Korean Journal of Agricultural and Forest Meteorology
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v.15
no.4
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pp.298-303
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2013
In this study, the installation effects of a windbreak net on reducing wind speed were examined using meteorological observation data. Three automatic weather systems (AWS) were installed at the inside of the windbreak net of an apple orchard along the distance, and one AWS was located at the outside. They were set up on Oct. $25^{th}$, 2012 at the apple orchard of Geochang County, and meteorological data, which were observed at four stations for about 1 year from October 26, 2012 through October 21, 2013, were used for this study. Meteorological variables include air temperature & relative humidity at a height of 1.5 meter, and wind speed & wind direction at a height of 2 meter and 4 meter. These variables were measured and recorded every 60 seconds. The preliminary results of this study was as follows: (1) Daily mean temperature at the inside of the windbreak net was lower than that of the outside by 0.1 through $0.2^{\circ}C$. (2) Daily mean relative humidity at the inside of the windbreak net was higher than that of the outside by 0.7 through 1.7%. (3) As compared to the outside, northerly daily maximum wind speed of the inside of the windbreak net at a height of 2 and 4 meter was reduced by 0.7~1.5 $ms^{-1}$ (30.4~65.2%) and 0.3~0.7 $ms^{-1}$ (10.3~24.1%), respectively.
Hong, Seung Hwan;Cho, Han Jin;Kim, Mi Kyeong;Sohn, Hong Gyoo
Journal of Korean Society for Geospatial Information Science
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v.23
no.1
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pp.113-121
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2015
Remote sensing technology using a multi-spectral satellite imagery can be utilized for the analysis of urban heat island effect in large area. However, weather condition of Korea mostly has a lot of clouds and it makes periodical observation using time-series of satellite images difficult. For this reason, we proposed the analysis of urban heat island effect using time-series of Landsat TM images and ATC model. To analyze vegetation condition and urbanization, NDVI and NDBI were calculated from Landsat images. In addition, land surface temperature was calculated from thermal infrared images to estimate the parameters of ATC model. Furthermore, the parameters of ATC model were compared based on the land cover map created by Korean Ministry of Environment to analyze urban heat island effect relating to the pattern of land use and land cover. As a result of a correlation analysis between calculated spectral indices and parameters of ATC model, MAST had high correlation with NDVI and NDBI (-0.76 and 0.69, respectively) and YAST also had correlation with NDVI and NDBI (-0.53 and 0.42, respectively). By comparing the parameters of ATC model based on land cover map, urban area had higher MAST and YAST than agricultural land and grassland. In particular, residential areas, industrial areas, commercial areas and transportation facilities showed higher MAST than cultural facilities and public facilities. Moreover, residential areas, industrial areas and commercial areas had higher YAST than the other urban areas.
Korean Journal of Agricultural and Forest Meteorology
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v.9
no.4
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pp.228-233
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2007
Pear psylla, Caccopsylla pyricola (Homoptera: Psyllidae), is a serious insect pest in pear orchards. C. pyricola overwinters as adults under rough bark scales of pear trees. When the weather warms up in the spring, the overwintered adults become active, climb up to the tree branches, and inhabit on fruit twigs to lay eggs. This study was conducted to develop a forecasting model for the onset of upward-movement of overwintered C. pyricola adults to control them by timely spraying of petroleum oil. The adult population densities were observed under rough barks (B) and on fruit twigs (T) of pear trees. Relative upward-movement rates (R) were calculated as T/(B+T). Low threshold temperatures for the activation of overwintered C. pyricola adults were selected arbitrarily from 5 to $9^{\circ}C$ at a $1^{\circ}C$ interval. Then, the days (D) when daily maximum air temperatures were above each low threshold temperature were counted from 1 February until to the dates with R $\geq$ 0.8. The same methods were applied for the prediction of the first observation of eggs. The variation of coefficients (CV) for the mean Des were lowest with the low threshold temperature of $6^{\circ}C$. At this selected threshold temperature, the upward movement of C. pyricola adults occurred with 12 D and they started laying eggs with 25 D. In the field validation, the model outputs with the $6^{\circ}C$ threshold temperature reasonably well explained the observed data in Suwon and Cheonan in 2002. Practical usages of the model were also discussed.
This study used high density network of integrated meteorological sensor, which are operated by SK Planet, with KMA weather stations to estimate the quantitative precipitation field in Seoul area. We introduced SK Planet network and analyzed quality of the observed data for 3 months data from 1 July to 30 September 2013. As the quality analysis result, we checked most SK Planet stations observed similar with previous KMA stations. We developed the real-time quality check and adjustment method to reduce the error effect for hydrological application by missing and outlier value and we confirmed the developed method can be corrected the missing and outlier value. Through this method, we used the 190 stations(KMA 34 stations, SK Planet 156 stations) that missing ratio is less than 20% and the effect of the outlier was the smallest for quantitative precipitation estimation. Moreover, we evaluated reproducibility of rainfall field high density rain gauge network has $3km^2$/gauge. As the result, the spatial relative frequency of rainfall field using SK Planet and KMA stations is similar with radar rainfall field. And, it supplement the blank of KMA observation network. Especially, through this research we will take advantage of the density of the network to estimate rainfall field which can be considered as a very good approximation of the true value.
The interest in rainfall observation and forecasting using remote sensing method like RADAR (Radio Detection and Ranging) and satellite image is increased according to increased damage by rapid weather change like regional torrential rain and flash flood. In this study, the basin runoff was calculated using adaptive neuro-fuzzy technique, one of the data driven model and MAPLE (McGill Algorithm for Precipitation Nowcasting by Lagrangian Extrapolation) forecasted precipitation data as one of the input variables. The flood estimation method using neuro-fuzzy technique and RADAR forecasted precipitation data was evaluated. Six rainfall events occurred at flood season in 2010 and 2011 in Chungju Reservoir basin were used for the input data. The flood estimation results according to the rainfall data used as training, checking and testing data in the model setup process were compared. The 15 models were composed of combination of the input variables and the results according to change of clustering methods were compared and analysed. From this study was that using the relatively larger clustering radius and the biggest flood ever happened for training data showed the better flood estimation. The model using MAPLE forecasted precipitation data showed relatively better result at inflow estimation Chungju Reservoir.
Kim, Young-Hyun;Kim, Eung-Sup;Choi, Myeong-Ju;Shim, Kyo-Moon;Ahn, Joong-Bae
Atmosphere
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v.29
no.5
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pp.671-687
/
2019
This study evaluates the long-term seasonal predictability of summer (June, July and August) heatwaves over South Korea using 30-year (1989~2018) Hindcast data of the Pusan National University Coupled General Circulation Model (PNU CGCM)-Weather Research and Forecasting (WRF) chain. Heatwave indices such as Number of Heatwave days (HWD), Heatwave Intensity (HWI) and Heatwave Warning (HWW) are used to explore the long-term seasonal predictability of heatwaves. The prediction skills for HWD, HWI, and HWW are evaluated in terms of the Temporal Correlation Coefficient (TCC), Root Mean Square Error (RMSE) and Skill Scores such as Heidke Skill Score (HSS) and Hit Rate (HR). The spatial distributions of daily maximum temperature simulated by WRF are similar overall to those simulated by NCEP-R2 and PNU CGCM. The WRF tends to underestimate the daily maximum temperature than observation because the lateral boundary condition of WRF is PNU CGCM. According to TCC, RMSE and Skill Score, the predictability of daily maximum temperature is higher in the predictions that start from the February and April initial condition. However, the PNU CGCM-WRF chain tends to overestimate HWD, HWI and HWW compared to observations. The TCCs for heatwave indices range from 0.02 to 0.31. The RMSE, HR and HSS values are in the range of 7.73 to 8.73, 0.01 to 0.09 and 0.34 to 0.39, respectively. In general, the prediction skill of the PNU CGCM-WRF chain for heatwave indices is highest in the predictions that start from the February and April initial condition and is lower in the predictions that start from January and March. According to TCC, RMSE and Skill Score, the predictability is more influenced by lead time than by the effects of topography and/or terrain feature because both HSS and HR varies in different leads over the whole region of South Korea.
In order to find out the condition of flow in sewer pipes, this study investigated the characteristics of tractive force of sewage flow estimated using actual measured values of water level, velocity, and flowrate in sewers located at uppermost portion in a treatment area during dry weather periods. When the scene of sewage flow was taken by CCTV after cohesive and non-cohesive solids (tofu and sand) were put on the sewer invert, it was found that the solids could be flushed without significant interruption. In sewer with slope of 0.00319, the frequency exceeding the minimum tractive force of sewage during a weekday was zero, while it was 10 per day with slope of 0.00603. During the week of the field observation, the event to exceed the minimum tractive force occurred once, suggesting that sewer odor would potentially increase. Maximum tractive force in sewer with steep slope was 2.9-3.1 N/㎡, but with gentle slope it decreased to 1.6-1.7N/㎡. It was also observed that the interval of time maintained below the criterion of minimum tractive force increased, during weekends compared to weekdays and for the sewage including non-cohesive particles which could enter combined sewers during a storm period. This study found that the sewer sediments formed by direct feces input into sewers, through sewer pipes which were designed meeting the standard sewer design criteria, could be flushed without staying as deposited solids state for a long time.
Park, Hye-In;Zo, Il-Sung;Kim, Bu-Yo;Jee, Joon-Bum;Lee, Kyu-Tae
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.
This study developed a climate informed Bayesian nonstationary frequency model which allows us to forecast seasonal summer rainfall at Nakdong River. We constructed a 37-year summer rainfall data set from 10 weather stations within Nakdong river basin, and two climate indices from sea surface temperature (SST) and outgoing longwave radiation (OLR) were derived through correlation analysis. The selected SST and OLR have been widely acknowledged as a climate driver for summer rainfall. The developed model was applied first to the 2010-year summer rainfall (888.1 mm) in order to assure ourself. We demonstrated model performance by comparing posterior distributions. It was confirmed that the proposed model is able to produce a reasonable forecast. The forecasted value is about 858.2 mm, and the difference between forecast and observation is about 30 mm. As the second case study, 2011-year summer rainfall forecast was made using an observed winter SSTs and an assumed 50% value of OLRs. The forecasted value is 967.7 mm and associated exceedance probability over average summer rainfall 680 mm is 92.9%. In addition, 50-year return period for summer rainfall was projected through the nonstationary frequency model. An exceedance probability over 1,400 mm corresponding to the 50-year return level is about 73.7%.
Journal of the Korean Data and Information Science Society
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v.28
no.4
/
pp.797-810
/
2017
The Korean peninsula is exposed to typhoons every year. Typhoons cause huge socioeconomic damage because tropical cyclones tend to occur with strong winds and heavy precipitation. In order to understand the complex dependence structure between strong winds and heavy precipitation, the copula links a set of univariate distributions to a multivariate distribution and has been actively studied in the field of hydrology. In this study, we carried out analysis using data of wind speed and precipitation collected from the weather stations in Busan and Jeju. Log-Normal, Gamma, and Weibull distributions were considered to explain marginal distributions of the copula. Kolmogorov-Smirnov, Cramer-von-Mises, and Anderson-Darling test statistics were employed for testing the goodness-of-fit of marginal distribution. Observed pseudo data were calculated through inverse transformation method for establishing the copula. Elliptical, archimedean, and extreme copula were considered to explain the dependence structure between strong winds and heavy precipitation. In selecting the best copula, we employed the Cramer-von-Mises test and cross-validation. In Busan, precipitation according to average wind speed followed t copula and precipitation just as maximum wind speed adopted Clayton copula. In Jeju, precipitation according to maximum wind speed complied Normal copula and average wind speed as stated in precipitation followed Frank copula and maximum wind speed according to precipitation observed Husler-Reiss copula.
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