• Korean Journal of Agricultural and Forest Meteorology
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• v.19 no.1
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• pp.19-26
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• 2017

Surface air temperature ($T_{air}$) is a key variable for the meteorology and climatology, and is a fundamental factor of the terrestrial ecosystem functions. Satellite remote sensing from the Moderate Resolution Imaging Spectroradiometer (MODIS) provides an opportunity to monitor the $T_{air}$. However, the several problems such as frequent cloud cover and mountainous region can result in substantial retrieval error and signal loss in MODIS $T_{air}$. In this study, satellite-based $T_{air}$ was estimated under both clear and cloudy sky conditions in Gangwon Province using Aqua MODIS07 temperature profile product (MYD07_L2) and GCOM-W1 Advanced Microwave Scanning Radiometer 2 (AMSR2) brightness temperature ($T_b$) at 37 GHz frequency, and was compared with the measurements from the Automated Mountain Meteorology Stations (AMOS). The application of ambient temperature lapse rate was performed to improve the retrieval accuracy in mountainous region, which showed the improvement of estimation accuracy approximately 4% of RMSE. A simple pixel-wise regression method combining synergetic information from MYD07_L2 $T_{air}$ and AMSR2 $T_b$ was applied to estimate surface $T_{air}$ for all sky conditions. The $T_{air}$ retrievals showed favorable agreement in comparison with AMOS data (r=0.80, RMSE=7.9K), though the underestimation was appeared in winter season. Substantial $T_{air}$ retrievals were estimated 61.4% (n=2,657) for cloudy sky conditions. The results presented in this study indicate that the satellite remote sensing can produce the surface $T_{air}$ at the complex mountainous region for all sky conditions.

• Asian Journal of Atmospheric Environment
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• v.10 no.1
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• pp.42-50
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• 2016

This study presents a performance evaluation of four different land surface models (LSM) available in Weather Forecast Research (WRF). The research site was located in Haean Basin in South Korea. The basin is very unique by its geomorphology and topography. For a better representation of the complex terrain in the mesoscale model were used a high resolution topography data with a spatial resolution of 30 meters. Additionally, land-use layer was corrected by ground mapping data-sets. The observation equipments used in the study were an ultrasonic anemometer with a gas analyzer, an automatic weather station and a tethered balloon sonde. The model simulation covers a four-day period during autumn. The result shows significant impact of LSM on meteorological simulation. The best agreement between observation and simulation was found in the case of WRF with Noah LSM (WRF-Noah). The WRF with Rapid Update Cycle LSM (WRF-RUC) has a very good agreement with temperature profiles due to successfully predicted fog which appeared during measurements and affected the radiation budget at the basin floor. The WRF with Pleim and Xiu LSM (WRF-PX) and WRF with Thermal Diffusion LSM (WRF-TD) performed insufficiently for simulation of heat fluxes. Both overestimated the sensible and underestimated the latent heat fluxes during the daytime.

• Aerospace Engineering and Technology
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• v.11 no.1
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• pp.27-41
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• 2012

In this paper, there is analyzed the disturbances to impact on COMS attitude and the attitude error using the received telemetries in KARI ground station during normal mode of COMS. COMS was launched successfully at Kourou, French Guiana on the 26th of June, 2010. Up to now after IOT(in-orbit test), COMS is performing well the main mission to measure meteorology and ocean during about half and one year. The disturbances to impact on COMS attitude are mostly by the Sun, by the motion of payload mirror and by the spike happened during operation of earth sensor mirror and wheel. The analysis result on the other cases happened rarely during the nominal operation, is summarized.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2003.04a
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• pp.69-74
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• 2003

GPS/Meteorology technique for PWV monitoring is currently actively being researched an advanced nation. But, there is no detailed research on an evaluation of precision of GPS derived PWV measurements during the period of foul weather condition. Here, we deal with the precision of GPS derived PWV during the passage of Typhoon RUSA. Typhoon RUSA which caused a series damage was passed over in Korea from August 30 to September 1, 2002. We compared th tropospheric wet delay estimated from GPS observation and radio-sonde data at four sites(Suwon, Kwangju, Taegu, Cheju). The mean standard deviation of PWV differences at each site is ${\pm}$0.005mm. We also obtained GPS PWV at 13 GPS permanent stations(Seoul, Wonju, Seosan, Sangju, Junju, Cheongju, Taegu, Wuljin, Jinju, Daejeon, Mokpo, Sokcho, Jeju). GPS PWV time series shows, in general, peak value before and during th passage of RUSA, and low after the RUSA. GPS PWV peak time at each station is related to the progress of a typhoon RUSA. We obtained very similar result as we compare GMS satellite image with tomograph using GPS PWV and we could present th possibility of practical use by numerical model for weather forecast.

• Wind and Structures
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• v.28 no.6
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• pp.381-388
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• 2019

This paper described the application of Geospatial Analysis in determining mean wind speed, $V_h$ for wind load calculation imposed to electrical transmission tower structural design. The basic wind speed data on available station obtained from Malaysian Meteorology Department is adjusted by considering terrain and ground roughness factor. The correlation between basic wind speed, terrain factor and ground roughness stated in EN-50341-1 is used to obtain the $V_h$ for overhead transmission line elements 50 m above ground. Terrain factor, $k_r$ and ground roughness, $z_0$ in this study are presented by land use types of study area. Wind load is then calculated by using equation stated in design code EN-50341-1 by using the adjusted mean wind speed. Scatter plots of $V_h$ for different $k_r$and $z_0$ are presented in this paper to see the effect of these parameters to the value of $V_h$. Geospatial analysis is used to represent the model of $V_h$. This model can be used to determine possible area that will subject to wind load which severe to the stability of transmission tower and transmission line.

• Korean Journal of Agricultural and Forest Meteorology
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• v.21 no.2
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• pp.85-96
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• 2019

Solar radiation is an important variable for estimation of energy balance and water cycle in natural and agricultural ecosystems. A deep neural network (DNN) model has been developed in order to estimate the daily global solar radiation. Temperature and precipitation, which would have wider availability from weather stations than other variables such as sunshine duration, were used as inputs to the DNN model. Five-fold cross-validation was applied to train and test the DNN models. Meteorological data at 15 weather stations were collected for a long term period, e.g., > 30 years in Korea. The DNN model obtained from the cross-validation had relatively small value of RMSE ($3.75MJ\;m^{-2}\;d^{-1}$) for estimates of the daily solar radiation at the weather station in Suwon. The DNN model explained about 68% of variation in observed solar radiation at the Suwon weather station. It was found that the measurements of solar radiation in 1985 and 1998 were considerably low for a small period of time compared with sunshine duration. This suggested that assessment of the quality for the observation data for solar radiation would be needed in further studies. When data for those years were excluded from the data analysis, the DNN model had slightly greater degree of agreement statistics. For example, the values of $R^2$ and RMSE were 0.72 and $3.55MJ\;m^{-2}\;d^{-1}$, respectively. Our results indicate that a DNN would be useful for the development a solar radiation estimation model using temperature and precipitation, which are usually available for downscaled scenario data for future climate conditions. Thus, such a DNN model would be useful for the impact assessment of climate change on crop production where solar radiation is used as a required input variable to a crop model.

• Korean Journal of Agricultural and Forest Meteorology
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• v.20 no.4
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• pp.277-283
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• 2018

The crop growth model has been widely used for climate change impact assessment. Crop growth model require genetic coefficients for simulating growth and yield. In order to determine the genetic coefficients, regional growth monitoring data or yield trial data of crops has been used to calibrate crop growth model. The aim of this study is to verify that yield trial data of corn is appropriate to calibrate genetic coefficients of CERES-MAIZE. Field experiment sites were Suwon, Jinju, Daegu and Changwon. The distance from the weather station to the experimental field were from 1.3km to 27km. Genetic coefficients calibrated by yield trial data showed good performance in silking day. The genetic coefficients associated with silking are determined only by temperature. In CERES-MAIZE model, precipitation or irrigation does not have a significant effect on phenology related genetic coefficients. Although the effective distance of the temperature could vary depending on the terrain, reliable genetic coefficients were obtained in this study even when a weather observation site was within a maximum of 27 km. Therefore, it is possible to estimate the genetic coefficients by yield trial data in study area. However, the yield-related genetic coefficients did not show good results. These results were caused by simulating the water stress without accurate information on irrigation or rainfall. The yield trial reports have not had accurate information on irrigation timing and volume. In order to obtain significant precipitation data, the distance between experimental field and weather station should be closer to that of the temperature measurement. However, the experimental fields in this study was not close enough to the weather station. Therefore, When determining the genetic coefficients of regional corn yield trial data, it may be appropriate to calibrate only genetic coefficients related to phenology.

• Atmosphere
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• v.23 no.2
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• pp.187-204
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• 2013

This study analyzed the synoptic distribution and vertical structure about four cases of precipitation occurrences using NCEP/NCAR reanalysis data and upper level data of winter intensive observation to be performed by National Institute of Meteorological Research at Bukgangneung, Incheon, Boseong during 63days from 4 JAN to 6 MAR in 2012, and Observing System Experiment (OSE) using 3DVAR-WRF system was conducted to examine the precipitation predictability of upper level data at western and southern coastal regions. The synoptic characteristics of selected precipitation occurrences were investigated as causes for 1) rainfall events with effect of moisture convergence owing to low pressure passing through south sea on 19 JAN, 2) snowfall events due to moisture inflowing from yellow sea with propagation of Siberian high pressure after low pressure passage over middle northern region on 31 JAN, 3) rainfall event with effect of weak pressure trough in west low and east high pressure system on 25 FEB, 4) rainfall event due to moisture inflow according to low pressures over Bohai bay and south eastern sea on 5 MAR. However, it is identified that vertical structure of atmosphere had different characteristics with heavy rainfall system in summer. Firstly, depth of convection was narrow due to absence of moisture convergence and strong ascending air current in middle layer. Secondly, warm air advection by veering wind with height only existed in low layer. Thirdly, unstable layer was limited in the narrow depth due to low surface temperature although it formed, and also values of instability indices were not high. Fourthly, total water vapor amounts containing into atmosphere was small due to low temperature distribution so that precipitable water vapor could be little amounts. As result of OSE conducting with upper level data of Incheon and Boseong station, 12 hours accumulated precipitation distributions of control experiment and experiments with additional upper level data were similar with ones of observation data at 610 stations. Although Equitable Threat Scores (ETS) were different according to cases and thresholds, it was verified positive influence of upper level data for precipitation predictability as resulting with high improvement rates of 33.3% in experiment with upper level data of Incheon (INC_EXP), 85.7% in experiment with upper level data of Boseong (BOS_EXP), and 142.9% in experiment with upper level data of both Incheon and Boseong (INC_BOS_EXP) about accumulated precipitation more than 5 mm / 12 hours on 31 January 2012.

• Korean Journal of Agricultural and Forest Meteorology
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• v.5 no.4
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• pp.261-265
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• 2003

Cold air accumulation plays a critical role in formulating daily minimum temperature in complex terrain on radiative cooling nights, and spatial interpolation can be improved by accommodating this important topoclimatic variable. Little is known about the spatial scale for computing cold air accumulation which influences daily minimum temperature. Air temperature was measured at 10-minute intervals during September 2002- February 2003 at eight locations within a 1 by 1 km hilly orchard area. Minimum temperature data for suspected radiative cooling nights were collected, and the deviations from reference observations at a near-by KMA automated weather station were calculated. A digital elevation model with a 10m cell size was used to calculate the cold air accumulation at 8 locations. Zonal averages of the cold air accumulation were computed for each location by increasing the cell radius from 1 to 10. Temperature deviations were regressed to a common logarithm of the smoothed averages of cold air accumulation to derive a linear relationship between the local temperature deviation and the site topography. The highest coefficient of determination ($r^2$ = 0.78) was found at a cell radius of 5, which corresponds to an approximately 1 ha boundary surrounding the point of interest.

• Korean Journal of Agricultural and Forest Meteorology
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• v.9 no.3
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• pp.195-202
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• 2007

The normalized difference in incident solar energy between a target surface and a level surface (overheating index, OHI) is useful in eliminating estimation error of site-specific maximum temperature in complex terrain. Due to the complexity in its calculation, however, an empirical proxy variable called northern exposure index (NEI) which combines slope and aspect has been used to estimate OHI based on empirical relationships between the two. An experiment with real-world landscape and temperature data was carried out to evaluate performance of the NEI - derived OHI (N-OHI) in reduction of spatial interpolation error for daily maximum temperature compared with that by the original OHI. We collected daily maximum temperature data from 7 sites in a mountainous watershed with a $149 km^2$ area and a 795m elevation range ($651{\sim}1,445m$) in Pyongchang, Kangwon province. Northern exposure index was calculated for the entire 166,050 grid cells constituting the watershed based on a 30-m digital elevation model. Daily OHI was calculated for the same watershed ana regressed to the variation of NEI. The regression equations were used to estimate N-OHI for 15th of each month. Deviations in daily maximum temperature at 7 sites from those measured at the nearby synoptic station were calculated from June 2006 to February 2007 and regressed to the N-OHI. The same procedure was repeated with the original OHI values. The ratio sum of square errors contributable by the N-OHI were 0.46 (winter), 0.24 (fall), and 0.01 (summer), while those by the original OHI were 0.52, 0.37 and 0.15, respectively.