• KOREAN JOURNAL OF CROP SCIENCE
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• v.59 no.1
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• pp.89-96
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• 2014

We aimed to evaluate the effects of climatic elements on potato yield and create a model with climatic elements for estimating the potato yield, using the results of the regional adjustment tests of potato. We used 86 data of the yield data of a potato variety, Sumi, from 17 regions over 11 years. According to the results, the climatic elements showed significant level of correlation coefficient with marketable yield appeared to be almost every climatic elements except wind velocity, which was daily average air temperature (Tave), daily minimum air temperature (Tmin), daily maximum air temperature(Tmax), daily range of air temperature (Tm-m), precipitation (Prec.), relative humidity (R.H.), sunshine hours (S.H.) and days of rain over 0.1 mm (D.R.) depending on the periods of days after planting or before harvest. The correlations between these climatic elements and marketable yield of potato were stepwised using SAS, statistical program, and we selected a model to predict the yield of marketable potato, which was $y=7.820{\times}Tmax_-1-6.315{\times}Prec_-4+128.214{\times}DR_-8+91.762{\times}DR_-3+643.965$. The correlation coefficient between the yield derived from the model and the real yield of marketable yield was 0.588 (DF 85).

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.24 no.8
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• pp.599-604
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• 2012

Most air pollution and smog are a result of the burning of fossil fuels. The use of fossil fuels also causes acid rain and global warming. So the need for solar energy utilization is increased. It is essentially important to make efforts to reduce usage of fossil energy resources. In this study, we analyzed the correlation between climatic elements(Cloud cover, Duration of sunshine, Temperature) and the photovoltaic power generation. Cloud cover of the correlation coefficient was 0.87. And duration of sunshine of the correlation coefficient was 0.93. The order of the correlation coefficient was duration of sunshine, cloud cover, temperature. To accurately analyze of the degree of correlation for the photovoltaic power generation, additional research about climatic elements that show a high correlation is needed.

• Journal of the Korean Solar Energy Society
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• v.32 no.1
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• pp.8-14
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• 2012

Concerning about global warming due to emission of greenhouse effect gas like C02 and depletion of fossil fuels have been spreading. So the need for solar energy utilization is increased. It is essentially important to make efforts to reduce usage of fossil energy resources. In this study, we analyzed the correlation between climatic elements and the photovoltaic power generation. Cloud cover of the correlation coefficient was 0.93. The order of the correlation coefficient was average temperatures, hours of sunshine duration of sunshine and the humidity. To accurately analyze of the degree of correlation for the photovoltaic power generation, additional research about climatic elements that show a high correlation is needed.

• Plant Resources
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• v.6 no.3
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• pp.178-182
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• 2003

This study was conducted to investigate the relationship between yearly variations of climatic elements and yearly variations of productivity in perilla. In addition, correlation coefficients among yield and yield components were estimated. The data of yield and yield components were investigated for 10 years from 1991 to 2000. The meteorological data gathered at the Yeosu Weather Station for the same period were used to find out the relationships between climatic elements and productivity. Yearly variation of the amount of precipitation in September was large with coefficients of variation(c. v.) of 11.1%, but the coefficient of variance(c. v.) in July and August were relative small with 1.8, 2.1%, respectively. Number of cluster per hill and weight of 1,000 grains were greatly with c. v. of 76.1, 79.3%, respectively, but the coefficients of variance(c. v.) of plant height and seed yield were more less with 9.58, 10.60%, respectively. Correlation coefficients between precipitation of September and seed yield were positively significant correlation at the level of 5.1%, respectively, but the duration of sunshine in September and seed yield were negatively significant at the level of 5.1%, respectively. Correlation coefficients of these, the plant height, number of branches per plant, cluster length, number of cluster per hill, weight of 1,000 grains and seed yield were positively significant at the level of 5.1% respectively.

• Plant Resources
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• v.5 no.3
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• pp.196-201
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• 2002

This study was conducted to investigate the relationships between yearly variations of climatic elements and yearly variations of productivity in sesame. In addition, correlation coefficients among yield and yield components were estimated. The data of yield and yield components were investigated for 10 years from 1992 to 2001. The meteorological data gathered at the Yeosu Weather Station for the same period were used to find out the relationships between climatic elements and productivity. Yearly variation of the amount of precipitation in July and September were large with coefficients of variation(c.v.) of 64.59, 92.47%, respectively, but the variation of the average temperature in June and August were relative small. Yield and plant height greatly with c. v. of 26.24, 23.41 %, respectively, 1, 000 grain weights show more or less c.v. of 3.83% and length capsule setting show still less variation. Correlation coefficients between maximun temperature in period of cultivation(from June to September) and yield are positively significant at the level of 5.1 %, respectively. Correlation coefficients amount the plant height, length capsule setting, number of capsules per plant, weight of 1, 000 grains and seed yield were positively significant at the level of 1 %, respectively. Simple linear regression equations by the least square method are estimated for number of capsules per plant(Y$_1$) and the maximun temperature in August(X) as $Y_1$=10.1255+0.1725X, and for yield(Y$_2$) and the maximun temperature in August(X) as $Y_2$=21.6151 + 1.3724X.

• Journal of Korea Water Resources Association
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• v.47 no.11
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• pp.1039-1050
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• 2014

The goal of this study is to demonstrate the diversity of model performance for various climatic elements and indicators. We evaluated the skills of the most advanced 17 General Circulation Models (GCMs) i.e., CMIP5 (Climate Model Inter-comparison project, phase 5) climate models in reproducing retrospective climatology from 1950 to 2000 over the Southeast US for the key climatic elements important in the hydrological and agricultural perspectives (i.e., precipitation, maximum and minimum temperature, and wind speed). The biases of raw CMIP5 GCMs were estimated for 16 different climatic indicators that imply mean climatology, temporal variability, extreme frequency, etc. using a grid-based observational dataset as reference. Based on the error (RMSE) and correlation (R) of GCM outputs, the error-based GCM ranks were assigned on average over the indicators. Overall, the GCMs showed much better accuracy in representing mean climatology of temperature comparing to other elements whereas few GCM showed acceptable skills for precipitation. It was also found that the model skills and ranks would be substantially different by the climatic elements, error statistics applied for evaluation, and indicators as well. This study presents significance of GCM uncertainty and the needs of considering rational strategies for climate model evaluation and selection.

• Journal of the Korean Geographical Society
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• v.33 no.1
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• pp.17-40
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• 1998

The purpose of this study is to classify climatic environment according to its characteristics in Korea using GIS. The necessary condition of climatic division is that it is able to indicate climatic phenomena systematically and it has scientific persuasive power. Precipitaiton, rainfall days, temperature and weather entropy which are consist of Korean climatic elements are of advantage to indicate climatic phenomena systematically. GIS(Geographic Information System)has scientific persuasive power. This paper shows the time-spatial variations of each climatic elements, using GIS to precipitation, rainfall days, Temperature and weather entropy in Korea. And writers tried to know these regional characteristics and to divide the detailed climatic environment objectively and systematically. The main result of this study is that the regional division of climatic environment in Korea can be classified into 8 types, in details, 26 or 48 types.

• Journal of the Korean Geographical Society
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• v.36
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• pp.13-25
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• 1987

이 글에서는 다음의 내용을 다루었다. 1. 주성분분석의 결과 및 고찰 2. 기후구분

• Plant Resources
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• v.6 no.3
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• pp.159-164
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• 2003

This study was conducted to investigate the relationship between yearly variations of climatic elements and yearly variations of productivity in malting barley. In addition, correlation coefficients among yield and yield components were estimated. The data of yield and yield components were investigated for 10 years from 1991 to 2000. The meteorological data gathered at the Yeosu Weather Station for the same period were used to find out the relationships between climatic elements and productivity. Yearly varation of the amount of precipitation in December and January were large with coefficients of variation(c. v.) of 97.9, 51.3%, respectively, but the variation of the maximum temperature and minimum temperature in April were relative small. Yield, weight of 1,000 grains and culm length were greatly with c. v. of 37.3, 49.3 and 41.3%, respectively. spike length and number of spikes show more or less c. v. of 3.8, 24.7% respectively and number of grains per spike show still less variation with c. v. of 9.4%. Correlation coefficients between temperature of mean, maximum and minimum in February and seed yield and yield components were positively significant at level of 5.1%, respectively. Correlation coefficients between precipitation of April and seed yield were positively significant correlation at the level of 5.1 %, respectively, but the duration of sunshine in April and seed yield were negatively significant at the level of 5.1%, respectively. Correlation coefficients of those, yield components and yield, culm length, spike length, number of grains per spike, number of spikes per $m^2$, weight of 1,000 grains and seed yield were positively significant at the level of 5.1 % respectively.

• Proceedings of the Plant Resources Society of Korea Conference
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• 2000.05a
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• pp.26-33
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• 2000

This study was conducted to investigate the relationships between yearly variations of elimatic elements and yearly variations of productivity in potato. In addition, correlation coefficients among yield and yield components were estimated. The data of yield and yield components were investigated for 9 years from 1987 to 1995. The meteorological data what gathered at the Goheung Weather Station for the same period of crop growing season were used to find out the relationships between climatic elements and crop productivity. Yearly variation of the daily minimum temperature in March and April were large with coefficients of variation (C.V.) of 126.0%, 368%, respectively, but the variation of the daily mean and maximum temperature in May and June were relative small. Stem length and number of stem show more C.V. of 9.3%, 14.3%, respectively, but the variation of the yield was relative small with 3.7%. Correlation coefficients between the amount of precipitation in April and yield, yield and daily mean temperature in June were negatively significant at the level of 5, 1 %, respectively. Correlation coefficients between the growth habits and yield are positively significant at the level of 5, 1 %, respectively. Simple linear regression equations by the least square method are estimated for stem length (Yl) and the precipitation in April(X) as Y,=82.47-0.11x (R2=0.3959), and for yield(Y2) and the precipitation in April(X) as Y,=2003.61-0.94X (R2=0.5418).