• The Journal of the Korea institute of electronic communication sciences
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• v.14 no.6
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• pp.1161-1170
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• 2019

In this study, we propose a model for predicting Cochlodinium polykrikoides red tide occurrence using deep neural networks. A deep neural network with eight hidden layers was constructed to predict red tide occurrence. The 59 marine and meteorological factors were extracted and used for neural network model training using satellite reanalysis data and meteorological model data. The red tide occurred in the entire dataset is very small compared to the case of no red tide, resulting in an unbalanced data problem. In this study, we applied over sampling with adding noise based data augmentation to solve this problem. As a result of evaluating the accuracy of the model using test data, the accuracy was about 97%.

• Journal of the Korean earth science society
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• v.31 no.5
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• pp.475-487
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• 2010

Sea surface wind field was retrieved from high-resolution SIR-C SAR data by using CMOD algorithms off the east coast of Korea. In order to extract wind direction information from SAR data, a two-dimensional spectral analysis method was applied to the normalized radar cross section of the image. An $180^{\circ}$-ambiguity problem in the determination of wind direction was solved by selecting a direction nearest to the wind vector of the ECMWF reanalysis data. Comparison of the wind retrieval patterns with the ECMWF and NCEP/NCAR dataset showed RMS errors in the range of 1.30 to $1.72\;ms^{-1}$. In contrast, comparison of wind directions revealed large errors of greater than $60^{\circ}$, which is enormously higher than the permitted limit of about $20^{\circ}$ for satellite scatterometer winds. Compared with wind speed results from different algorithms, wind vectors based on commonly-used CMOD4 algorithm showed good agreement with those derived by other algorithms such as CMOD_IFR2 and CMOD5, particularly at medium winds from 4 to $8\;ms^{-1}$. However, apparent discrepancy appeared at low winds (< $4\;ms^{-1}$). This study also addressed an importance of accurate wind direction data to improve the accuracy of wind speed retrieval and discussed potential causes of wind retrieval errors from SAR data.

• Korean Journal of Remote Sensing
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• v.36 no.4
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• pp.587-607
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• 2020

Soil moisture is essential information for meteorological and hydrological analyses. To date, many efforts have been made to achieve the two goals for soil moisture data, i.e., the improvement of accuracy and resolution, which is very challenging. We presented an ensemble downscaling method for quality improvement of gridded soil moisture data in terms of the accuracy and the spatial resolution by the integration of BMA (Bayesian model averaging) and ATPRK (area-to-point regression kriging). In the experiments, the BMA ensemble showed a 22% better accuracy than the data sets from ESA CCI (European Space Agency-Climate Change Initiative), ERA5 (ECMWF Reanalysis 5), and GLDAS (Global Land Data Assimilation System) in terms of RMSE (root mean square error). Also, the ATPRK downscaling could enhance the spatial resolution from 0.25° to 0.05° while preserving the improved accuracy and the spatial pattern of the BMA ensemble, without under- or over-estimation. The quality-improved data sets can contribute to a variety of local and regional applications related to soil moisture, such as agriculture, forest, hydrology, and meteorology. Because the ensemble downscaling method can be applied to the other land surface variables such as temperature, humidity, precipitation, and evapotranspiration, it can be a viable option to complement the accuracy and the spatial resolution of satellite images and numerical models.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.36 no.3
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• pp.241-248
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• 2023

The value of experimentally obtained data becomes highest when they are properly analyzed based on valid logics. Many physical and chemical properties such as electrical and magnetic properties, chemical reaction rates, etc. are known to be thermally activated; thus, a proper understanding of thermally-activated processes is of importance. However, there are still a number of papers published with falsely analyzed data. In this contribution, we would like to revisit the meaning of thermally-activated processes, and then reanalyze a data set published misinterpreted. By showing a step-by-step procedure for the reanalysis, we would like to help researchers who may come across such data in the future not to make mistakes in their analysis.

• Journal of Environmental Science International
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• v.25 no.7
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• pp.1029-1042
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• 2016

The initial and boundary conditions are important factors in regional chemical transport modeling systems. The method of generating the chemical boundary conditions for regional air quality models tends to be different from the dynamically varying boundary conditions in global chemical transport models. In this study, the impact of real time Copernicus atmosphere monitoring service (CAMS) re-analysis data from the modeling atmospheric composition and climate project interim implementation (MACC) on the regional air quality in the Korean Peninsula was carried out using the community multi-scale air quality modeling system (CMAQ). A comparison between conventional global data and CAMS for numerical assessments was also conducted. Although the horizontal resolution of the CAMS re-analysis data is not higher than the conventionally provided data, the simulated particulate matter (PM) concentrations with boundary conditions for CAMS re-analysis is more reasonable than any other data, and the estimation accuracy over the entire Korean peninsula, including the Seoul and Daegu metropolitan areas, was improved. Although an inland area such as the Daegu metropolitan area often has large uncertainty in PM prediction, the level of improvement in the prediction for the Daegu metropolitan area is higher than in the coastal area of the western part of the Korean peninsula.

• Women's Health Nursing
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• v.5 no.3
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• pp.349-361
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• 1999

This study is designed to describe and analyze the experiences of hysterectomy. It also attempts to develop the practical theory of their experiences and thus suggest a fundamental frame that can help nurses broaden their clinical understanding of hysterectomy patients and take better care. The data was collected through interviewing the selected subjects. The subjects were five hysterectomy patients. They were interviewed at first hand by this researcher and recorded under their permissions. Each interview took one hour or two hours per interviewer. The data was collected through the interview. The method of "the Ground Theory" by Strauss & Corbin (1990) was used for data analysis. A total of 129 concepts were extracted from the data analysis. which were classified into 27 subcategories through reanalysis. The subcategories were grouped under 12 higher categories. During the process of the data analysis the following three propositions repeatedly appeared. (1) The higher importance of sexual life and pregnancy, the greater the patients' despair. The support system was not satisfied. The closed defense intensified their despair. They felt that the operation result was out of control. (2) The lower the importance of sexual life and pregnancy, the lesser the patients' despair. The support system proved to be highly satisfactory. As a result more favorably. (3) The lower physical change, the lesser importance of pregnancy. the lesser the patients' despair, the patients' thought turned out to be more positive, which, in turn, left the patients the less despaired. As a results the patients accept the operation result more favorably.

• The Korean Journal of Applied Statistics
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• v.21 no.4
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• pp.705-716
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• 2008

The objectives of this study are the detection and forecast of climate change signal in the annual mean of surface temperature data, which are generated by MRI/JMA CGCM over the Korean Peninsula. MRI/JMA CGCM outputs consist of control run data(experiment with no change of $CO_2$ concentration) and scenario run data($CO_2$ 1%/year increase experiment to quadrupling) during 142 years for surface temperature and precipitation. And ECMWF reanalysis data during 43 years are used as observations. All data have the same spatial structure which consists of 42 grid points. Two statistical models, the Bayesian fingerprint method and the regression model with autoregressive error(AUTOREG model), are separately applied to detect the climate change signal. The forecasts up to 2100 are generated by the estimated AUTOREG model only for detected grid points.

• Journal of the Korean earth science society
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• v.44 no.2
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• pp.119-134
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• 2023

The synoptic, thermodynamic, and dynamic characteristics of a snowfall event that occurred in the Yeongdong region on March 1-2, 2021, were investigated. Surface weather charts, ERA5 reanalysis data, rawinsonde data, GK-2A satellite data, and WISSDOM data were used for analysis. The snow depth, exceeding 10 cm, was observed at four weather stations during the analysis period. The maximum snow depth (37.4 cm) occurred at Bukgangneung. According to the analysis of the weather charts, old and dry air was trapped within relatively warm, humid air in the upper atmosphere over the East Sea and adjacent Yeongdong region. This caused unstable atmospheric conditions that led to developing convective clouds and snowfall over Bukgangneung. In particular, based on the thermodynamic and kinematic vertical analysis, we suggest that strong winds attributable to the vertical gradient of potential temperature in the low layer and the development of convective instability due to cold advection played a significant role in the occurrence of snowfall in the Yeongdong region. These results were confirmed from the vertical analysis of the rawinsonde data.

• Proceedings of the KSRS Conference
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• 2004.10a
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• pp.192-195
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• 2004

Products of gridded surface wind and windstress vectors over the world ocean have been constructed by satellite scatterometer data with highly temporal and spatial resolutions. Even if the ADEOS-II/SeaWinds has supplied surface wind data only for short duration in Apr. to Oct. 2003 to us, it permits us to construct a product with higher resolution together with the Qscat/SeaWinds. In addition to our basic product with its resolution of $1^{\circ}\times1^{\circ}$ in space and daily in time, we try to construct products with $1/2^{\circ}\times1/2^{\circ}$ and semi- and quarter-daily resolution. These products are validated by inter-comparison with in-situ data (TAO and NDBC buoys), and also compared with numerical weather prediction(NWP) ones (NCEP reanalysis). Result reveals that our product has higher reliability in the study area than the NCEP's. For the open ocean regions in the middle and high latitudes where there are no in-situ data, we find that there are clear differences between them. Especially in the southern westerly region of 400-600S, the' wind-stress magnitudes by the NCEP are significantly larger than the others, suggesting that they are overestimated. We also calculate wind-stress curl field that is an important factor for ocean dynamics and focus its spatial character in the northwestern Pacific around Japan. Positive curl areas are found to cover from southwest to northeast in our focus region and almost correspond to the Kuroshio path. It is suggested that the vorticity field in the lower atmosphere is related to the upper oceanic one, and thus an aspect of air-sea interaction process.

• Korean Journal of Remote Sensing
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• v.19 no.3
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• pp.223-231
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• 2003

With the negative influences and damage from Asian dust increasing, it's getting important to investigate the climate and soil condition of the source region of Asian dust. There is a high possibility that the desertification and the drastic decrease of plants in China and Mongolia make worse the situation (bad effects of Asian Dust). To detect the movement of Asian dust caused by air circulation, we need to watch the state of the source region to get useful information for the prevention of the dust pollution, and to predict what part of China will become the source region. Therefore, using TOMS aerosol index data, NCEP reanalysis data that is Remote Sensing data from 1981 to 2000 (except 1993~1996, 4 years), for 16 years, examined the relation between the dust occurrence and weather elements. Dust occurrence appeared much in spring season from March to May in study areas. It had a dry climate during that season as follows : relative humidity about 20~40%, temperature about -5~5$^{\circ}C$, precipitation about 33-180 mm, wind speed about 4-10 ms-1. Dust occurrence and weather element annual change in study areas decreased gradually till 1990, but in Gobi desert the incidence of dust occurrence increased since 1997. As a result, found out that the more the precipitation, the less dust occurrence, because the precipitation and surface wind speed had a direct influence on the soil of the source region of dust.