• Journal of the Korean Data and Information Science Society
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• 제20권5호
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• pp.765-777
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• 2009

본 연구에서는 대기오염물질 중에서 주목을 받고 있는 분진 직경이 10마이크로미터 (micrometer) 이내의 것을 대상으로 실제로 증가하는지 감소하는지를 알아보기 위하여 교락 요인을 제외한 분진을 대상으로의 순수한 장기 추세를 연구하였다. 자료는 1996년에서 2000년까지 서울시의 기상 변수들 (최대기온, 평균습도, 최대풍속, 일사량)과 27지점에서 얻은 분진 직경이 10마이크로미터 이내의 것을 이용한다. 이 자료를 이용하여 분진과 비선형 관계를 보이는 기상 변수들의 회귀 스플라인을 이용하여 계절성을 통제한 일반화 부가모형을 세웠다. 그 결과 증가가 아닌 감소하는 순수 장기 추세를 얻을 수 있었다.

• Journal of Korean Society for Atmospheric Environment
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• 제10권E호
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• pp.343-356
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• 1994

In this study, a statistical investigation was carried out for the evaluation of any relationship between polycyclic aromatic hydrocarbons (PAHss) associated with ambient aerosols and other air quality parameters under varying meteorological conditions. Daily measurements for PAHs and air quality/meteorological parameters were selected from a data-base constructed by a comprehensive air monitoring in London during 1985-1987. Correlation coefficients were calculated to examine any significant relationship between the PAHs and other individual variables. Statistical analysis was further Performed for the air quality/meteorological data set using a principal component analysis to derive important factors inherent in the interactions among the variables. A total of six components were identified, representing vehicle emission, photochemical activity/volatilization, space heating, atmospheric humidity, atmospheric stability, and wet deposition. It was found from a stepwise multiple regression analysis that the vehicle emission component is overall the most important factor contributing to the variability of PAHs concentrations at the monitoring site. The photochemical activity/volatilzation component appeared to be also an important factor particularly for the lower molecular weight PAHs. In general, the space heating component was found to be next important factor, while the contributions of other three components to the variance of each PAHs did not appear to be as much important as the first three components in most cases. However, a consistency for these components in their negative correlations with PAHs data was found, indicating their roles in the depletion of PAHs concentrations in the urban atmosphere.

• 한국산림과학회지
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• 제57권1호
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• pp.45-51
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• 1982

잣나무의 착과량(着果量)에 미치는 기상환경인자(氣象環境因子)의 영향(影響)을 7개년간(個年間)의 착과량(着果量)과 기상자료간(氣象資料間)의 상관(相關) 및 회귀분석(回歸分析)을 통(通)해 연구(硏究)했다. 잣나무의 착과량(着果量)은 화아분화(花芽分化) 당년(當年) 년평균기온(年平均氣温)이 낮고 화아분화(花芽分化) 전년(前年) 일조량(日照量)과 화아분화전(花芽分化前) 동계기간(冬季期間)의 일조량(日照量)이 많을 때 증가(增加)되었으며 특(特)히 화아분화전(花芽分化前) 6월(月)의 기온(氣溫)이 낮고 강수량(降水量)이 적고 일조량(日照量)이 많을 경우 착과량(着果量)이 많았다.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 1998년도 Proceedings of International Symposium on Remote Sensing
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• pp.37-42
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• 1998

Latent and sensible heat fluxes over the global oceans are estimated using SSM/I (Special Sensor Microwave Imager) and AVHRR MCSST (Advanced Very High Resolution Radiometer Multi-Channel Sea Surface Temperature). The heat fluxes are computed from SSM/I wind speeds and surface humidity, the MCSST, and NCEP Reanalysis sea level pressures and 2-m temperatures from 1996 to 1997. The diabatic conditions bulk formula (Kondo, 1975) is used to compute the heat fluxes. To validate, the derived fluxes are compared to the measurements of 3 JMA buoys. The wind speeds and surface humidity derived from SSM/I have accuracies of 1.37m/s and 1.7g/kg, respectively. The heat fluxes were estimated these factors and the standard error of the latent and sensible heat fluxes are 5.53 W/m$^2$ and 3.33 W/m$^2$. The latest El-Nino phenomenon started at the beginning of 1997 and this event was larger than any others. We compare the heat fluxes in 1997 with the fluxes in 1996 and investigate the spatial movement of meteorological factors as well as the heat fluxes associated with El-Nino appearance.

• 대기
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• 제31권1호
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• pp.73-83
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• 2021

Numerical weather prediction (NWP) models play an essential role in predicting weather factors, but using them is challenging due to various factors. To overcome the difficulties of NWP models, deep learning models have been deployed in weather forecasting by several recent studies. This study adapts long short-term memory (LSTM), which demonstrates remarkable performance in time-series prediction. The combination of LSTM model input of meteorological features and activation functions have a significant impact on the performance therefore, the results from 5 combinations of input features and 4 activation functions are analyzed in 9 Automated Surface Observing System (ASOS) stations corresponding to cities/islands/mountains. The optimized LSTM model produces better performance within eight forecast hours than Local Data Assimilation and Prediction System (LDAPS) operated by Korean meteorological administration. Therefore, this study illustrates that this LSTM model can be usefully applied to very short-term weather forecasting, and further studies about CNN-LSTM model with 2-D spatial convolution neural network (CNN) coupled in LSTM are required for improvement.

• 대기
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• 제16권4호
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• pp.387-393
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• 2006

In this study, journal selection processes of the Science Citation Index (SCI) and the SCOPUS are investigated aiming at making the Journal of the Korean Meteorological Society (JKMS) an SCI journal. In addition, some characteristic features of the SCI journals in the field of atmospheric sciences published in Asian countries are examined. Some domestic journals in the related disciplines that are recently listed in the SCI and SCOPUS are also analyzed in terms of strategic approaches. Results of this study may provide fundamental strategic information in pursuing the JKMS to be listed in the SCI in the near future.

• 대기
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• 제27권3호
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• pp.301-316
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• 2017

This study analyzes the spatio-temporal variability of terrestrial carbon flux and the response of land carbon sink with climate factors to improve of understanding of the variability of land-atmosphere carbon exchanges accurately. The coupled carbon-climate models of CMIP5 (the fifth phase of the Coupled Model Intercomparison Project) and CT (CarbonTracker) are used. The CMIP5 multi-model ensemble mean overestimated the NEP (Net Ecosystem Production) compares to CT and GCP (Global Carbon Project) estimates over the period 2001~2012. Variation of NEP in the CMIP5 ensemble mean is similar to CT, but a couple of models which have fire module without nitrogen cycle module strongly simulate carbon sink in the Africa, Southeast Asia, South America, and some areas of the United States. Result in comparison with climate factor, the NEP is highly affected by temperature and solar radiation in both of CT and CMIP5. Partial correlation between temperature and NEP indicates that the temperature is affecting NEP positively at higher than mid-latitudes in the Northern Hemisphere, but opposite correlation represents at other latitudes in CT and most CMIP5 models. The CMIP5 models except for few models show positive correlation with precipitation at $30^{\circ}N{\sim}90^{\circ}N$, but higher percentage of negative correlation represented at $60^{\circ}S{\sim}30^{\circ}N$ compare to CT. For each season, the correlation between temperature (solar radiation) and NEP in the CMIP5 ensemble mean is similar to that of CT, but overestimated.

• 한국환경과학회지
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• 제20권9호
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• pp.1095-1104
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• 2011

A survey of professionals employed in marine related fields was conducted on subjects related to marine meteorological forecasts and special reports. The outcome of the survey indicated that the respondents were overall satisfied with the determination of the zones related to marine meteorological forecasts and special reports and with the number of forecast factors, but in regards to the questions about specific adjustment methods, it was found that the respondents perceived a need for adjustment. In addition, although there was a high consensus among the respondents that the criteria for watch and warning in the marine special reports were suitable, they voiced the opinion that it will be necessary to implement changes in the current criteria for watch and warning in order to further improve the compatibility of the criteria. The survey found that there was a high level of utilization for the marine meteorological information provided by the Korea Meteorological Administration(KMA), and that respondents mostly acquired this information via internet and TV. On the other hand, however, the satisfaction level regarding the accuracy of the marine meteorological information was low in comparison to the utilization level. The survey regarding areas for improvement in the forecasts and special reports also indicated that the need for 'improvement in the accuracy of forecasts' was cited most frequently.

• International Journal of Contents
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• 제15권4호
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• pp.65-73
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• 2019

Social media is a massive dataset in which individuals' thoughts are freely recorded. So there have been a variety of efforts to analyze it and to understand the social phenomenon. In this study, Twitter was used to define the moments when negative perceptions of the Korean Meteorological Administration (KMA) were displayed and the reasons people were dissatisfied with the KMA. Machine learning methods were used for sentiment analysis to automatically train the implied awareness on Twitter which mentioned the KMA July-October 2011-2014. The trained models were used to validate sentiments on Twitter 2015-2016, and the frequency of negative sentiments was compared with the satisfaction of forecast users. It was found that the frequency of the negative sentiments increased before satisfaction decreased sharply. And the tweet keywords and the news headlines were qualitatively compared to analyze the cause of negative sentiments. As a result, it was revealed that the individual caused the increase in the monthly negative sentiments increase in 2016. This study represents the value of sentiment analysis that can complement user satisfaction surveys. Also, combining Twitter and news headlines provided the idea of analyzing the causes of dissatisfaction that are difficult to identify with only satisfaction surveys. The results contribute to improving user satisfaction with weather services by efficiently managing changes in satisfaction.

• 대기
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• 제31권4호
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• pp.445-459
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• 2021

This study uses a cloud-resolving storm simulator (CReSS) to understand the individual effect of determinant meteorological factors on snowfall characteristics in the Yeongdong region based on the rawinsonde soundings for two snowfall cases that occurred on 23 February (Episode 1) and 13 December (Episode 2) 2016; one has a single-layered cloud and the other has two-layered cloud structure. The observed cloud and precipitation (snow crystal) features were well represented by a CReSS model. The first ideal experiment with a decrease in low-level temperature for Episode 1 indicates that total precipitation amount was decreased by 19% (26~27% in graupel and 53~67% in snow) compared with the control experiment. In the ideal experiment that the upper-level wind direction was changed from westerly to easterly, although total precipitation was decreased for Episode 1, precipitation was intensified over the southwestern side (specifically in terrain experiment) of the sounding point (128.855°E, 37.805°N). In contrast, the precipitation for Episode 2 was increased by 2.3 times greater than the control experiment under terrain condition. The experimental results imply that the low-level temperature and upper-level dynamics could change the location and characteristics of precipitation in the Yeongdong region. However, the difference in precipitation between the single-layered experiment and control (two-layered) experiment for Episode 2 was negligible to attribute it to the effect of upper-level cloud. The current results could be used for the development of guidance of snowfall forecast in this region.