• 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.57 no.5
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• pp.333-346
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• 2024

High-resolution medium-range streamflow prediction is crucial for sustainable water quality and aquatic ecosystem management. For reliable medium-range streamflow predictions, it is necessary to understand the characteristics of forcings and to effectively utilize weather forecast data with low spatio-temporal resolutions. In this study, we presented a comparative analysis of medium-range streamflow predictions using the distributed hydrological model, WRF-Hydro, and the numerical weather forecast Global Data Assimilation and Prediction System (GDAPS) in the Geumho River basin, Korea. Multiple forcings, ground observations (AWS&ASOS), numerical weather forecast (GDAPS), and Global Land Data Assimilation System (GLDAS), were ingested to investigate the performance of streamflow predictions with highresolution WRF-Hydro configuration. In terms of the mean areal accumulated rainfall, GDAPS was overestimated by 36% to 234%, and GLDAS reanalysis data were overestimated by 80% to 153% compared to AWS&ASOS. The performance of streamflow predictions using AWS&ASOS resulted in KGE and NSE values of 0.6 or higher at the Kangchang station. Meanwhile, GDAPS-based streamflow predictions showed high variability, with KGE values ranging from 0.871 to -0.131 depending on the rainfall events. Although the peak flow error of GDAPS was larger or similar to that of GLDAS, the peak flow timing error of GDAPS was smaller than that of GLDAS. The average timing errors of AWS&ASOS, GDAPS, and GLDAS were 3.7 hours, 8.4 hours, and 70.1 hours, respectively. Medium-range streamflow predictions using GDAPS and high-resolution WRF-Hydro may provide useful information for water resources management especially in terms of occurrence and timing of peak flow albeit high uncertainty in flood magnitude.

• Journal of The Korean Society of Agricultural Engineers
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• v.58 no.3
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• pp.57-69
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• 2016

In this study, we analyzed the extreme rainfall distribution scenarios based on probable rainfall calculation and applying various time distribution models over the landslide high risk zones in urban areas. We used observed rainfall data form total 71 ASOS (Automated Synoptic Observing System) station and AWS (Automatic Weather Station) in KMA (Korea Meteorological Administration), and we analyzed the linear trends for 1-hr and 24-hr annual maximum rainfall series using simple linear regression method, which are identified their increasing trends with slopes of 0.035 and 0.660 during 1961-2014, respectively. The Gumbel distribution was applied to obtain the return period and probability precipitation for each duration. The IDF (Intensity-Duration-Frequency) curves for landslide high risk zones were derived by applying integrated probability precipitation intensity equation. Results from IDF analysis indicate that the probability precipitation varies from 31.4~38.3 % for 1 hr duration, and 33.0~47.9 % for 24 hr duration. It also showed different results for each area. The $Huff-4^{th}$ Quartile method as well as Mononobe distribution were selected as the rainfall distribution scenarios of landslide high risk zones. The results of this study can be used to provide boundary conditions for slope collapse analysis, to analyze sediment disaster risk, and to use as input data for risk prediction of debris flow.

• Atmosphere
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• v.19 no.1
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• pp.9-36
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• 2009

Two heavy snowfall events occurred in Yeongnam and Yeongdong regions of the Korean Peninsula during the period from 4 to 6 March 2005 are analyzed. The events were developed by two different meso-scale snow clouds associated with an extratropical low passing over the Western Pacific. Based on synoptic data, GOES-9 satellite images, and precipitation amount data, the events were named as Sokcho and Busan cases, respectively. We analyzed the development mechanism of the events using meterological variables from the NCEP(National Centers for Environmental Prediction) /NCAR(National Centers for Atmospheric Research) reanalysis data such as potential vorticity(PV), divergence, tropopause undulation, static stability, and meridional wind circulation. The present analyses show that in the case of Sokcho, the cyclonic circulation in the lower atmosphere in the strong baroclinic region induced the cyclonic circulation in the upper atmosphere. The cyclonic circulation in the lower and upper atmosphere caused a heavy snowfall in the Sokcho region. In the case of Busan, the strong cyclonic circulation in the upper atmosphere was initiated by the stratospheric air intrusion with the high positive PV into the troposphere during the tropopause folding. The upper strong cyclonic circulation enhanced the cyclonic circulation in the lower disturbed atmosphere due to the extratropical low. This lower cyclonic circulation in turn, intensified the upper cyclonic circulation, that caused a heavy snowfall in the Busan region.

• Journal of Korean Society on Water Environment
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• v.34 no.1
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• pp.67-76
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• 2018

There are 34 mega-cities with a population of more than 10 million in the world. One of the highly populated cities in the world is Seoul in South Korea. Seoul receives $1,140million\;m^3/year$ for domestic water, $2million\;m^3/year$ for agricultural water and $6million\;m^3/year$ for industrial water from multi-purpose dams. The maintenance water used for water conservation, ecosystem protection and landscape preservation is $158million\;m^3/year$, which is supplied from natural precipitation. Recently, the use of the other water for preservation of water quality and ecosystem protection in urban areas is increasing. The objectives of this study is to develop the seasonal forecast method of environmental water in urban areas (Seoul, Daejeon, Gwangju, Busan) and to evaluate its predictability. In order to estimate the seasonal outlook information of environmental water from Land Surface Model (LSM), we used the observation weather data of Automated Synoptic Observing System (ASOS) sites, forecast and hind cast data of GloSea5. In the past 30 years (1985 ~ 2014), precipitation, natural runoff and Urban Environmental Water Index (UEI) were analyzed in the 4 urban areas. We calculated the seasonal outlook values of the UEI based on GloSea5 for 2015 year and compared it to UEI based on observed data. The seasonal outlook of UEI in urban areas presented high predictability in the spring, autumn and winter. Studies have depicted that the proposed UEI will be useful for evaluating urban environmental water and the predictability of UEI using GloSea5 forecast data is likely to be high in the order of autumn, winter, spring and summer.

• Journal of Korean Society for Atmospheric Environment
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• v.20 no.5
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• pp.697-711
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• 2004

Severe haze, mist, and fog phenomena occurred in the central part of Korea during 15~25 May 2003 resulted in poor visibility and air quality. When these phenomena occurred, Korean peninsula was under the effects of anticyclone. The atmosphere was stable, and wind speed was so weak. Under this meteorological conditions, air quality was worse and worse. The characteristics of aerosol in Seoul, Incheon, and Gosan (Jeju) during this period are investigated from the $PM_{10}$. TSP concentrations and aerosol number concentrations. Concentrations of $PM_{10}$ and TSP measured at KMA increased upto 176 and 230 J.${\mu}g/m^3$ on 22 May 2003, respectively. Aerosol number concentrations of size range from 0.82 to 6.06 ${\mu}m$ increased in Seoul on 17, 19, and 21~24 May 2003, and the concentrations of $NO_2$ and $SO_2$had maximum value of 0.165 ppm at Gwanak Mt. and 0.036 ppm at Guro-dong on 23 May 2003, respectively. Result from analysis on heavy metal elements showed high concentrations of Zn, Pb, Cr, Ni, Cu, and Cd during 20~24 May 2003. This event is examined by comprehensive analyses of synoptic weather conditions, satellite images, concentrations of suspended particles and air pollutants, and heavy metal elements.

• Journal of Environmental Science International
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• v.6 no.2
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• pp.95-106
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• 1997

The characteristics on the transtion probabilities and periodicity for the daily precipitation occurrence in Korean peninsula are investigated by applying the Markov chain properties to daily precipitation occurrence. In order to examine the responses of Markov Chain properties to the applied period and their magnitudes, three cases (Case A: 1956~ 1985 at 14 stations, Case B: 1965~ 1994 at 14 stations, and Case C: 1985~ 1994 at 63 stations) are considered In this study. The transition probabilities from wet day to wet day for all cases are about 0.50 and in summer, especially July, are higher. In addition, considering them in each station we can find that they are the highest at Ullung-do and lowest at Inchon for all cases. The annual equilibrium probabilities of a wet day appear 0.31 In Case A, 0.30 Case B, and 0. 29 Case C, respectively. This may explain that as the data-period used becomes shorter, the higher the equilibrium probability is. The seasonal distributions of equilibrium probabilities are appeared the lowest(0.23~0.28) in winter and the highest(more than 0.39) in spring and monthly in .truly and in October, repectively. The annual mean wet duration for all cases is 2.04 days in Case A, 1.99 Case B, and 1.89 Case C, repectively. The weather cycle obtained from the annual mean wet and dry duration is 6.54~6.59 days, which are closely associated with the movement of synoptic systems. And the statistical tests show that the transitions of daily precipitation occurrence for all cases may have two-state first Markov chain property, being the stationarity in time and heterogeneity in space.

• Asian Journal of Atmospheric Environment
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• v.10 no.2
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• pp.57-66
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• 2016

Wet deposition fluxes of ions at a coastal site in southwestern Japan in the period 1996-2003 were investigated to quantify the respective contributions of cyclone-, stationary front- and typhoon-associated rains. On average, the deposition fluxes of terrigenous-origin ions, nss-$SO_4{^{2-}}$, $NO_3{^-}$, $NH_4{^+}$ and nss-$Ca^{2+}$ were $37.6{\pm}7.3$, $16.3{\pm}4.2$, $19.0{\pm}3.4$ and $9.6{\pm}4.8meq\;m^{-2}yr^{-1}$, and those of $Na^+$ and $Cl^-$, the major ions in sea water, were $97.0{\pm}38.2$ and $115.2{\pm}48.2meq\;m^{-2}yr^{-1}$, respectively. Cyclone-associated rain constituted more than 50% of the fluxes of the terrigenous ions in almost all years. Stationary front-associated rain also contributed significantly, although the contribution was lower than the contribution by Cyclone-associated rain in almost all years. In particular, the wet deposition flux of nitrogen compounds of $NO_3{^-}$ and $NH_4{^+}$, which are important nutrients for micro-bioactivities in sea surface water, was dominated by cyclone-associated rain. Due to the extreme abundance of $Na^+$ and $Cl^-$ in the rainwater of typhoons, the fluxes of $Na^+$ and $Cl^-$ were contributed substantially by typhoons in years with typhoons' passage although cyclones were still the largest contributor to the fluxes. These results indicate the dominance of cyclones in the wet deposition to the East China Sea areas and the necessity to take rain types into account for a more accurate elucidation of the temporal and spatial variation of the wet deposition.

• Journal of Environmental Science International
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• v.19 no.8
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• pp.983-999
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• 2010

Wind power energy is one of the favorable and fast growing renewable energies. It is most important for exact analysis of wind to evaluate and forecast the wind power energy. The purpose of this study is to improve the performance of numerical atmospheric model by data assimilation over a complex coastal area. The benefit of the profiler is its high temporal resolution and dense observation data at the lower troposphere. Three wind profiler sites used in this study are inhomogeneously situated near south-western coastal area of Korean Peninsula. The method of the data assimilation for using the profiler to the model simulation is the three-dimensional variational data assimilation (3DVAR). The experiment of two cases, with/without assimilation, were conducted for how to effect on model results with wind profiler data. It was found that the assimilated case shows the more reasonable results than the other case compared with vertical observation and surface Automatic Weather Station(AWS) data. Although the effect of sonde data was better than profiler at a higher altitude, the profiler data improves the model performance at lower atmosphere. Comparison with the results of 4 June and 5 June suggests that the efficiency with hourly assimilated profiler data is strongly influenced by synoptic conditions. The reduction rate of Normalized Mean Error(NME), mean bias normalized by averaged wind speed of observation, on 4 June was 28% which was larger than 13% of 5 June. In order to examine the difference in wind power energy, the wind power density(WPD) was calculated and compared.

• Journal of Environmental Science International
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• v.23 no.5
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• pp.873-885
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• 2014

To identify the characteristics of extreme heat events and tropical nights in major cities, the correlations between automated synoptic observing station (ASOS), automatic weather station (AWS), and temperature in seven metropolitan areas were analyzed. Temperatures at ASOS were found to be useful sources of the reference temperature of each area. To set the standard for identifying dates of extreme heat events in relation to regional topography and the natural environment, the monthly and yearly frequency of extreme heat in each region was examined, based on the standards for extreme heat day (EHD), tropical night day (TND), and extreme heat and tropical night day (ETD). All three cases identified 1994 as the year with the most frequent heat waves. The frequency was low according to all three cases in 1993, 2003 and 2009. Meanwhile, the yearly rate of increase was the highest in 1994, followed by 2010 and 2004, indicating that the frequency of extreme heat changed significantly between 1993 and 1994, 2003 and 2004, and 2009 and 2010. Therefore all three indexes can be used as a standard for high temperature events. According to monthly frequency data for EHD, TND, and ETD, July and August accounted for 80% or more of the extreme heat of the entire year.