerosol's direct and indirect effect.

• Journal of The Korean Society of Agricultural Engineers
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• v.63 no.6
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• pp.1-16
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• 2021

Global warming due to climate change is expected to significantly affect the hydrological cycle of agriculture. Therefore, in order to predict the magnitude of climate impact on agricultural water resources in the future, it is necessary to estimate the water demand for irrigation as the climate change. This study aimed at evaluating the future changes in water demand for irrigation under two Shared Socioeconomic Pathways (SSPs) (SSP2-4.5 and SSP5-8.5) scenarios for paddy rice in Gimje, South Korea. The APEX-Paddy model developed for the simulation of paddy environment was used. The model was calibrated and validated using the H₂O flux observation data by the eddy covariance system installed at the field. Sixteen General Circulation Models (GCMs) collected from the Climate Model Intercomparison Project phase 6 (CMIP6) and downscaled using Simple Quantile Mapping (SQM) were used. The future climate data obtained were subjected to APEX-Paddy model simulation to evaluate the future water demand for irrigation at the paddy field. Changes in water demand for irrigation were evaluated for Near-future-NF (2011-2040), Mid-future-MF (2041-2070), and Far-future-FF (2071-2100) by comparing with historical data (1981-2010). The result revealed that, water demand for irrigation would increase by 2.3%, 4.8%, and 7.5% for NF, MF and FF respectively under SSP2-4.5 as compared to the historical demand. Under SSP5-8.5, the water demand for irrigation will worsen by 1.6%, 5.7%, 9.7%, for NF, MF and FF respectively. The increasing water demand for irrigating paddy field into the future is due to increasing evapotranspiration resulting from rising daily mean temperatures and solar radiation under the changing climate.

• Korean Journal of Agricultural and Forest Meteorology
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• v.25 no.4
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• pp.311-325
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• 2023

This study was conducted to analyze the habitat suitability of the major honey trees including Kalopanax septemlobus Koidz., Prunus spp., Tilia spp., and Styrax obassia Siebold & Zucc. indigenous to mountain Gariwang and Yumeong using the machine learning approach (i.e., MaxEnt model). The AUC values of the model predictions were mostly above 0.7, and the results of the response curves showed that the environmental drivers that had effects on the habitat suitability of the major honey trees were elevation, mean annual precipitation, and mean annual temperature. These results indicate that climatic drivers along the elevation gradient are the main environmental drivers in explaining the distribution patterns of the major honey trees. In addition, the results of the response curves of Prunus spp. and Styrax obassia Siebold & Zucc. differed slightly in terms of slope and mean annual solar radiation as the main environmental drivers. The results of this study will be valuable for the establishment of honey tree forests and management plans for the natural and artificial forests in South Korea, as well as for the mapping the distribution of honey trees. Further studies at different regional levels, reflecting biotic drivers, will be needed to expand the production of honey and pollen at different strata and to produce honey annually.

• Korean Journal of Agricultural and Forest Meteorology
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• v.26 no.1
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• pp.1-30
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• 2024

The international community adopts the SSP (Shared Socioeconomic Pathways) scenario as a new greenhouse gas emission pathway. As part of efforts to reflect these international trends and support for climate change adaptation measure in the agricultural sector, the National Institute of Agricultural Sciences (NAS) produced high-resolution (1 km) climate change scenarios for the Korean Peninsula based on SSP scenarios, certified as a "National Climate Change Standard Scenario" in 2022. This paper introduces SSP climate change scenario of the NAS and shows the results of the climate change projections. In order to produce future climate change scenarios, global climate data produced from 18 GCM models participating in CMIP6 were collected for the past (1985-2014) and future (2015-2100) periods, and were statistically downscaled for the Korean Peninsula using the digital climate maps with 1km resolution and the SQM method. In the end of the 21^st century (2071-2100), the average annual maximum/minimum temperature of the Korean Peninsula is projected to increase by 2.6~6.1℃/2.5~6.3℃ and annual precipitation by 21.5~38.7% depending on scenarios. The increases in temperature and precipitation under the low-carbon scenario were smaller than those under high-carbon scenario. It is projected that the average wind speed and solar radiation over the analysis region will not change significantly in the end of the 21st century compared to the present. This data is expected to contribute to understanding future uncertainties due to climate change and contributing to rational decision-making for climate change adaptation.