• Journal of Information Processing Systems
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• v.11 no.1
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• pp.134-147
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• 2015

This paper presents the applications of Kriging spatial interpolation methods for meteorologic variables, including temperature and relative humidity, in regions of Vietnam. Three types of interpolation methods are used, which are as follows: Ordinary Kriging, Universal Kriging, and Universal Kriging plus Digital Elevation model correction. The input meteorologic data was collected from 98 ground weather stations throughout Vietnam and the outputs were interpolated temperature and relative humidity gridded fields, along with their error maps. The experimental results showed that Universal Kriging plus the digital elevation model correction method outperformed the two other methods when applied to temperature. The interpolation effectiveness of Ordinary Kriging and Universal Kriging were almost the same when applied to both temperature and relative humidity.

• Journal of Environmental Science International
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• v.24 no.8
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• pp.993-1001
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• 2015

Comparing to the other air pollutants like $SO_2$, CO, the number of exceedance of the ozone national ambient air quality standard(NAAQS) and the ozone warning increased recently in Busan. The purpose of this study is to find out the preliminary symptoms for high ozone days in Busan area. In order to find out the preliminary symptoms, the hourly ozone data at air quality monitoring stations and the hourly meterological parameters at Busan regional meteorological 2007 to 2013 were used for the analysis. Averaged daily max ozone concentration was the highest(0.055 ppm) at Noksan and Youngsuri in the ozone season from 2007 to 2013. The horizontal distributions of daily max. ozone including all stations in Busan at high ozone days(the day exceeding 0.1 ppm of ozone concentration at least one station) were classified from two to five clusters by hierarchial cluster analysis. The meteorological variables showing strong correlation with daily max. ozone were the daily mean dew point temperature, averaged total insolation, the daily mean relative humidity and the daily mean cloud amount. And the most frequent levels were $19-23^{\circ}C$ in dew point temperature, $21-24 MJ/m^2$ in total insolation on the day before, $2.6-3.0 MJ/m^2$ on the very day, 67-80% in relative humidity and 0-3 in cloud amount.

• The Journal of Fisheries Business Administration
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• v.52 no.2
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• pp.55-67
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• 2021

Global warming affects critical natural resources, one of which is the oceans that occupy 70% of the total cover of the earth. In other words, ocean warming is a subset of global warming which needs to be addressed urgently. Purple laver (pyropia spp.) is one of the most vulnerable items to climate change although it is a major export product of Korean fisheries. The purpose of this study is to analyze the causality of how climate change caused by global warming affects the increase or decrease of PLP (purple laver production). The target area for analysis was set to Maro-hae between Jindo-gun and Haenam-gun. We selected marine environmental factors and meteorologic factors that could affect PLP as variables, as well as co-integration tests to determine long-term balance, and the Granger causticity tests. As a result, PLP and marine environmental factors WT (water temperature), pH, and DO confirmed that long-term equilibrium relationships were established, respectively. However, there is only causality with WT and it is confirmed that there is only a correlation between pH and DO (dissolved oxygen). There was no long-term equilibrium relationship between PLP and HDD (heating degree days) and there is a causal effect that HDD affects PLP; however, it was less clear than that of WT. The relationship between PLP and RF (rainfall), WS (wind speed), SS (percentage of sunshine), and FF (farm facilities) was all balanced in the long term, and causality exists. Based on the results of the analysis, policy proposals were made.

• Journal of Korea Water Resources Association
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• v.36 no.3 s.134
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• pp.345-363
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• 2003

From the General Circulation Models(GCMs), it is known that the increases of concentrations of greenhouse gases will have significant implications for climate change in global and regional scales. The GCM has an uncertainty in analyzing the meteorologic processes at individual sites and so the 'downscaling' techniques are used to bridge the spatial and temporal resolution gaps between what, at present, climate modellers can provide and what impact assessors require. This paper describes a method for assessing local climate change impacts using a robust statistical downscaling technique. The method facilitates the rapid development of multiple, low-cost, single-site scenarios of daily surface weather variables under current and future regional climate forcing. The construction of climate change scenarios based on spatial regression(transfer function) downscaling and on the use of a local stochastic weather generator is described. Regression downscaling translates the GCM grid-box predictions with coarse resolution of climate change to site-specific values and the values were then used to perturb the parameters of the stochastic weather generator in order to simulate site-specific daily weather values. In this study, the global climate change scenarios are constructed using the YONU GCM control run and transient experiments.