• 신재생에너지
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• 제20권1호
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• pp.102-109
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• 2024

The Typical Meteorological Year (TMY) dataset compiles 12 months of data that best represent long-term climate patterns, focusing on global horizontal irradiance and other weather-related variables. However, the irradiance measured on the plane of the array (POA) shows certain distinct distribution characteristics compared with the irradiance in the TMY dataset, and this may introduce some biases. Our research recalculated POA irradiance using both the Isotropic and DIRINT models, generating an updated dataset that was tailored to POA characteristics. Our analysis showed a 28% change in the selection of typical meteorological months, an 8% increase in average irradiance, and a 40% reduction in the range of irradiance values, thus indicating a significant shift in irradiance distribution patterns. This research aims to inform stakeholders about accurate use of TMY datasets in potential decision-making. These findings underscore the necessity of creating a typical dataset by using the time series of POA irradiance, which represents the orientation in which PV panels will be deployed.

• 대한원격탐사학회지
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• 제34권3호
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• pp.519-533
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• 2018

2014년부터 2017년까지 4년의 기간 동안 COARE 3.5 벌크 알고리즘과 위성 기반의 대기-해양 변수 자료를 이용하여 한반도 주변 해양의 현열 플럭스(Sensible Heat Flux; SHF)와 잠열 플럭스(Latent Heat Flux; LHF)를 $40W/m^2$ 산출하였다. 열 플럭스 산출에 필요한 변수 중 10-m 풍속(U)과 해수면온도($T_s$) 자료는Advanced Microwave Scanning Radiometer 2(AMSR2)와 Global Precipitation Measurement Microwave Imager(GMI) 위성 센서로부터 관측되는 값을 일 평균하여 생성하였으며, 위성으로부터 직접 관측이 되지 않는 대기 온도($T_a$)와 대기 비습($Q_a$)은 위성 기반의 W 및 $T_s$와 갖는 상관성을 이용하여 경험적 통계식을 통해 추정하였다. 추정된 $T_a$와 $Q_a$는 해양 부이에서 관측된 값과 각각 0.96 이상의 높은 상관성을 보였다. 위성 기반으로 관측 및 추정된 대기-해양 변수 자료들을 이용해 한반도 주변 해양(서해, 동해, 남해)의 SHF와 LHF를 산출하였고 월평균 시공간분포의 특성을 확인하였다. SHF는 3월부터 8월까지 한반도 전 해역에 걸쳐 $20W/m^2$의 낮은 값을 보였으며, 특히 7월에는 일부 해양에서 $0W/m^2$ 이하의 낮은 값을 보였다. SHF는 9월부터 점차 증가하여 12월에 가장 높은 값이 나타났다. LHF는 4월부터 7월까지 $40W/m^2$ 정도의 낮은 값을 보이다가 가을철부터 급격히 증가하여 SHF과 마찬가지로 12월에 남해에서 최대 $380W/m^2$ 이상의 높은 값을 보였다. 두 열 플럭스는 모두 쿠로시오 난류가 지나가는 지역에서 연중 높은 값을 나타냈다. 해양 플럭스에 영향을 미치는 대기-해양 변수의 월평균 특성을 분석한 결과 SHF와 LHF는 각각 대기-해양 온도 차이(${\Delta}T$)와 비습 차이(${\Delta}Q$)의 변화에 밀접하게 연관되며, 겨울철에는 U에 대한 민감도가 증가하여 현열 및 잠열 플럭스가 겨울철에 가장 큰 값을 보이는 것에 기여한 것으로 분석된다.

• 한국농림기상학회지
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• 제14권3호
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• pp.99-107
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• 2012

세계적으로 기후변화에 의한 온난화 현상과 대기오염증가와 아울러 알레르기 유발성 꽃가루의 증가로 천식, 비염, 결막염 등 알레르기 질환 환자가 급증하고 있다. 본 연구에서는 꽃가루 농도의 변화에 따른 영향을 체계적으로 표준화하기 위하여 한국의 꽃가루 특성을 분석하였다. 관측된 꽃가루는 1998~2010년(단, 2006년은 제외)의 알레르기를 일으키는 소나무, 수목류(소나무 제외), 잡초류를 서울, 부산, 대구, 광주, 강릉, 제주지역을 중심으로 분석하였다. 꽃가루는 지난 12년간 서울을 포함한 대도시 지역에서는 장기적으로 증가하고 있으며, 앞으로도 장기적으로 증가할 것으로 판단된다. 꽃가루 농도와 기상요소는 매우 높은 상관관계가 있으며 특히 기온과 양의 상관관계를 가진다. 지역별로는 꽃가루 농도와 기상요소는 서로 다른 상관관계를 가진다. 꽃가루농도에 영향을 주는 기상요소 중저온누적도와의 관계를 이용하여 꽃가루 개화기간의 예측식을 도출하였다. 분석결과로부터 수목류의 경우, 충분히 낮은 기온이 만족되면, 개화기간이 줄어드는 결론을 얻었다. 이 모형에 의한 결과로부터 알레르기 유발 꽃가루의 유행시기변화를 생물계절모형으로 예측 가능함을 판단할 수 있다.

• Water Engineering Research
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• 제1권1호
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• pp.25-37
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• 2000

This study presents some results of a preliminary study for the coupled precipitation and river flow prediction system. The model system in based on three numerical models, Mesoscale Atmospheric Simulation model for generating atmospheric variables. Soil-Plant-Snow model for computing interactions within soil-canopy-snow system as well as the energy and water exchange between the atmosphere and underlying surfaces, and TOPMODEL for simulating stream flow, subsurface flow, and water tabled depth in an watershed. The selected study area is the 2,703 $\alpha_4$ $\km_2$ Soyang River basin with outlet at Soyang dam site. In addition to providing the results of rainfall and stream flow predictions, some results of DEM and GIS application are presented. It is obvious that the accurate river flow predictions are highly dependant on the accurate predictation predictions.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 1999년도 Proceedings of International Symposium on Remote Sensing
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• pp.117-121
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• 1999

Relations between GMS-5 infrared brightness temperature with SSM/I retrieved rain rate are determined by a probability matching method similar to Atlas et al. and Crosson et al. For this study, coincident data sets of the GMS-5 infrared measurements and SSM/I data during two summer seasons of 1997 and 1998 are constructed. The cumulative density functions (CDFs) of infrared brightness temperature and rain rate are matched at pairs of two variables which give the same percentile contribution. The method was applied for estimating rain rate on 31 July 1998, examining heavy rainfall estimation of a flash flood event over Mt. Jiri. Results were compared with surface gauge observations run by Korean Meteorological Administration. It was noted that the method produced reasonably good quality of rain estimate, however, there was large area giving false rain due to the anvil type clouds surrounding deep convective clouds. Extensive validation against surface rain observation is currently under investigation.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2017년도 학술발표회
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• pp.183-183
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• 2017

Pan evaporation (Epan) is an important indicator of water and energy balance. Despite global warming, decreasing annual Epan has been reported across different continents over last decades, which is claimed as pan evaporation paradox. However, such trend is not necessarily found in seasonal data because the level of contributions on Epan vary among meteorological components. This study investigates long-term trend in seasonal pan evaporation from 1908 to 2016 across South Korea. Meteorological variables including air temperature (Tair), wind speed (U), vapor pressure deficit (VPD), and solar radiation (Rs) are selected to quantify the effects of individual contributing factor to Epan. We found overall decreasing trend in Epan, which agrees with earlier studies. However, mixed tendencies between seasons due to variation of dominant factor contributing Epan were found. We also evaluated the reference evapotranspiration based on Penman-Monteith method and compared this with Epan to better understand the physics behind the evaporation paradox.

• 한국대기환경학회지
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• 제23권3호
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• pp.364-372
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• 2007

The ozone concentration is one of the important environmental issue for measurement of the atmospheric condition of the country. In this article, two time series ARE models, the direct ARE model and applied ARE model have been considered for analyzing the ozone data at southern part of the Gyeonggi-Do, Pyeongtaek, Osan and Suwon monitoring sites in Korea. The result shows that the direct ARE model is better suited for describing the ozone concentration in all three sites. In both of the ARE models, eight meteorological variables and four pollution variables are used as the explanatory variables. Also the high level of ozone data (over 80 ppb) have been analyzed at the Pyeongtaek, Osan and Suwon monitoring sites.

• Water Engineering Research
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• 제4권3호
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• pp.111-126
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• 2003

Meteorological data are often needed to evaluate the long-term effects of proposed hydrologic changes. The evaluation is frequently undertaken using deterministic mathematical models that require daily weather data as input including precipitation amount, maximum and minimum temperature, relative humidity, solar radiation and wind speed. Stochastic generation of the required weather data offers alternative to the use of observed weather records. The precipitation is modeled by a Markov Chain-exponential model. The other variables are generated by multivariate model with means and standard deviations of the variables conditioned on the wet or dry status of the day as determined by the precipitation model. Ultimately, the objective of this paper is to compare Richardson's model and the improved weather generation model in their ability to provide daily weather data for the crop model to study potential impacts of climate change on the irrigation needs and crop yield. However this paper does not refer to the improved weather generation model and the crop model. The new weather generation model improved will be introduced in the Journal of KWRA.

• 한국입자에어로졸학회지
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• 제7권2호
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• pp.59-68
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• 2011

The objective of the study was to investigate the main factors that contribute the variation of $PM_{10}$ concentration of Seoul and to quantify their effects using generalized additive model (GAM). The analysis was performed with 3 year air pollution data (2004~2006) measured at 27 urban sites and 7 roadside sites in Seoul, a background site in Gangwha and a rural site in Pocheon. The diurnal variation of urban $PM_{10}$ concentrations of Seoul showed a typical bimodal pattern with the same peak times as that of roadside, and the maximum difference of $PM_{10}$ level between urban and roadside was about $14{\mu}g/m^{3}$ at 10 in the morning. The wind direction was found to be a major factor that affects $PM_{10}$ level in all investigated areas. The overall $PM_{10}$ level was reduced when air came from east, but background $PM_{10}$ level in Gangwha was rather higher than the urban $PM_{10}$ level in Seoul, indicating that the $PM_{10}$ level in Gangwha is considerably influenced by that in Seoul metropolitan area. When hourly variations of $PM_{10}$ were analyzed using GAM, wind direction and speed explained about 34% of the variance in the model where the variables were added as a 2-dimensional smoothing function. In addition, other variables, such as diurnal variation, difference of concentrations between roadside and urban area, precipitation, month, and the regression slope of a plot of carbon monooxide versus $PM_{10}$, were found to be major explanatory variables, explaining about 64% of total variance of hourly variations of $PM_{10}$ in Seoul.

• 한국항공운항학회지
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• 제28권2호
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• pp.53-62
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• 2020

This study is to evaluate the accuracy of the meteorological information provided for the aircraft operating at low altitude. At first, it is necessary to identify crucial elements of weather information closely related to flight safety during low altitude flights. The study conducted a survey of pilots of low altitude aircraft, divided into pre-flight and in-flight phases, and reached an opinion that wind direction, wind speed, cloud coverage and ceiling and visibility are important items. Related to these items, we compared and calculated the accuracy of TAFs and METARs from Taean Airfield, Seosan Airport and Gunsan Airport because of their high number of domestic low-altitude flights. Accuracy analysis evaluated the accuracy of two numerical variables, Mean Absolute Error(MAE) and Root Mean Square Error(RMSE), and the cloud coverage which is categorical variable was calculated and compared by accuracy. For numeric variables, one-way ANOVA, which is a parameter-test, was approached to identify differences between actual forecast values and observations based on absolute errors for each item derived from the results of MAE and RMSE accuracy analyses. To determine the satisfaction of both normality assumptions and equivalence variability assumptions, the Shapiro-Wilk test was performed to verify that they do not have a normality distribution for numerical variables, and for the non-parametric test, Kruscal-Wallis test was conducted to determine whether or not they are satisfied.