• New & Renewable Energy
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• v.20 no.1
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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.

• Korean Journal of Remote Sensing
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• v.34 no.3
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• pp.519-533
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• 2018

The sensible heat flux (SHF)and latent heat flux (LHF) over Korean Peninsula ocean during recent 4 years were calculated using Coupled Ocean-Atmosphere Response Experiment (COARE) 3.5 bulk algorithm and satellite-based atmospheric-ocean variables. Among the four input variables (10-m wind speed; U, sea surface temperature; $T_s$, air temperature; $T_a$, and air humidity; $Q_a$) required for heat flux calculation, Ta and $Q_a$, which are not observed directly by satellites, were estimated from empirical relations developed using satellite-based columnar atmospheric water vapor (W) and $T_s$. The estimated satellite-based $T_a$ and $Q_a$ show high correlation coefficients above 0.96 with the buoy observations. The temporal and spatial variability of monthly ocean heat fluxes were analyzed for the Korean Peninsula ocean. The SHF showed low values of $20W/m^2$ over the entire areas from March to August. Particularly, in July, SHF from the atmosphere to the ocean, which is less than $0W/m^2$, has been shown in some areas. The SHF gradually increased from September and reached the maximum value in December. Similarly, The LHF showed low values of $40W/m^2$ from April to July, but it increased rapidly from autumn and was highest in December. The analysis of monthly characteristics of the meteorological variables affecting the heat fluxes revealed that the variation in differences of temperature and humidity between air and sea modulate the SHF and LHF, respectively. In addition, as the sensitivity of SHF and LHF to U increase in winter, it contributed to the highest values of ocean heat fluxes in this season.

• Korean Journal of Agricultural and Forest Meteorology
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• v.14 no.3
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• pp.99-107
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• 2012

There has been increasing number of patients with asthma, rhinitis, and conjunctivitis due to the atmospheric pollution and global warming. In this study, we investigated daily observed number of pollens to establish a standardized method for the impact analysis of the climate changes on the number of daily pollens in Korea. Daily observed allergenic pollens of trees, weeds, and pine were analyzed during the period of 1998 to 2010 (except 2006) in Seoul, Busan, Daegu, Gwangju, Gangneung, and Jeju. They increased in large cities including Seoul during the last 12 years and the long-term trend may continue in the future. Daily concentration or amount of pollens was highly correlated with weather variables. Positive correlation was found between air temperature and the pollens although different relationships existed for different locations. Chill days were utilized to estimate the length of the flowering or pollen period. The pollen period of trees was shorter in the field when the winter temperature was low. This approach may be utilized to determine the quantitative change in length of the pollen season in the future.

• Water Engineering Research
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• v.1 no.1
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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.

• Proceedings of the KSRS Conference
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• 1999.11a
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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.

• Proceedings of the Korea Water Resources Association Conference
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• 2017.05a
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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.

• Journal of Korean Society for Atmospheric Environment
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• v.23 no.3
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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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• v.4 no.3
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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.

• Particle and aerosol research
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• v.7 no.2
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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.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.28 no.2
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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.