• Title/Summary/Keyword: Duration of Sunshine

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Influence of Land Use and Meteorological Factors for Evapotranspiration Estimation in the Coastal Urban Area (해안도시 지역에서 증발산량 산정에 토지이용도와 기상인자의 영향성)

  • Yang, Sung-Il;Kang, Dong-Hwan;Kwon, Byung-Hyuk;Kim, Byung-Woo
    • Journal of Environmental Science International
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    • v.19 no.3
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    • pp.295-304
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    • 2010
  • Actual evapotranspiration (AET) in the Suyeong-gu was estimated and correlations between AET and meteorological factors were analyzed. The study area was Suyeong-gu lay at the east longitude $129^{\circ}$ 05' 40" ~ 129$^{\circ}$ 08' 08" and north latitude $35^{\circ}$ 07' 59" ~ $35^{\circ}$ 11' 01". The Kumryun mountain, the Bae mountain, the Suyeong river and the Suyeong bay are located on west, north, northeaster and south side in the study area, respectively. AET was estimated using precipitation (P), potential evapotranspiration (PET) and plant-available water coefficient. Meteorological factors to estimate PET were air temperature, dewpoint temperature, atmospheric pressure, duration of sunshine and mean wind speed (MWS). PET and AET were estimated by a method of Allen et al. (1998) and Zhang et al. (2001), respectively. PET was the highest value (564.45 mm/yr) in 2002 year, while it was the lowest value (449.95 mm/yr) in 2003 year. AET was estimated highest value (554.14 mm/yr) in 2002 year and lowest value (427.91 mm/yr) in 2003 year. Variations of PET and AET were similar. The linear regression function of AET as PET using monthly data was AET=0.87$\times$PET+3.52 and coefficient of determination was high, 0.75. In order to analyze relationship between the evapotranspiration and meteorological factors, correlation analysis using monthly data were accomplished. Correlation coefficient of AET-PET was 0.96 high, but they of AET-P and PET-P were very low. Correlation coefficients of AET-MWS and PET-MWS were 0.67 and 0.73, respectively. Thus, correlation between evapotranspiration and MWS was the highest among meteorological factors in Suyong-gu. This means that meteorological factor to powerfully effect for the variation of evapotranspiration was MWS. The linear regression function of AET as MWS was AET=84.73$\times$MWS+223.05 and coefficient of determination was 0.54. The linear regression function of PET as MWS was PET=83.83$\times$MWS+203.62 and coefficient of determination was 0.45.

Reference evapotranspiration estimates based on meteorological variables over Korean agro-climatic zones for rice field (남한지역의 논 농업기후지대에 대한 기상자료 기반의 기준 증발산량 추정)

  • Jung, Myung-Pyo;Hur, Jina;Shim, Kyo-Moon;Kim, Yongseok;Kang, Kee-Kyung;Choi, Soon-Kun;Lee, Byeong-Tae
    • Korean Journal of Agricultural and Forest Meteorology
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    • v.21 no.4
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    • pp.229-237
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    • 2019
  • This study was conducted to estimate annual reference evapotranspiration (ET0) for the agro-climatic zones for rice paddy fields in South Korea between 1980 and 2015. The daily ET0 was estimated by applying the Penman-Monteith method to meteorological data from 61 weather stations provided by Korean Meteorological Administration (KMA). The average of annual ET0 from 1980 to 2015 was 1334.1±33.89 mm. The ET0 was the highest at the Southern Coastal Zone due to their higher air temperature and lower relative humidity. The ET0 had significantly increased with 2.81 mm/yr for the whole zones over 36 years. However, the change rate of it was different among agro-climatic zones. The annual ET0 highly increased in central zones and eastern coastal zones. In terms of correlation coefficient, the temporal change of the annual ET0 was closely related to variations of four meteorological factors (i.e., mean, minimum temperatures, sunshine duration, and relative humidity). The results demonstrated that whole Korean agro-climatic zones have been undergoing a significant change in the annual ET0 for the last 36 years. Understanding the spatial pattern and the long-term variation of the annual ET0 associated with global warming would be useful to improve crop and water resource managements at each agro-climatic zone of South Korea.

Analysis of Contribution of Climate and Cultivation Management Variables Affecting Orchardgrass Production (오차드그라스의 생산량에 영향을 미치는 기후 및 재배관리의 기여도 분석)

  • Moonju Kim;Ji Yung Kim;Mu-Hwan Jo;Kyungil Sung
    • Journal of The Korean Society of Grassland and Forage Science
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    • v.43 no.1
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    • pp.1-10
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    • 2023
  • This study aimed to confirm the importance ratio of climate and management variables on production of orchardgrass in Korea (1982-2014). For the climate, the mean temperature in January (MTJ, ℃), lowest temperature in January (LTJ, ℃), growing days 0 to 5 (GD 1, day), growing days 5 to 25 (GD 2, day), Summer depression days (SSD, day), rainfall days (RD, day), accumulated rainfall (AR, mm), and sunshine duration (SD, hr) were considered. For the management, the establishment period (EP, 0-6 years) and number of cutting (NC, 2nd-5th) were measured. The importance ratio on production of orchardgrass was estimated using the neural network model with the perceptron method. It was performed by SPSS 26.0 (IBM Corp., Chicago). As a result, EP was the most important variable (100%), followed by RD (82.0%), AR (79.1%), NC (69.2%), LTJ (66.2%), GD 2 (63.3%), GD 1 (61.6%), SD (58.1%), SSD (50.8%) and MTJ (41.8%). It implies that EP, RD, AR, and NC were more important than others. Since the annual rainfall in Korea is exceed the required amount for the growth and development of orchardgrass, the damage caused by heavy rainfall exceeding the appropriate level could be reduced through drainage management. It means that, when cultivating orchardgrass, factors that can be controlled were relatively important. Although it is difficult to interpret the specific effect of climates on production due to neural networking modeling, in the future, this study is expected to be useful in production prediction and damage estimation by climate change by selecting major factors.

Examining Impact of Weather Factors on Apple Yield (사과생산량에 영향을 미치는 기상요인 분석)

  • Kim, Mi Ri;Kim, Seung Gyu
    • Korean Journal of Agricultural and Forest Meteorology
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    • v.16 no.4
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    • pp.274-284
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    • 2014
  • Crops and varieties are mostly affected by temperature, the amount of precipitation, and duration of sunshine. This study aims to identify the weather factors that directly influence to apple yield among the series of daily measured weather variables during growing seasons. In order to identify them, 1) a priori natural scientific knowledge with respect to the growth stage of apples and 2) pure statistical approaches to minimize bias due to the subject selection of variables are considered. Each result estimated by the Panel regression using fixed/random effect models is evaluated through suitability (i.e., Akaike information criterion and Bayesian information criterion) and predictability (i.e., mean absolute error, root mean square error, mean absolute percentage). The Panel data of apple yield and weather factors are collected from fifteen major producing areas of apples from 2006 to 2013 in Korea for the case study. The result shows that variable selection using factor analysis, which is one of the statistical approaches applied in the analysis, increases predictability and suitability most. It may imply that all the weather factors are important to predict apple yield if statistical problems, such as multicollinearity and lower degree of freedom due to too many explanatory variables used in the regression, can be controlled effectively. This may be because whole growth stages, such as germination, florescence, fruit setting, fatting, ripening, coloring, and harvesting, are affected by weather.

Difference of Growth and Yield among Rice Cultivars and Direct Seeding Methods as Affected by Yearly Variation Weather (연차간 기상조건에 따른 벼 품종의 담수직파재배 양식간 생육 및 수량)

  • Choi, Weon-Young;Kang, Si-Yong;Lee, Jeong-Taek
    • Korean Journal of Environmental Agriculture
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    • v.18 no.3
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    • pp.229-235
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    • 1999
  • To identify the differences on plant growth and yield of two rice cultivars among direct water-seeding methods broadcasting on flooded paddy surface(BF), drilling on flooded paddy surface(DF), and puddled-soil drill seeding(PD) under markedly different weather condition between 1995 and 1996. The mean air temperature for duration from May to June, early growth stage of rice in 1995 was lower $1{\sim}3^{\circ}C$ than that in normal or 1996. In 1995 the respiratory consumption index during panicle formation stage and early ripening stage was higher than those of in 1996 or normal year. Number of seedling stand among the methods of direct seeding rice appeared slightly higher in order of BF>DF>PD. Properly in Nonganbyeo, the number of seedling stand was much low in 1995 compared with in 1996. The leaf area index and shoot dry weight at early growth stage of rice plant and culm length at mature in 1995 were larger in direct water seeding rice than those of machanical transplanting rice, but in 1996. Faster ripening speed and shorter ripening period of rice crop appeared in 1996 compared to in 1995. It was due to higher growing degree-days, sunshine hours and solar radiation during rice growing season in 1996. Dongjinbyeo rice showed higher yield than Nonganbyeo which had lower ripened grains especially in 1995.

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Bayesian structural equation modeling for analysis of climate effect on whole crop barley yield (청보리 생산량의 기후요인 분석을 위한 베이지안 구조방정식 모형)

  • Kim, Moonju;Jeon, Minhee;Sung, Kyung-Il;Kim, Young-Ju
    • The Korean Journal of Applied Statistics
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    • v.29 no.2
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    • pp.331-344
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    • 2016
  • Whole Crop Barley (WCB) is a representative self-sufficient winter annual forage crop, along with Italian Ryegrass (IRG), in Korea. In this study, we examined the path relationship between WCB yield and climate factors such as temperature, precipitation, and sunshine duration using a structural equation model. A Bayesian approach was considered to overcome the limitations of the small WCB sample size. As prior distribution of parameters in Bayesian method, standard normal distribution, the posterior result of structural equation model for WCB, and the posterior result of structural equation model for IRG (which is the most popular winter crop) were used. Also, Heywood case correction in prior distribution was considered to obtain the posterior distribution of parameters; in addition, the best prior to fit the characteristics of winter crops was identified. In our analysis, we found that the best prior was set by using the results of a structural equation model to IRG with Heywood case correction. This result can provide an alternative for research on forage crops that have hard to collect sample data.

Cadmium, Lead, and Zinc Accumulation in Rice Grown at Paddy Soils near Old Zinc-Mining Sites (아연광산(亞鉛鑛山) 인근답(隣近沓)의 토양중(土壤中) 중금속함량(重金屬含量)과 현미중(玄米中) 함량(含量)과의 관계(關係))

  • Yoo, Sun-Ho;Park, Moo-Eon;Ro, Hee-Myoung
    • Korean Journal of Environmental Agriculture
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    • v.2 no.1
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    • pp.18-23
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    • 1983
  • Effect of Cd, Pb, and Zn content in soil on their accumulation in rice was studied by analyzing brown rice(93) and soil samples(180) collected from paddy soils near old zinc-mining sites in 1979 and 1980. Ratio of Cd, Pb, and Zn in brown rice to soil decreased with the increase of their contents in soil and found to be linear function of the inversed values of their contents in soil. Contents of Cd, Pb, and Zn in brown rice harvested in 1980 were lower than those in 1979. The significant difference in contents of Pb and Zn between two years might be attributed to weather. Air temperature and duration of sunshine in 1980 were significantly lower than those in 1979.

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Exploring NDVI Gradient Varying Across Landform and Solar Intensity using GWR: a Case Study of Mt. Geumgang in North Korea (GWR을 활용한 NDVI와 지형·태양광도의 상관성 평가 : 금강산 지역을 사례로)

  • Kim, Jun Woo;Um, Jung Sup
    • Journal of Korean Society for Geospatial Information Science
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    • v.21 no.4
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    • pp.73-81
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    • 2013
  • Ordinary least squares (OLS) regression is the primary statistical method in previous studies for vegetation distribution patterns in relation to landform. However, this global regression lacks the ability to uncover some local-specific relationships and spatial autocorrelation in model residuals. This study employed geographically weighted regression (GWR) to examine the spatially varying relationships between NDVI (Normalized Difference Vegetation Index) patterns and changing trends of landform (elevation, slope) and solar intensity (insolation and duration of sunshine) in Mt Geum-gang of North-Korea. Results denoted that GWR was more powerful than OLS in interpreting relationships between NDVI patterns and landform/solar intensity, since GWR was characterized by higher adjusted R2, and reduced spatial autocorrelations in model residuals. Unlike OLS regression, GWR allowed the coefficients of explanatory variables to differ by locality by giving relatively more weight to NDVI patterns which are affected by local landform and solar factors. The strength of the regression relationships in the GWR increased significantly, by showing regression coefficient of higher than 70% (0.744) in the southern ridge of the experimental area. It is anticipated that this research output will serve to increase the scientific and objective vegetation monitoring in relation to landform and solar intensity by overcoming serious constraints suffered from the past non-GWR-based approach.

A Sub-grid Scale Estimation of Solar Irradiance in North Korea (북한지역 상세격자 디지털 일사량 분포도 제작)

  • Choi, Mi-Hee;Yun, Jin-I.
    • Korean Journal of Agricultural and Forest Meteorology
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    • v.13 no.1
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    • pp.41-46
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    • 2011
  • Reliable information on the surface solar radiation is indispensable for rebuilding food production system in the famine plagued North Korea. However, transfer of the related modeling technology of South Korea is not possible simply because raw data such as solar radiation or sunshine duration are not available. The objective of this study is restoring solar radiation data at 27 synoptic stations in North Korea by using satellite remote sensing data. We derived relationships between MODIS radiation estimates and the observed solar radiation at 18 locations in South Korea. The relationships were used to adjust the MODIS based radiation data and to restore solar radiation data at those pixels corresponding to the 27 North Korean synoptic stations. Inverse distance weighted averaging of the restored solar radiation data resulted in gridded surfaces of monthly solar radiation for 4 decadal periods (1983-1990, 1991-2000 and 2001-2010), respectively. For a direct application of these products, we produced solar irradiance estimates for each sub-grid cell with a 30 m spacing based on a sun-slope geometry. These products are expected to assist planning of the North Korean agriculture and, if combined with the already prepared South Korean data, can be used for climate change impact assessment across the whole Peninsula.

A Study on the Factors Influencing Air Pollutions in the Islands of Korean Peninsula: Focusing on the Case of Ulleung, Jeju, and Baengnyong Island (한반도 도서 지역 대기질 영향요인에 관한 연구 -울릉도, 제주도, 백령도 등을 중심으로)

  • Hwang, Kyu-Won;Kim, Dong-Yeon;Jin, Se-Jun;Kim, Im-Hyeon
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.21 no.11
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    • pp.814-824
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    • 2020
  • Recently, public interest in air pollutants has increased, and the Korean government and local governments have attempted to improve air quality. This study examined the secondary air pollutant contribution in Ulleung Island, Jeju Island, and Baengnyeong Island and compared the differences between them by analyzing the air pollution level and weather conditions in these regions. The weather conditions of the island regions, such as wind speed, precipitation, and sunshine duration, and the average concentration of air pollutants, such as SO2, NO2, CO, O3, PM10, PM2.5, were examined. The correlation coefficient between air quality factors of each island region and weather conditions was calculated. Regression analysis was conducted by setting primary air pollutants, SO2, NO2, and CO as independent variables, and secondary air pollutants, O3, PM10, and PM2.5 as dependent variables to identify the regional contribution and impact. Therefore, the government and local governments should establish air quality management for each island region.