• Journal of the Korean Institute of Intelligent Systems
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• v.26 no.2
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• pp.93-98
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• 2016

For accurate precipitation forecasts the choice of weather factors and prediction method is very important. Recently, machine learning has been widely used for forecasting precipitation, and artificial neural network, one of machine learning techniques, showed good performance. In this paper, we suggest a new method for forecasting precipitation using DBN, one of deep learning techniques. DBN has an advantage that initial weights are set by unsupervised learning, so this compensates for the defects of artificial neural networks. We used past precipitation, temperature, and the parameters of the sun and moon's motion as features for forecasting precipitation. The dataset consists of observation data which had been measured for 40 years from AWS in Seoul. Experiments were based on 8-fold cross validation. As a result of estimation, we got probabilities of test dataset, so threshold was used for the decision of precipitation. CSI and Bias were used for indicating the precision of precipitation. Our experimental results showed that DBN performed better than MLP.

• Journal of the Society of Disaster Information
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• v.16 no.2
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• pp.248-266
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• 2020

Purpose: The purpose of this study is to create a checklist for each type of disaster and to suggest a method for establishing an appropriate response system and making accurate and rapid decision-making. Method: In order to derive checklist factors, previous case analyses (Tropical Storm Rusa (2002), Typhoon Maemi (2003), and Typhoon Chaba (2016) were conducted for typhoon disaster. Grouping was conducted to derive checklist factors by analyzing general status (climate and weather) information and characteristics by case. Result: The case study was divided into national level and county level. In terms of national unit, eight forecasts were included: weather forecast, typhoon landing status, typhoon intensity, typhoon radius, central pressure, heavy rain conditions, movement speed, and route. Local governments should reflect regional characteristics, focusing on the presence or absence of similar typhoons (paths) in the past, typhoon landing time, regional characteristics, population density, prior disaster recovery, recent disaster occurrence history, secondary damage, forecast warning system. A total of eight items were derived. Conclusion: In the event of a disaster, decision making will be faster if the checklist proposed in this study is used and applied. In addition, it can be used as the basic data for disaster planners' response plans in case of disasters, and it is expected to be a more clear and quick disaster preparedness and response because it reflects local characteristics.

• Journal of the Korean Society for Marine Environment & Energy
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• v.8 no.1
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• pp.46-52
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• 2005

A marine environmental information system (MEIS) useful for optimal route planning of ships running in the ocean was developed. Utilizing the simulated marine environmental data produced by the European Center for Medium-Range Weather Forecasts based on global environmental data observed by satellites, the real-time forecast and long-term statistics of marine environments around planned and probable ship routes are provided. The MEIS consists of a land-based data acquisition and analysis system(MEIS-Center) and a onboard information display system(MEIS-Ship) for graphic description of marine information and optimal route planning of ships. Also, it uses of satellite communication system for data transfer. The marine environmental components of winds, waves, air pressures and storms are provided, in which winds are described by speed and direction and waves are expressed in terms of height, direction and period for both of wind waves and swells. The real-time information is characterized by 0.5° resolution, 10 day forecast in 6 hour interval and daily update. The statistic information of monthly average and maximum value expected for a return period is featured by 1.5° resolution and based on 15 year database. The MEIS-Ship include an editing tool for route simulation and the forecasting and statistic information on planned routes can be displayed in graph or table. The MEIS enables for navigators to design an optimal navigational route that minimizes probable risk and operational cost.

• Korean Journal of Agricultural and Forest Meteorology
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• v.21 no.4
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• pp.221-228
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• 2019

The effects of wind speed on the temperature change during day time could be insignificant in a region with a complex terrain. The objective of this study was to derive empirical relationship between solar radiation and hourly temperature under a windy condition for the period from sunrise to sunset in order to improve hourly air temperature at a site-specific scale. The deviation of the temperature measurements was analyzed along with the changes of the hourly sunlight at weather observation sites located on the east and west slopes under given wind speed. An empirical model where wind speed use used as an independent variable was obtained to quantify the solar effects on the temperature change (MJ/㎡). This model was verified estimating the hourly temperature during the daytime (0600-1900 h) at 25 weather observation sites located in the study area that has complex topography for the period from January to December 2018. The mean error (ME) and root mean square error (RMSE)of the estimated and measured values ranged from -0.98 to 0.67 ℃, and from 0.95 to 2.04 ℃, respectively. The daytime temperature at 1500 h were estimated using new and previous models. It was found that to the model proposed in the present study reduced the measurement errors of the hourly temperature in the afternoon in comparison with the previous model. For example, the ME and RMSE of the previous model were (ME -0.91 ℃ and 1.47 ℃, respectively. In contrast, the values of ME and RMSE were -0.45 ℃ and 1.22 ℃ for the new model, respectively. Our results suggested that the reliability of hourly temperature estimates at a specific site could be improved taking into account the effect of wind as well as solar radiation.

• Journal of the Korean Society of Hazard Mitigation
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• v.7 no.1 s.24
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• pp.21-28
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• 2007

It is very difficult to forecast accurately a damage from the natural disaster which occurs frequently due to the climate change. When the significant weather event is forecast, it will be able to minimize a damage with the suitable prevention action. But 2000's our country meterological disaster damage is a several trillion won. Therefore, this paper analyzes Korea Meterological Administration, Japan Meterological Agency, television and newspaper have reported, information substance, transmission system, an ex post facto valuation about typhoon Nabi between september $5{\sim}7$ in 2005 and heavy rainfall in 1998 at Japan. Through the investigation, we want to present basic data order to rises the application effect of disaster prevention meterological information. We think KMA must present many information report to promote a people's understanding about the meterological information and the serious disaster situation. Also the disaster damage estimation model development is necessary, which forecasts the accurate damage scale due to the weather event, such as typhoon, heavy rainfall, strong wind. And also we think the KMA, National Emergency Management Agency, related agency, television and newspaper must positive reports the contents which is suitable to disaster response phases and an ex post facto examination. Then it grasps the problem of disaster prevention meterological information and must improve effectively.

• Korean Journal of Agricultural and Forest Meteorology
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• v.23 no.4
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• pp.268-279
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• 2021

The geospatial schemes based on topo-climatology have been developed to produce digital climate maps at a site-specific scale. Their development processes are reviewed here to derive the needs for new schemes in the future. Agricultural and forestry villages in Korea are characterized by complexity and diversity in topography, which results in considerably large spatial variations in weather and climate over a small area. Hence, the data collected at a mesoscale through the Automated Synoptic Observing System (ASOS) operated by the Korea Meteorological Administration (KMA) are of limited use. The geospatial schemes have been developed to estimate climate conditions at a local scale, e.g., 30 m, lowering the barriers to deal with the processes associated with production in agricultural and forestry industries. Rapid enhancement of computing technologies allows for near real-time production of climate information at a high-resolution even in small catchment areas and the application to future climate change scenarios. Recent establishment of the early warning service for agricultural weather disasters can provide growth progress and disaster forecasts for cultivated crops on a farm basis. The early warning system is being expanded worldwide, requiring further advancement in geospatial schemes and digital climate mapping.

• Journal of the Korean earth science society
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• v.44 no.6
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• pp.557-577
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• 2023

This study defines non-precipitation information as areas with weak precipitation or cloud particles that radar cannot detect due to weak returned signals, and suggests methods for its utilization in data assimilation. Previous studies have demonstrated that assimilating radar data from precipitation echoes can produce precipitation in model analysis and improve subsequent precipitation forecast. However, this study also recognizes the non-precipitation information as valuable observation and seeks to assimilate it to suppress spurious precipitation in the model analysis and forecast. To incorporate non-precipitation information into data assimilation, we propose observation operators that convert radar non-precipitation information into hydrometeor mixing ratios and relative humidity for the Weather Research and Forecasting Data Assimilation system (WRFDA). We also suggest a preprocessing method for radar non-precipitation information. A single-observation experiment indicates that assimilating non-precipitation information fosters an environment conducive to inhibiting convection by lowering temperature and humidity. Subsequently, we investigate the impact of assimilating non-precipitation information to a real case on July 23, 2013, by performing a subsequent 9-hour forecast. The experiment that assimilates radar non-precipitation information improves the model's precipitation forecasts by showing an increase in the Fractional Skill Score (FSS) and a decrease in the False Alarm Ratio (FAR) compared to experiments in which do not assimilate non-precipitation information.

• Ecology and Resilient Infrastructure
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• v.10 no.4
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• pp.116-124
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• 2023

As the flood damage on small streams increase due to the increase in frequency of extreme climate events, the need to measure hydraulic data of them has increased for disaster risk management. National Disaster Management Institute, Ministry of Interior and Safety develops CADMT, a CCTV-based automatic discharge measurement technology, and operates pilot small streams to verify its performance and develop disaster risk management technology. The research selects two small streams such as the Neungmac and the Jungsunpil streams to develop the Nomograph by using the 4-Parameter Logistic method using only the observed rainfall data from the Automatic Weather System operated by the Korea Meteorological Agency closest to the small streams and discharge data collected by using the CADMT. To evaluate developed Nomograph, the research forecasts floods discharges in each small stream and compares the result with the observed discharges. As a result of the evaluations, the forecasted value is found to represent the observed value well, so if more accurate observed data are collected and the Nomograph based on it is developed in the future, the high-accuracy flood prediction and warning will be possible.

• Journal of the Korean earth science society
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• v.34 no.4
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• pp.303-312
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• 2013

Typhoon Sanba was selected for describing the Korea Meteorological Administration (KMA) Global Data Assimilation Prediction System (GDAPS) model bias tendency in forecast for the interaction between mid-latitude trough and movement speed of typhoon. We used the KMA GDAPS analyses and forecasts initiated 00 UTC 15 September 2012 from the historical typhoon record using Typhoon Analysis and Prediction System (TAPS) and Combined Meteorological Information System-3 (COMIS-3). Sea level pressure fields illustrated a development of the low level mid-latitude cyclogenesis in relation to Jet Maximum at 500 hPa. The study found that after Sanba entered the mid-latitude domain, its movement speed was forecast to be accelerated. Typically, Snaba interacted with mid-latitude westerlies at the front of mid-latitude trough. This event occurred when the Sanba was nearing recurvature at 00 and 06 UTC 17 September. The KMA GDAPS sea level pressure forecasts provided the low level mid-latitude cyclone that was weaker than what it actually analyzed in field. As a result, the mid-latitude circulations affecting on Sanba's movement speed was slower than what the KMA GDAPS actually analyzed in field. It was found that these circulations occurred due to the weak mid-tropospheric jet maximum at the 500 hPa. In conclusion, the KMA GDAPS forecast tends to slow a bias of slow movement speed when Sanba interacted with the mid-latitude trough.

• Journal of the Korean earth science society
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• v.40 no.6
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• pp.584-598
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• 2019

In this study, the effects of air-sea interactions on precipitation over the Seoul-Gyeonggi region of the Korean Peninsula from 28 to 30 August 2018, were analyzed using a Regional atmosphere-ocean Coupled Model (RCM). In the RCM, a WRF (Weather Research Forecasts) was used as the atmosphere model whereas ROMS (Regional Oceanic Modeling System) was used as the ocean model. In a Regional Single atmosphere Model (RSM), only the WRF model was used. In addition, the sea surface temperature data of ECMWF Reanalysis Interim was used as low boundary data. Compared with the observational data, the RCM considering the effect of air-sea interaction represented that the spatial correlations were 0.6 and 0.84, respectively, for the precipitation and the Yellow Sea surface temperature in the Seoul-Gyeonggi area, which was higher than the RSM. whereas the mean bias error (MBE) was -2.32 and -0.62, respectively, which was lower than the RSM. The air-sea interaction effect, analyzed by equivalent potential temperature, SST, dynamic convergence fields, induced the change of SST in the Yellow Sea. In addition, the changed SST caused the difference in thermal instability and kinematic convergence in the lower atmosphere. The thermal instability and convergence over the Seoul-Gyeonggi region induced upward motion, and consequently, the precipitation in the RCM was similar to the spatial distribution of the observed data compared to the precipitation in the RSM. Although various case studies and climatic analyses are needed to clearly understand the effects of complex air-sea interaction, this study results provide evidence for the importance of the air-sea interaction in predicting precipitation in the Seoul-Gyeonggi region.