• Journal of Wetlands Research
• /
• v.21 no.4
• /
• pp.305-311
• /
• 2019

Recently, global climate change causes abnormal weather and disaster countermeasures do not provide sufficient defense and mitigation because they were established according to the historical climate condition. Repeated torrential rains, in particular, are causing damage even in the robust urban flood defense system. Therefore, in this study, the change of runoff considering the spatial distribution of rainfall and urban characteristics was analyzed. For rainfall concentrated in small catchment, rainfall in the watershed must be accurately measured. This study is based on the rainfall data observed with Automated Surface Observing System (ASOS) and Automatic Weather Stations (AWS) provided by the Seoul Meteorological Administration. Effluent from the pumping station was estimated using the EPA-SWMM model and compared and analyzed. Catchments with rainwater pumping station are small with large portion of impermeable areas. Thus, when the ASOS data where is located from from the chatchment, runoff is often calculated using rainfall data that is different from rainfall in the catchment. In this study, the difference between rainfall data observed in the AWS near the catchment and ASOS away from the catchment was calculated. It was found that accurate rainfall should be used to operate rainwater pumping stations or forecast urban flooding floods. In addition, the results of this study may be helpful for estimating design rainfall and runoff calculation.

• Korean Journal of Remote Sensing
• /
• v.36 no.6_3
• /
• pp.1711-1720
• /
• 2020

Particulate matter (PM) that has been artificially generated during the recent of rapid industrialization and urbanization moves and disperses according to weather conditions, and adversely affects the human skin and respiratory systems. The purpose of this study is to predict the PM10 concentration in Seoul using meteorological factors as input dataset for multiple linear regression (MLR), support vector machine (SVM), and random forest (RF) models, and compared and evaluated the performance of the models. First, the PM10 concentration data obtained at 39 air quality monitoring sites (AQMS) in Seoul were divided into training and validation dataset (8:2 ratio). The nine meteorological factors (mean, maximum, and minimum temperature, precipitation, average and maximum wind speed, wind direction, yellow dust, and relative humidity), obtained by the automatic weather system (AWS), were composed to input dataset of models. The coefficients of determination (R2) between the observed PM10 concentration and that predicted by the MLR, SVM, and RF models was 0.260, 0.772, and 0.793, respectively, and the RF model best predicted the PM10 concentration. Among the AQMS used for model validation, Gwanak-gu and Gangnam-daero AQMS are relatively close to AWS, and the SVM and RF models were highly accurate according to the model validations. The Jongno-gu AQMS is relatively far from the AWS, but since PM10 concentration for the two adjacent AQMS were used for model training, both models presented high accuracy. By contrast, Yongsan-gu AQMS was relatively far from AQMS and AWS, both models performed poorly.

• Atmosphere
• /
• v.22 no.2
• /
• pp.267-277
• /
• 2012

The objectives of this study are to develop a real-time drought monitoring and prediction system on the East Asia domain and to evaluate the performance of the system by using past historical drought records. The system is mainly composed of two parts: drought monitoring for providing current drought indices with meteorological and hydrological conditions; drought outlooks for suggesting future drought indices and future hydrometeorological conditions. Both parts represent the drought conditions on the East Asia domain (latitude $21.15{\sim}50.15^{\circ}$, longitude $104.40{\sim}149.65^{\circ}$), Korea domain (latitude $30.40{\sim}43.15^{\circ}$, longitude $118.65{\sim}135.65^{\circ}$) and South Korea domain (latitude $30.40{\sim}43.15^{\circ}$, longitude $118.65{\sim}135.65^{\circ}$), respectively. The observed meteorological data from ASOS (Automated Surface Observing System) and AWS (Automatic Weather System) of KMA (Korean Meteorological Administration) and model-driven hydrological data from LSM (Land Surface model) are used for the real-time drought monitoring, while the monthly and seasonal weather forecast information from UM (Unified Model) of KMA are utilized for drought outlooks. For the evaluation of the system, past historical drought records occurred in Korea are surveyed and are compared with the application results of the system. The results demonstrated that the selected drought indices such as KMA drought index, SPI (3), SPI (6), PDSI, SRI and SSI are reasonable, especially, the performance of SRI and SSI provides higher accuracy that the others.

• Journal of Korea Water Resources Association
• /
• v.39 no.8 s.169
• /
• pp.717-726
• /
• 2006

In this study, we developed a rainfall forecasting model using data from radiosonde and rain gauge network and neural networks. The primary hypothesis is that if we can consider the moving direction of the rain generating weather system in forecasting rainfall, we can get more accurate results. We assume that the moving direction of the rain generating weather system is same as the wind direction at 700mb which is measured at radiosonde networks. Neural networks are consisted of 8 different modules according to 8 different wind directions. The model was verified using 350 AWS data and Pohang radiosonde data. Correlation coefficient is improved from 0.41 to 0.73 and skill score is 0.35. Statistical performance measures of the Quantitative Precipitation Forecast (QPF) model show improved output compared to that of rainfall forecasting model using only AWS data.

• Korean Journal of Remote Sensing
• /
• v.20 no.6
• /
• pp.397-408
• /
• 2004

In this study, surface temperature which was extracted from Landsat TM band 6 was compared and analyzed with the AWS(Automatic Weather System) observation data for studying urban heat environment properties with possibility of remote sensing data application. In order to verification of the distribution properties of urban surface temperature, correlation analysis between surface temperature and NDVI, the distribution properties of urban surface temperature by land use/cover patterns were carried out by GIS spatial analysis techniques. The results presented that the spatial distribution of urban surface temperature was very different depending on various land use/cover patterns of surrounding areas. Also there was the reverse linear relationship between surface temperature and NDVI. These results will be worked as one of the major factors for environmentally sustainable urban planning considering the characteristics of weather environments in the near future.

• International Journal of Computer Science & Network Security
• /
• v.22 no.8
• /
• pp.371-379
• /
• 2022

The environment in Kosovo is a topic of concern for the citizens and the state because of the temperatures that affect the health of the citizens and the climate around the world. Kosovo's climate is related to its geographical position. Stretching in the middle latitude, Kosovo's climate depends on the amount of heat coming from the Sun, the proximity of the Adriatic Sea, the Vardar valley, the openness to the north. In order to better understand the climatic features of Kosovo, one must know the elements of the climate such as: sunshine, temperature, precipitation, atmospheric pressure, winds. The Meteorological Institute of Kosovo is responsible for measuring temperatures in Kosovo since 2014 and until now 12 meteorological stations have been operationalized with automatic measurement and real-time data transfer to the central system for data collection and archiving. The hydrometeorological institute lacks an application for measuring temperatures in all the countries of Kosovo. Software applications are generally built to suit the requirements of different governments and clients in order to enable easier management of the jobs they operate on. One of the forms of application development is the development of mobile applications based on android. The purpose of the work is to create a mobile application based on the Android operating system that aims to display information about the weather, this type of application is necessary and important for users who want to see the temperature in different places in Kosovo, but also the world. This type of application offers many options such as maximum temperature, minimum temperature, humidity, and air pressure. The built application will have real and accurate data; this will be done by comparing the results with other similar applications. Such an application is necessary for everyone, especially for those people whose daily work is dependent on the weather or even for those who decide to spend their vacations, such as summer or winter. In this paper, comparisons are also made within android applications for tablets, televisions and smart watches.

• Journal of Korea Water Resources Association
• /
• v.45 no.7
• /
• pp.631-641
• /
• 2012

In this study, satellite data (MTSAT-1R), a numerical weather prediction model, RDAPS (Regional Data Assimilation and Prediction System) output, ground weather station data, and artificial neural networks were used to improve the accuracy of summer rainfall forecasts. The developed model was applied to the Seoul station to forecast the rainfall at 3, 6, 9, and 12-hour lead times. Also to reflect the different weather conditions during the summer season which is related to the frontal precipitation and the cyclonic precipitation such as Jangma and Typhoon, the neural network models were formed for two different periods of June-July and August-September respectively. The rainfall forecast model was trained during the summer season of 2006 and 2008 and was verified for that of 2009 based on the data availability. The results demonstrated that the model allows us to get the improved rainfall forecasts until lead time of 6 hour, but there is still a large room to improve the rainfall forecast skill.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.63 no.4
• /
• pp.526-533
• /
• 2014

In this study, we introduce design methodology to develop a guidance for issuing heavy rainfall warning by using both RBFNNs(Radial basis function neural networks) and SVR(Support vector regression) model, and then carry out the comparative studies between two pattern classifiers. Individual classifiers are designed as architecture realized with the aid of optimization and pre-processing algorithm. Because the predictive performance of the existing heavy rainfall forecast system is commonly affected from diverse processing techniques of meteorological data, under-sampling method as the pre-processing method of input data is used, and also data discretization and feature extraction method for SVR and FCM clustering and PSO method for RBFNNs are exploited respectively. The observed data, AWS(Automatic weather wtation), supplied from KMA(korea meteorological administration), is used for training and testing of the proposed classifiers. The proposed classifiers offer the related information to issue a heavy rain warning in advance before 1 to 3 hours by using the selected meteorological data and the cumulated precipitation amount accumulated for 1 to 12 hours from AWS data. For performance evaluation of each classifier, ETS(Equitable Threat Score) method is used as standard verification method for predictive ability. Through the comparative studies of two classifiers, neuro-fuzzy method is effectively used for improved performance and to show stable predictive result of guidance to issue heavy rainfall warning.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.30 no.6_1
• /
• pp.567-574
• /
• 2012

For the past few years, the video surveillance market has shown a rapid growth due to the increasing demand for Closed Circuit Television(CCTV) by the public sector and the private security industry. While the overall utilization of CCTV in the public and private sectors is expanding, its usage in the field of disaster management is less than sufficient. Therefore, the authors of this study, in an effort to revisit the role of CCTV in disaster situations, have carried out a case analysis in the vicinity of the Gangnam Station which has been designated as a natural disaster-prone area. First, the CCTV images around the target location are collected and the time and depth of inundation are measured through field surveys and image analyses. Next, a rainfall analysis was conducted using the Automatic Weather Station(AWS) data and the past inundation records. Lastly, the authors provide an estimate of rainfall for the areas around the station and suggest viable warning systems and countermeasures. The results from this study are expected to make positive contributions towards a significant reduction of the damages caused by the floods around the Gangnam Station.

• Journal of Satellite, Information and Communications
• /
• v.7 no.3
• /
• pp.30-34
• /
• 2012

National Meteorological Satellite Center(NMSC) of Korea Meteorological Administration(KMA) has launched to implement the application development to get prepared for the space weather operation since 2010. As a action of KMA's space weather work, NMSC constructed Global Navigation Satellite System(GNSS) application system for meteorology and space weather. We will introduce NMSC's space weather application system which derives regional TEC(Total Electron Content) in near real time using nation-wide GNSS network data. First, We constructed system for collecting GNSS data, which is currently collecting about 80 stations operated by agencies like NGII(National Geographic Information Institute), Central Office of DGPS(Differential GPS), and KASI(Korea Astronomy and Space Science) including KMA's own data of 2 stations. In order to retreive regional TEC over Korean peninsular, we build up the automatic processes running every 1-hour. In these processes, firstly, GNSS data of every stations with 24 hours time window are processed to derive DCBs(Differential Code Biases) of each GNSS station and TEC values on every ionosphere piercing point(IPP). Then we made gridded regional TEC map with resolution of 0.25 degree from 31N, 121E to 41N, 135E by combination of all station results within 30 minutes window with assumption that TEC of a given point during a given 30 minutes window would have a constant value. The grid points without TEC value are interpolated using Barnes objective analysis. We presentour regional TEC maps, which can describe better on the status of ionosphere over Korean peninsular compared to IGS TEC maps.