• Journal of Bio-Environment Control
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• v.32 no.1
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• pp.48-56
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• 2023

High-pressure sodium (HPS) lamps have been widely used as a useful supplemental light source to emit sufficient photosynthetically active radiation and provide a radiant heat, which contribute the heat requirement in greenhouses. The objective of this study to analyze the thermal characteristics of HPS lamp and thermal behavior in supplemented greenhouse, and evaluate the performance of a horizontal leaf temperature of sweet pepper plants using computational fluid dynamics (CFD) simulation. We simulated horizontal leaf temperature on upper canopy according to three growth stage scenarios, which represented 1.0, 1.6, and 2.2 plant height, respectively. We also measured vertical leaf and air temperature accompanied by heat generation of HPS lamps. There was large leaf to air temperature differential due to non-uniformity in temperature. In our numerical calculation, thermal energy of HPS lamps contributed of 50.1% the total heat requirement on Dec. 2022. The CFD model was validated by comparing measured and simulated data at the same operating condition. Mean absolute error and root mean square error were below 0.5, which means the CFD simulation values were highly accurate. Our result about vertical leaf and air temperature can be used in decision making for efficient thermal energy management and crop growth.

• Journal of the Korean Society of Radiology
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• v.17 no.4
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• pp.541-549
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• 2023

The aim of this study wasto conduct a quantitative analysis of CT image quality according to an algorithm designed to reduce metal artifacts induced by metal components. Ten baseline images were obtained with the standard filtered back-projection algorithm using spectral detector-based CT and CT ACR 464 phantom, and ten images were also obtained on the identical phantom with the standard filtered back-projection algorithm after inducing metal artifacts. After applying the to raw data from images with metal artifacts, ten additional images for each were obtained by applying the virtual monoenergetic algorithm. Regions of interest were set for polyethylene, bone, acrylic, air, and water located in the CT ACR 464 phantom module 1 to conduct compare the Hounsfield units for each algorithm. The algorithms were individually analyzed using root mean square error, mean absolute error, signal-to-noise ratio, peak signal-to-noise ratio, and structural similarity index to assess the overall image quality. When the Hounsfield units of each algorithm were compared, a significant difference was found between the images with different algorithms (p < .05), and large changes were observed in images using the virtual monoenergetic algorithm in all regions of interest except acrylic. Image quality analysis indices revealed that images with the metal artifact reduction algorithm had the highest resolution, but the structural similarity index was highest for images with the metal artifact reduction algorithm followed by an additional virtual monoenergetic algorithm. In terms of CT images, the metal artifact reduction algorithm was shown to be more effective than the monoenergetic algorithm at reducing metal artifacts, but to obtain quality CT images, it will be important to ascertain the advantages and differences in image qualities of the algorithms, and to apply them effectively.

• Korean Journal of Remote Sensing
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• v.28 no.5
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• pp.477-487
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• 2012

Sea surface winds in the sea off the east coast of Korea were derived from L-band ALOS (Advanced Land Observing Satellite) PALSAR (Phased Array type L-band Synthetic Aperture Radar) data and their characteristics of errors were analyzed. We could retrieve high-resolution wind vectors off the east coast of Korea including the coastal region, which has been substantially unavailable from satellite scatterometers. Retrieved SAR-wind speeds showed a good agreement with in-situ buoy measurement by showing relatively small an root-mean-square (RMS) error of 0.67 m/s. Comparisons of the wind vectors from SAR and scatterometer presented RMS errors of 2.16 m/s and $19.24^{\circ}$, 3.62 m/s and $28.02^{\circ}$ for L-band GMF (Geophysical Model Function) algorithm 2009 and 2007, respectively, which tended to be somewhat higher than the expected limit of satellite scatterometer winds errors. L-band SAR-derived wind field exhibited the characteristic dependence on wind direction and incidence angle. The previous version (L-band GMF 2007) revealed large errors at small incidence angles of less than $21^{\circ}$. By contrast, the L-band GMF 2009, which improved the effect of incidence angle on the model function by considering a quadratic function instead of a linear relationship, greatly enhanced the quality of wind speed from 6.80 m/s to 1.14 m/s at small incident angles. This study addressed that the causes of wind retrieval errors should be intensively studied for diverse applications of L-band SAR-derived winds, especially in terms of the effects of wind direction and incidence angle, and other potential error sources.

• Journal of Korea Water Resources Association
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• v.47 no.4
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• pp.371-384
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• 2014

This study developed a new algorithm of extreme rainfall extraction based on the Communication, Ocean and Meteorological Satellite (COMS) and the Tropical Rainfall Measurement Mission (TRMM) Satellite image data and evaluated its applicability for the heavy rainfall event in July-2011 in Seoul, South Korea. The power-series-regression-based Z-R relationship was employed for taking into account for empirical relationships between TRMM/PR, TRMM/VIRS, COMS, and Automatic Weather System(AWS) at each elevation. The estimated Z-R relationship ($Z=303R^{0.72}$) agreed well with observation from AWS (correlation coefficient=0.57). The estimated 10-minute rainfall intensities from the COMS satellite using the Z-R relationship generated underestimated rainfall intensities. For a small rainfall event the Z-R relationship tended to overestimated rainfall intensities. However, the overall patterns of estimated rainfall were very comparable with the observed data. The correlation coefficients and the Root Mean Square Error (RMSE) of 10-minute rainfall series from COMS and AWS gave 0.517, and 3.146, respectively. In addition, the averaged error value of the spatial correlation matrix ranged from -0.530 to -0.228, indicating negative correlation. To reduce the error by extreme rainfall estimation using satellite datasets it is required to take into more extreme factors and improve the algorithm through further study. This study showed the potential utility of multi-geostationary satellite data for building up sub-daily rainfall and establishing the real-time flood alert system in ungauged watersheds.

• Journal of the Korean earth science society
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• v.37 no.7
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• pp.448-464
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• 2016

The purpose of this study is to optimize the parameters related to consensus coherency within the PCL 1300, the operating program of wind profiler, from a validation of wind data between rawinsonde and wind profiler at Chupungryeong ($36^{\circ}13^{\prime}$, $127^{\circ}59^{\prime}$) site in Korea. It is then to analyze the diurnal and seasonal characteristics of the turbulence energy dissipation rate (${\varepsilon}$) in clear and rainy days from March 2009 to February 2010. In comparison of the wind data between wind profiler and rawinsonde during April 22-23, 2010, it was shown in a big error more than $10ms^{-1}$ over the height of 3,000 meters in the zonal (u) and meridional (v) wind components. When removing more than $10ms^{-1}$ in each wind speed difference of u an v components between the two instruments, the correlation coefficients of these wind components were 0.92 and 0.88, respectively, and the root mean square errors were 3.07 and $1.06ms^{-1}$. Based on these results, when the data processing time and the minimum available data within the PCL 1300 program were adjusted as 30 minutes and 60%, respectively, the bias errors were small. In addition, as a result of an analysis of sensitivity to consensus coherency of u and v components within the PCL1300 program, u components were underestimated in radial coherency, instantaneous and winbarbs coherency, whereas v components were overestimated. Finally by optimizing parameters of the PCL1300 program, the diurnal and seasonal means of ${\varepsilon}$ at each height were higher in rainy days than those in clear days because of increasing in the vertical wind speed due to upward and downward motions. The mean ${\varepsilon}$ for clear and rainy days in winter was lower than those of other seasons, due to stronger horizontal wind speed in winter than those in other seasons. Consequently, when the turbulence energy dissipation rates in the vertical wind speed of more than ${\pm}10cm\;s^{-1}$ were excluded for clear and rainy days, the mean ${\varepsilon}$ in rainy days was 6-7 times higher than that in clear days, but when considering them, it was 4-5 times higher.

• 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.

• Journal of the Korean earth science society
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• v.39 no.2
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• pp.139-153
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• 2018

The sea surface wind field has long been obtained from satellite scatterometers or passive microwave radiometers. However, the importance of satellite altimeter-derived wind speed has seldom been addressed because of the outstanding capability of the scatterometers. Satellite altimeter requires the accurate wind speed data, measured simultaneously with sea surface height observations, to enhance the accuracy of sea surface height through the correction of sea state bias. This study validates the wind speeds from the satellite altimeters (GFO, Jason-1, Envisat, Jason-2, Cryosat-2, SARAL) and analyzes characteristics of errors. In total, 1504 matchup points were produced using the wind speed data of Ieodo Ocean Research Station (IORS) and of Korea Meteorological Administration (KMA) buoys at Marado and Oeyeondo stations for 10 years from December 2007 to May 2016. The altimeter wind speed showed a root mean square error (RMSE) of about $1.59m\;s^{-1}$ and a negative bias of $-0.35m\;s^{-1}$ with respect to the in-situ wind speed. Altimeter wind speeds showed characteristic biases that they were higher (lower) than in-situ wind speeds at low (high) wind speed ranges. Some tendency was found that the difference between the maximum and minimum value gradually increased with distance from the buoy stations. For the improvement of the accuracy of altimeter wind speed, an equation for correction was derived based on the characteristics of errors. In addition, the significance of altimeter wind speed on the estimation of sea surface height was addressed by presenting the effect of the corrected wind speeds on the sea state bias values of Jason-1.

• Korean Journal of Agricultural and Forest Meteorology
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• v.13 no.4
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• pp.176-184
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• 2011

Cold air on sloping surfaces flows down to the valley bottom in mountainous terrain at calm and clear nights. Based on the assumption that the cold air flow may be the same as the water flow, current models estimate temperature drop by regarding the cold air accumulation at a given location as the water-like free drainage. At a closed catchment whose outlet is blocked by man-made obstacles such as banks and roads, however, the water-like free drainage assumption is no longer valid because the cold air accumulates from the bottom first. We developed an empirical model to estimate quantitatively the effect of cold pool on nocturnal temperature in a closed catchment. In our model, a closed catchment is treated like a "vessel", and a digital elevation model (DEM) was used to calculate the maximum capacity of the cold pool formed in a closed catchment. We introduce a topographical variable named "shape factor", which is the ratio of the cold air accumulation potential across the whole catchment area to the maximum capacity of the cold pool to describe the relative size of temperature drop at a wider range of catchment shapes. The shape factor is then used to simulate the density profile of cold pool formed in a given catchment based on a hypsometric equation. The cold lake module was incorporated with the existing model (i.e., Chung et al., 2006), generating a new model and predicting distribution of minimum temperature over closed catchments. We applied this model to Akyang valley (i.e., a typical closed catchment of 53 $km^2$ area) in the southern skirt of Mt. Jiri National Park where 12 automated weather stations (AWS) are operational. The performance of the model was evaluated based on the feasibility of delineating the temperature pattern accurately at cold pool forming at night. Overall, the model's ability of simulating the spatial pattern of lower temperature were improved especially at the valley bottom, showing a similar pattern of the estimated temperature with that of thermal images obtained across the valley at dawn (0520 to 0600 local standard time) of 17 May 2011. Error in temperature estimation, calculated with the root mean square error using the 10 low-lying AWSs, was substantially decreased from $1.30^{\circ}C$ with the existing model to $0.71^{\circ}C$ with the new model. These results suggest the feasibility of the new method in predicting the site-specific freeze and frost warning at a closed catchment.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.23 no.1
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• pp.1-19
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• 2018

In order to compare significant wave height (SWH) data from multi-satellites (GFO, Jason-1, Envisat, Jason-2, Cryosat-2, SARAL) and SWH measurements from Ieodo Ocean Research Station (IORS), we constructed a 12 year matchup database between satellite and IORS measurements from December 2004 to May 2016. The satellite SWH showed a root mean square error (RMSE) of about 0.34 m and a positive bias of 0.17 m with respect to the IORS wave height. The satellite data and IORS wave height data did not show any specific seasonal variations or interannual variability, which confirmed the consistency of satellite data. The effect of the wind field on the difference of the SWH data between satellite and IORS was investigated. As a result, a similar result was observed in which a positive biases of about 0.17 m occurred on all satellites. In order to understand the effects of topography and the influence of the construction structures of IORS on the SWH differences, we investigated the directional dependency of differences of wave height, however, no statistically significant characteristics of the differences were revealed. As a result of analyzing the characteristics of the error as a function of the distance between the satellite and the IORS, the biases are almost constant about 0.14 m regardless of the distance. By contrast, the amplitude of the SWH differences, the maximum value minus the minimum value at a given distance range, was found to increase linearly as the distance was increased. On the other hand, as a result of the accuracy evaluation of the satellite SWH from the Donghae marine meteorological buoy of Korea Meteorological Administration, the satellite SWH presented a relatively small RMSE of about 0.27 m and no specific characteristics of bias such as the validation results at IORS. In this paper, we propose a conversion formula to correct the significant wave data of IORS with the satellite SWH data. In addition, this study emphasizes that the reliability of data should be prioritized to be extensively utilized and presents specific methods and strategies in order to upgrade the IORS as an international world-wide marine observation site.

• Journal of the Korean earth science society
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• v.43 no.3
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• pp.367-385
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• 2022

This study evaluates the temperature and precipitation results in East Asia simulated from the Hadley Centre Global Environmental Model version 3 regional climate model (HadGEM3-RA) developed by the UK Met Office. The HadGEM3-RA is conducted in the Coordinated Regional climate Downscaling Experiment-East Asia (CORDEX-EA) Phase II domain for 15 year (2000-2014). The spatial distribution of rainbands produced from the HadGEM3-RA by the summer monsoon is in good agreement with the Asian Precipitation Highly Resolved Observational Data Integration Towards Evaluation of water resources (APRODITE) data over the East Asia. But, precipitation amount is overestimated in Southeast Asia and underestimated over the Korean Peninsula. In particular, the simulated summer rainfall and APRODITE data show the least correlation coefficient and the maximum value of root mean square error in South Korea. Prediction of temperature in Southeast Asia shows underestimation with a maximum error during winter season, while it appears the largest underestimation in South Korea during spring season. In order to evaluate local predictability, the time series of temperature and precipitation compared to the ASOS data of the Seoul Meteorological Station is similar to the spatial average verification results in which the summer precipitation and winter temperature underestimate. Especially, the underestimation of the rainfall increases when the amounts of precipitation increase in summer. The winter temperature tends to underestimate at low temperature, while it overestimates at high temperature. The results of the extreme climate index comparison show that heat wave is overestimated and heavy rainfall is underestimated. The HadGEM3-RA simulated with a horizontal resolution of 25 km shows limitations in the prediction of mesoscale convective system and topographic precipitation. This study indicates that improvement of initial data, horizontal resolution, and physical process are necessary to improve predictability of regional climate model.