• Atmosphere
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• v.31 no.5
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• pp.577-592
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• 2021

This study evaluates the predictability of the number of days of heat and cold damages by growth stages of rice in South Korea using the hindcast data (1986~2020) produced by Pusan National University Coupled General Circulation Model-Weather Research and Forecasting (PNU CGCM-WRF) model chain. The predictability is accessed in terms of Root Mean Square Error (RMSE), Normalized Standardized Deviations (NSD), Hit Rate (HR) and Heidke Skill Score (HSS). For the purpose, the model predictability to produce the daily maximum and minimum temperatures, which are the variables used to define heat and cold damages for rice, are evaluated first. The result shows that most of the predictions starting the initial conditions from January to May (01RUN to 05RUN) have reasonable predictability, although it varies to some extent depending on the month at which integration starts. In particular, the ensemble average of 01RUN to 05RUN with equal weighting (ENS) has more reasonable predictability (RMSE is in the range of 1.2~2.6℃ and NSD is about 1.0) than individual RUNs. Accordingly, the regional patterns and characteristics of the predicted damages for rice due to excessive high- and low-temperatures are well captured by the model chain when compared with observation, particularly in regions where the damages occur frequently, in spite that hindcasted data somewhat overestimate the damages in terms of number of occurrence days. In ENS, the HR and HSS for heat (cold) damages in rice is in the ranges of 0.44~0.84 and 0.05~0.13 (0.58~0.81 and -0.01~0.10) by growth stage. Overall, it is concluded that the PNU CGCM-WRF chain of 01RUN~05RUN and ENS has reasonable capability to predict the heat and cold damages for rice in South Korea.

• Journal of Internet Computing and Services
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• v.23 no.2
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• pp.29-35
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• 2022

UV rays have beneficial or harmful effects on the human body depending on the degree of exposure. An accurate UV information is required for proper exposure to UV rays per individual. The UV rays' information is provided by the Korea Meteorological Administration as one component of daily weather information in Korea. However, it does not provide an accurate UVI at the user's location based on the region's Ultraviolet index. Some operate measuring instrument to obtain an accurate UVI, but it would be costly and inconvenient. Studies which assumed the UVI through environmental factors such as solar radiation and amount of cloud have been introduced, but those studies also could not provide service to individual. Therefore, this paper proposes a deep learning model to calculate UVI using solar object information and sunlight characteristics to provide an accurate UVI at individual location. After selecting the factors, which were considered as highly correlated with UVI such as location and size and illuminance of sun and which were obtained through the analysis of sky images and solar characteristics data, a data set for DNN model was constructed. A DNN model that calculates the UVI was finally realized by entering the solar object information and sunlight characteristics extracted through Mask R-CNN. In consideration of the domestic UVI recommendation standards, it was possible to accurately calculate UVI within the range of MAE 0.26 compared to the standard equipment in the performance evaluation for days with UVI above and below 8.

• Korean Journal of Agricultural and Forest Meteorology
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• v.23 no.3
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• pp.149-155
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• 2021

Early warning systems for weather risk management in the agricultural sector have been developed to predict potential wind damage to crops. These systems take into account the daily maximum wind speed to determine the critical wind speed that causes fruit drops and provide the weather risk information to farmers. In an effort to increase the accuracy of wind risk predictions, an artificial neural network for binary classification was implemented. In the present study, the daily wind speed and other weather data, which were measured at weather stations at sites of interest in Jeollabuk-do and Jeollanam-do as well as Gyeongsangbuk- do and part of Gyeongsangnam- do provinces in 2019, were used for training the neural network. These weather stations include 210 synoptic and automated weather stations operated by the Korean Meteorological Administration (KMA). The wind speed data collected at the same locations between January 1 and December 12, 2020 were used to validate the neural network model. The data collected from December 13, 2020 to February 18, 2021 were used to evaluate the wind risk prediction performance before and after the use of the artificial neural network. The critical wind speed of damage risk was determined to be 11 m/s, which is the wind speed reported to cause fruit drops and damages. Furthermore, the maximum wind speeds were expressed using Weibull distribution probability density function for warning of wind damage. It was found that the accuracy of wind damage risk prediction was improved from 65.36% to 93.62% after re-classification using the artificial neural network. Nevertheless, the error rate also increased from 13.46% to 37.64%, as well. It is likely that the machine learning approach used in the present study would benefit case studies where no prediction by risk warning systems becomes a relatively serious issue.

• Journal of Korea Water Resources Association
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• v.54 no.6
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• pp.419-431
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• 2021

In Seoul, it has been confirmed that the duration of rainfall is shortened and the frequency and intensity of heavy rains are increasing with a changing climate. In addition, due to high population density and urbanization in most areas, floods frequently occur in flood-prone areas for the increase in impermeable areas. Furthermore, the Seoul City is pursuing various projects such as structural and non-structural measures to resolve flood-prone areas. A disaster prevention performance target was set in consideration of the climate change impact of future precipitation, and this study conducted to reduce the overall flood damage in Seoul for the long-term. In this study, 29 GCMs with RCP4.5 and RCP8.5 scenarios were used for spatial and temporal disaggregation, and we also considered for 3 research periods, which is short-term (2006-2040, P1), mid-term (2041-2070, P2), and long-term (2071-2100, P3), respectively. For spatial downscaling, daily data of GCM was processed through Quantile Mapping based on the rainfall of the Seoul station managed by the Korea Meteorological Administration and for temporal downscaling, daily data were downscaled to hourly data through k-nearest neighbor resampling and nonparametric temporal detailing techniques using genetic algorithms. Through temporal downscaling, 100 detailed scenarios were calculated for each GCM scenario, and the IDF curve was calculated based on a total of 2,900 detailed scenarios, and by averaging this, the change in the future extreme rainfall was calculated. As a result, it was confirmed that the probability of rainfall for a duration of 100 years and a duration of 1 hour increased by 8 to 16% in the RCP4.5 scenario, and increased by 7 to 26% in the RCP8.5 scenario. Based on the results of this study, the amount of rainfall designed to prepare for future climate change in Seoul was estimated and if can be used to establish purpose-wise water related disaster prevention policies.

• Journal of the Korean Institute of Landscape Architecture
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• v.44 no.1
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• pp.93-106
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• 2016

This study aimed to estimate and evaluate the thermal mitigation of the urban tree canopy on the summer outdoor environment by quantitative use of mean radiant temperature. This study applied the SOLWEIG model based $T_{mrt}$ comparison method by using both (1) urban tree canopy presence examples and (2) urban tree canopy absence examples as constructed from airborne LiDAR system based three-dimensional point cloud data. As a result, it was found that an urban tree canopy can provide a decrease in the entire domain averaged daily mean $T_{mrt}$ about $5^{\circ}C$ and that the difference can increase up to $33^{\circ}C$ depending both on sun position and site conditions. These results will enhance urban microclimate studies such as indices (e.g., wind speed, humidity, air temperature) and biometeorology (e.g., perceived temperature) and will be used to support forest based public green policy development.

• Journal of Korean Society for Atmospheric Environment
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• v.25 no.5
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• pp.459-471
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• 2009

Air Monitoring Network(11 urban stations) is operated to measure ambient air quality in Daegu city. The urban air monitoring stations include 6 in residence area, 3 in industrial area, 1 in commercial area, and 1 in green area. In this study, hourly data (2006. 1. 1~2008. 12. 31) of $PM_{10}$ were measured at 11 urban air monitoring stations. $PM_{10}$ mean concentrations were high in fall and winter because of low wind speed and many haze days. The number of exceeding the daily standard of $PM_{10}$ in industrial area was approximately twice as many as that in residence area. $PM_{10}$ concentrations and visibility were influenced significantly by wind speed. Wind speed and visibility were below 1.8 m/s and 10 km, respectively when $PM_{10}$ concentrations were over $120{\mu}g/m^3$. $PM_{10}$ concentrations were high when haze was observed. The mean concentrations of $PM_{10}$ were $104{\pm}41.3{\mu}g/m^3$, $63{\pm}35.1{\mu}g/m^3$, and $49{\pm}26.9{\mu}g/m^3$, respectively when haze, mist and clear were observed.

• Journal of the Korean Society of Tobacco Science
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• v.26 no.2 s.52
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• pp.93-101
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• 2004

This study was conducted to investigate the relationship between weather factors during the growing season and chemical components of flue-cured tobacco. Chemical components used in this study was from 'Farm Leaf Tobacco Test' conducted at KT&G Central Research Institute from 1986 through 2003. Data of weather factors during growing season(April to July) were collected in 10 districts measured at Korea Meteorological Adminstration(KMA). Nicotine and total sugar contents, and total sugar to nicotine(TS/Nic.) ratio were increased, whereas total nitrogen to nicotine(TN/Nic.) ratio and chloride content were decreased from 1986 through 2003. Year to year variation of rainfall was the largest, followed by that of sunshine hour. Month to month variation of rainfall also was the largest, followed by that of mean daily air temperature(MDAT). Rainfall was correlated positively with relative humidity(RH), but negatively with sunshine hour. Nicotine content was correlated positively with MDAT(in July, June$\~$July, May$\~$July and average), but negatively with rainfall(in May$\~$July) and with RH(in June, July, May $\~$June, June $\~$July, April$\~$June, May $\~$July and average). Total sugar content was correlated positively with MDAT(in May), but negatively with sunshine hour(average) and RH(in June, July, June$\~$July, April$\~$June, May$\~$July and average). The positive correlation was found between total nitrogen content and sunshine hour(in April, May, April$\~$May, May$\~$July, April$\~$June and average). The negative correlation was found between TS/Nic. ratio and sunshine hour(in May$\~$July and average). TN/Nic. ratio was correlated positively with sunshine hour(in May and April$\~$May) and with RH(in July and June$\~$July), but negatively with MDAT(in July, June$\~$July, May$\~$July and average). Ether extraction content was correlated positively with MDAT(in July, June$\~$July, May$\~$July and average) and with sunshine hour(in July and June$\~$July), but negatively with rainfall(in April, July, May­July and average). Chloride content was correlated positively with sunshine hour(in April, July, April$\~$May, June$\~$July, April$\~$June, May$\~$July and average), but negatively with rainfall(in April, April$\~$June and average).

• Journal of Bio-Environment Control
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• v.26 no.4
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• pp.346-352
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• 2017

In this study, we analyzed environmental factors including annual fruit growth and meteorological conditions in Suwon area from 2000 to 2014 to develop and verify a fruit width prediction model in 'Fuji' apple. The 15-year average of full bloom data was April 28 and that of fruit development period was 181 days. The fruit growth until 36 days after full bloom followed single sigmoid curve. The environmental factors affecting fruit width were BIO2, precipitation in September, the average of daily maximum and minimum temperature in April, minimum temperature in August, and growing degree days (GDD) in April. Among them, the model was constructed by combining BIO2 and precipitation in September, which are not cross-correlated with each other or, with other factors. And then, the final model was selected as 19.33095 + (5.76242 ${\times}$ BIO2) - (0.01891 ${\times}$ September precipitation) + (2.63046 ${\times}$ minimum temperature in April) which was the most suitable model with AICc of 92.61 and the adjusted $R^2$ value of 0.53. The model was compared with the observed values f rom 2000 to 2014. As a result, the mean difference between the measured and predicted values of 'Fuji' apple fruit width was ${\pm}2.9mm$ and the standard deviation was 3.54.

• Journal of Korean Society for Atmospheric Environment
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• v.21 no.1
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• pp.119-129
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• 2005

The ambient TSP data measured at Seoul, Incheon. Taean, Daegu, Busan in Korea were used to explain the chemical composition and general features of Asian Dust (AD) observed in Korea. 9 episodes out of 19 were sampled from 2000 through May 2002, and measurements were conducted covering ionic and metal components with mass concentration. The results showed that daily averaged mass concentration (TSP) during the AD episodes was 458 $\mu\textrm{g}$/㎥, and ionic and metal concentrations were 27.93 $\mu\textrm{g}$/㎥ and 71.7 $\mu\textrm{g}$/㎥, respectively, accounting for 6.1 % and 15.5% of the total aerosol mass. TSP concentrations during episodes were varied from 120 to 1742 $\mu\textrm{g}$/㎥ according to the impact of Asian Dusts and had a tendency of showing higher values at sites in the west side of Korea, which can be explained by the effect of diffusion and deposition. In this study, ionic components like Ca (NO$_3$)$_2$, CaSO$_4$, NaNO$_3$, Na$_2$SO$_4$ were prominent types in secondary aerosol during AD periods and also indicated that V, Co as well as soil elements such as Ca, Fe, Mg, Mn, K correlated well with Al, while Cu, Cd, Pb, Zn didn't agree well with it. In addition, enrichment factors (EFs) for each metal component were obtained to provide simple information about source contribution of Asian Dust, and the results were compared with those from other AD studies. In this study, the results showed that aerosol properties in Korea during the Asian Dust were considerably different from those of general atmospheric condition and specially varied from case to case rather than site to site, which implies that there are certain variations in the soil of source region, pathways of air mass, and meteorological condition. For the enhanced study, those factors should be combined with the features of Asian Dust resolved from this study.

• Journal of Korea Water Resources Association
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• v.46 no.5
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• pp.519-530
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• 2013

To provide a reliable tool for runoff simulations of ungauged watersheds upstream of reservoirs, a daily runoff simulation model, Tank model, is restructured, the parameter regionalization of the model is conducted, and the model's applicability is evaluated. Taking into account the characteristics of runoffs from the watersheds, a three-tank model is employed. The percolation process of the model's third tank is eliminated, considering the water budgets of the watersheds, and its evapotranspiration component is improved, reflecting the conditions of meteorological observation in South Korea. The sensitivity analysis of the model shows that the model's behaviors, varying with a sensitive parameter, ${\alpha}$, are reasonable. The regional parameter estimation equations are determined, using the characteristics and land uses of the watersheds as variables. The model is applied for the runoff simulations of three watersheds and the water stage simulation of one reservoir, and the simulation results are then compared with the observed values, which prove to be in close agreement with the observations. In addition, the results from simulating inflows of twenty-four reservoirs using the model show that the averages of evapotranspiration rate and runoff rate are 42.8% and 56.6%, respectively, which are resonable. Consequently, it is concluded that the model is practically applicable to simulating runoffs from watersheds upstream of reservoirs, and simulated inflow data are useful for watershed management and reservoir planning, design, and operation.