• The Bulletin of The Korean Astronomical Society
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• v.42 no.2
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• pp.61.1-61.1
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• 2017

As the application of deep-learning methods has been succeeded in various fields, they have a high potential to be applied to space weather forecasting. Convolutional neural network, one of deep learning methods, is specialized in image recognition. In this study, we apply the AlexNet architecture, which is a winner of Imagenet Large Scale Virtual Recognition Challenge (ILSVRC) 2012, to the forecast of daily solar flare occurrence using the MatConvNet software of MATLAB. Our input images are SOHO/MDI, EIT $195{\AA}$, and $304{\AA}$ from January 1996 to December 2010, and output ones are yes or no of flare occurrence. We consider other input images which consist of last two images and their difference image. We select training dataset from Jan 1996 to Dec 2000 and from Jan 2003 to Dec 2008. Testing dataset is chosen from Jan 2001 to Dec 2002 and from Jan 2009 to Dec 2010 in order to consider the solar cycle effect. In training dataset, we randomly select one fifth of training data for validation dataset to avoid the over-fitting problem. Our model successfully forecasts the flare occurrence with about 0.90 probability of detection (POD) for common flares (C-, M-, and X-class). While POD of major flares (M- and X-class) forecasting is 0.96, false alarm rate (FAR) also scores relatively high(0.60). We also present several statistical parameters such as critical success index (CSI) and true skill statistics (TSS). All statistical parameters do not strongly depend on the number of input data sets. Our model can immediately be applied to automatic forecasting service when image data are available.

• Proceedings of the KSRS Conference
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• 2008.10a
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• pp.340-343
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• 2008

The Soya Warm Current (SWC) is a coastal boundary current, which flows along the coast of Hokkaido in the Sea of Okhotsk. Seasonal and subinertial variations in the SWC are investigated using data obtained by high-frequency (HF) ocean radars, coastal tide gauges, and a bottom-mounted acoustic Doppler current profiler (ADCP). The HF radars clearly capture the seasonal variations in the surface current fields of the SWC. The velocity of the SWC reaches its maximum, approximately 1 m/s, in the summer, and becomes weaker in the winter. The velocity core is located 20 to 30 km from the coast, and its width is approximately 50 km. The almost same seasonal cycle was repeated in the period from August 2003 to March 2007. In addition to the annual variation, the SWC exhibits subinertial variations with a period from 10-15 days. The surface transport by the SWC shows a significant correlation with the sea level difference between the Sea of Japan and Sea of Okhotsk for both of the seasonal and subinertial variations, indicating that the SWC is driven by the sea level difference between the two seas. Generation mechanism of the subinertial variation is discussed using wind data from the European Centre for Medium-range Weather Forecasts (ECMWF) analyses. The subinertial variations in the SWC are significantly correlated with the meridional wind component over the region. The subinertial variations in the sea level difference and surface current delay from the meridional wind variations for one or two days. Continental shelf waves triggered by the meridional wind on the east coast of Sakhalin and west coast of Hokkaido are considered to be a possible generation mechanism for the subinertial variations in the SWC.

• Atmosphere
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• v.27 no.1
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• pp.93-104
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• 2017

The effect of Advanced Microwave Sounding Unit-A (AMSU-A) observations on the short-range forecast in East Asia (EA) was investigated for the Northern Hemispheric (NH) summer and winter months, using the Forecast Sensitivity to Observations (FSO) method. For both periods, the contribution of radiosonde (TEMP) to the EA forecast was largest, followed by AIRCRAFT, AMSU-A, Infrared Atmospheric Sounding Interferometer (IASI), and the atmospheric motion vector of Communication, Ocean and Meteorological Satellite (COMS) or Multi-functional Transport Satellite (MTSAT). The contribution of AMSU-A sensor was largely originated from the NOAA 19, NOAA 18, and MetOp-A (NOAA 19 and 18) satellites in the NH summer (winter). The contribution of AMSU-A sensor on the MetOp-A (NOAA 18 and 19) satellites was large at 00 and 12 UTC (06 and 18 UTC) analysis times, which was associated with the scanning track of four satellites. The MetOp-A provided the radiance data over the Korea Peninsula in the morning (08:00~11:30 LST), which was important to the morning forecast. In the NH summer, the channel 5 observations on MetOp-A, NOAA 18, 19 along the seaside (along the ridge of the subtropical high) increased (decreased) the forecast error slightly (largely). In the NH winter, the channel 8 observations on NOAA 18 (NOAA 15 and MetOp-A) over the Eastern China (Tibetan Plateau) decreased (increased) the forecast error. The FSO provides useful information on the effect of each AMSU-A sensor on the EA forecasts, which leads guidance to better use of AMSU-A observations for EA regional numerical weather prediction.

• Atmosphere
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• v.30 no.1
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• pp.1-15
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• 2020

This study analyzed and compared development mechanisms leading to heat waves of 2016 and 2018 in Korea. The European Centre for Medium-Range Weather Forecasts Reanalysis Interim (ERA Interim) dataset and Automated Surface Observing System data are used for synoptic scale analysis. The synoptic conditions are investigated using geopotential height, temperature, equivalent potential temperature, thickness, potential vorticity, omega, outgoing longwave radiation, and blocking index, etc. Heat waves in South Korea occur in relation to Western North Pacific Subtropical High (WNPSH) pressure system which moves northwestward to East Asia during summer season. Especially in 2018, WNPSH intensified due to strong large-scale circulation associated with convective activities in the Philippine Sea, and moved farther north to Korea when compared to 2016. In addition, the Tibetan high near the tropopause settled over Northern China on top of WNPSH creating a very strong anticyclonic structure in the upper-level over the Korean Peninsula. Unlike 2018, WNPSH was weaker and centered over the East China Sea in 2016. Analysis of blocking indices show wide blocking phenomena over the North Pacific and the Eurasian continent during heat wave event in both years. The strong upper-level ridge which was positioned zonally near 60°N, made the WNPSH over the South Korea stagnant in both years. Analysis of heat wave intensity (HWI) and duration (HWD) show that HWI and HWD in 2018 was both strong leading to extreme high temperatures. In 2016 however, HWI was relatively weak compared to HWD. The longevity of HWD is attributed to atmosphere blocking in the surrounding Eurasian continent.

• Journal of Korea Water Resources Association
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• v.37 no.3
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• pp.173-184
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• 2004

The objective of this study is to examine the usefulness of climate model simulations (GCM) in Korea water resource management. The methods are based on probabilistic measures of the effectiveness of GCM simulations of an indicator variable for discriminating high versus low regional observations of a target variable. The formulation uses the significance probability of the Kolmogorov-Smirnov test for detecting differences between two variables. AMIP-II(Atmospheric Model Intercomparison Project-II) type GCM simulation done by ECMWF(European Centre for Medium-Range Weather Forecasts) was used for indicator variable and observed mean average precipitation(MAP) values on 7 major river basins were used as target variable. Monte Carlo simulation is used to establish the significance of the estimator values. The results show that GCM simulations done by ECMWF are skillful in discriminating the high from the low of the observed MAP for wet season in all seven basins of Korea, but not enough for dry season.

• Economic and Environmental Geology
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• v.50 no.5
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• pp.415-422
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• 2017

This study focuses on the sustainable development and intelligence information society, analyzing the results of science and technology forecasts from Korea and Japan for 2040-2050. Future geological environment and disaster technologies are presented, such as base geology, geophysical geological disaster, weather adjustment, $CO_2$ reduction, environmental disaster, and smart ecocity developments. For the future technologies in energy and resources technology, space resources development and nuclear fusion will be realized by 2040 and 2050. Moreover, new material and resource technologies will be applied to replace existing energy and mineral resources by 2040. Japan has introduced intelligent information viewpoints and presented new technologies.

• Atmosphere
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• v.21 no.1
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• pp.85-93
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• 2011

UK Met Office Unified Model (UM) is a grid model applicable for both global and regional model configurations. The Met Office has developed a 4D-Var data assimilation system, which was implemented in the global forecast system on 5 October 2004. In an effort to improve its Numerical Weather Prediction (NWP) system, Korea Meteorological Administration (KMA) has adopted the UM system since 2008. The aim of this study is to provide the basic information on the effects of satellite data assimilation on UM performance by conducting global satellite data denial experiments. Advanced Tiros Operational Vertical Sounder (ATOVS), Infrared Atmospheric Sounding Interferometer (IASI), Special Sensor Microwave Imager Sounder (SSMIS) data, Global Positioning System Radio Occultation (GPSRO) data, Air Craft (CRAFT) data, Atmospheric Infrared Sounder (AIRS) data were assimilated in the UM global system. The contributions of assimilation of each kind of satellite data to improvements in UM performance were evaluated using analysis data of basic variables; geopotential height at 500 hPa, wind speed and temperature at 850 hPa and mean sea level pressure. The statistical verification using Root Mean Square Error (RMSE) showed that most of the satellite data have positive impacts on UM global analysis and forecasts.

• Atmosphere
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• v.27 no.2
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• pp.189-197
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• 2017

Progressing from weather forecasts and warnings to multi-hazard impact-based forecast and warning services represents a paradigm shift in service delivery. Urban flooding is a typical meteorological disaster. This study proposes support plan for urban flooding impact-based forecast by providing inundation risk matrix. To achieve this goal, we first configured storm sewer management model (SWMM) to analyze 1D pipe networks and then grid based inundation analysis model (GIAM) to analyze 2D inundation depth over the Gangnam drainage area with $7.4km^2$. The accuracy of the simulated inundation results for heavy rainfall in 2010 and 2011 are 0.61 and 0.57 in POD index, respectively. 20 inundation scenarios responding on rainfall scenarios with 10~200 mm interval are produced for 60 and 120 minutes of rainfall duration. When the inundation damage thresholds are defined as pre-occurrence stage, occurrence stage to $0.01km^2$, 0.01 to $0.1km^2$, and $0.1km^2$ or more in area with a depth of 0.5 m or more, rainfall thresholds responding on each inundation damage threshold results in: 0 to 20 mm, 20 to 50 mm, 50 to 80 mm, and 80 mm or more in the rainfall duration 60 minutes and 0 to 30 mm, 30 to 70 mm, 70 to 110 mm, and 110 mm or more in the rainfall duration 120 minutes. Rainfall thresholds as a trigger of urban inundation damage can be used to form an inundation risk matrix. It is expected to be used for urban flood impact forecasting.

• Journal of Environmental Impact Assessment
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• v.12 no.1
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• pp.23-34
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• 2003

The emergency response modeling system CARIS has been developed at CCSM (Center for Chemical Safety Management), NIER (National Institute of Environmental Research) to track and predict dispersion of hazardous chemicals for the environmental decision support in case of accidents at chemical or petroleum companies in Korea. The main objective of CARIS is to support making decision by rapidly providing the key information on the efficient emergency response of hazardous chemical accidents for effective approaches to risk management. In particular, the integrated modeling system in CARIS consisting of a real-time numerical weather forecasting model and air pollution dispersion model is supplemented for the diffusion forecasts of hazardous chemicals, covering a wide range of scales and applications for atmospheric information. In this paper, we introduced the overview of components of CARIS and described the operational modeling system and its configurations of coupling/integration in CARIS. Some examples of the operational modeling system is presented and discussed for the real-time risk assessments of hazardous chemicals.

• Journal of Aerospace System Engineering
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• v.13 no.5
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• pp.49-56
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• 2019

The Long-Term Sustainability (LTS) guidelines have attracted the most attention in the recent formation of international norms of behavior regarding outer space activities. The discussion began at the U.N. COPUOS in 2010. In June 2019, the 21 guidelines were finally adopted. The guidelines include international cooperation to promote and support the observation of the situation of orbiting objects, including space debris, for the purpose of preserving the space environment indefinitely, sharing data and forecasts on space weather, and announcing each country's space policy in accordance with international law. Some guidelines have failed to reach a consensus as the mitigation of space debris is often difficult to separate from space weapons tests. As plans for small satellites and Rendezvous and Proximity Operations have been projected for the future, it is expected that each countries' position on preserving the space environment will become more acute.