• Title/Summary/Keyword: Climatic data

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Analysis of the Typical Meteorological Data and the Weighting Factor of TRY (표준기상데이터 형식 분석 및 TRY 가중치 적용)

  • Yoo, Ho-Chun;Lee, Gwan-ho;Park, So-Hee;Kim, Kyoung-Ryul
    • Journal of the Korean Solar Energy Society
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    • v.27 no.4
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    • pp.157-165
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    • 2007
  • Typical meteorological data is fundamental to computer simulation introduced for environment-friendly architecture designs. Therefore, in order to improve accuracy of computer simulation, typical meteorological data should be established. By examining how to choose typical meteorological data, this study selected the optimized weight factor for TRY where weighting factor was not clearly set. As a result, the same weighting factor was applied to each climatic element and TRY data where the weight factor was applied could have the distribution very similar to measurement data. The weighting factor is considered to reflect geographical characteristics of Seoul and applied climatic elements.

Modeling of Daily Reference Evapotranspiration using Polynomial Networks Approach (PNA) (PNA를 이용한 일 기준증발산량의 모형화)

  • Kim, Seong-Won
    • Proceedings of the Korea Water Resources Association Conference
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    • 2011.05a
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    • pp.473-473
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    • 2011
  • Group method of data handling neural networks model (GMDH-NNM) is used to estimate daily reference evapotranspiration (ETo) using limited climatic variables such as max temperature ($T_{max}$), min temperature ($T_{min}$), mean wind speed ($W_{mean}$), mean relative humidity ($RH_{mean}$) and sunshine duration (SD). And, for the performances of GMDH-NNM, it consists of training and test performances, respectively. The training and test performances are carried out using daily time series data, respectively. From this research, we evaluate the impact of GMDH-NNM for the modeling of the nonlinear time series data. We should, thus, construct the credible data of the daily ETo data using GMDH-NNM, and can suggest the methodology for the irrigation and drainage networks system. Furthermore, this research represents that the strong nonlinear relationship such as ETo modeling can be generalized using GMDH-NNM.

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Statistical estimation of crop yields for the Midwestern United States using satellite images, climate datasets, and soil property maps

  • Kim, Nari;Cho, Jaeil;Hong, Sungwook;Ha, Kyung-Ja;Shibasaki, Ryosuke;Lee, Yang-Won
    • Korean Journal of Remote Sensing
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    • v.32 no.4
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    • pp.383-401
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    • 2016
  • In this paper, we described the statistical modeling of crop yields using satellite images, climatic datasets, soil property maps, and fertilizer data for the Midwestern United States during 2001-2012. Satellite images were obtained from the Moderate Resolution Imaging Spectroradiometer (MODIS), and climatic datasets were provided by the Parameter-elevation Regressions on Independent Slopes Model (PRISM) Climate Group. Soil property maps were derived from the Harmonized World Soil Database (HWSD). Our multivariate regression models produced quite good prediction accuracies, with differences of approximately 8-15% from the governmental statistics of corn and soybean yields. The unfavorable conditions of climate and vegetation in 2012 could have resulted in a decrease in yields according to the regression models, but the actual yields were greater than predicted. It can be interpreted that factors other than climate, vegetation, soil, and fertilizer may be involved in the negative biases. Also, we found that soybean yield was more affected by minimum temperature conditions while corn yield was more associated with photosynthetic activities. These two crops can have different potential impacts regarding climate change, and it is important to quantify the degree of the crop sensitivities to climatic variations to help adaptation by humans. Considering the yield decreases during the drought event, we can assume that climatic effect may be stronger than human adaptive capacity. Thus, further studies are demanded particularly by enhancing the data regarding human activities such as tillage, fertilization, irrigation, and comprehensive agricultural technologies.

Causality between climatic and soil factors on Italian ryegrass yield in paddy field via climate and soil big data

  • Kim, Moonju;Peng, Jing-Lun;Sung, Kyungil
    • Journal of Animal Science and Technology
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    • v.61 no.6
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    • pp.324-332
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    • 2019
  • This study aimed to identify the causality between climatic and soil variables affecting the yield of Italian ryegrass (Lolium multiflorum Lam., IRG) in the paddy field by constructing the pathways via structure equation model. The IRG data (n = 133) was collected from the National Agricultural Cooperative Federation (1992-2013). The climatic variables were accumulated temperature, growing days and precipitation amount from the weather information system of Korea Meteorological Administration, and soil variables were effective soil depth, slope, gravel content and drainage class as soil physical properties from the soil information system of Rural Development Administration. In general, IRG cultivation by the rice-rotation system in paddy field is important and unique in East Asia because it contributes to the increase of income by cultivating IRG during agricultural off-season. As a result, the seasonal effects of accumulated temperature and growing days of autumn and next spring were evident, furthermore, autumnal temperature and spring precipitation indirectly influenced yield through spring temperature. The effect of autumnal temperature, spring temperature, spring precipitation and soil physics factors were 0.62, 0.36, 0.23, and 0.16 in order (p < 0.05). Even though the relationship between soil physical and precipitation was not significant, it does not mean there was no association. Because the soil physical variables were categorical, their effects were weakly reflected even with scale adjustment by jitter transformation. We expected that this study could contribute to increasing IRG yield by presenting the causality of climatic and soil factors and could be extended to various factors.

Effect of Climate Change Characteristics on Operation of Water Purification Plant (정수장 운영에 영향을 미치는 기후변화 요인 분석)

  • Youjung Jang;Hyeonwoo Choi;Seojun Lee;Jaeyoung Choi;Hyeonsoo Choi;Heekyong Oh
    • Journal of Korean Society on Water Environment
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    • v.40 no.2
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    • pp.89-100
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    • 2024
  • Climate change has a broad impact on the entire water environment, and this impact is growing. Climate adaptation in water supply systems often involves quantity and quality control, but there has been a lack of research examining the impacts of climatic factors on water supply productivity and operation conditions. Therefore, the present study focused on, first, building a database of climatic factors and water purification operating conditions, and then identifying the correlations between factors to reveal their impacts. News big data was analyzed with keywords of climatic factors and water supply systems in either nationwide or region-wide analyses. Metropolitan area exhibited more issues with cold waves whereas there were more issues with drought in the Southern Chungcheong area. A survey was conducted to seek experts' opinions on the climatic impacts leading to these effects. Pre-chlorination due to drought, high-turbidity of intake water due to rainfall, an increase of toxins in intake water due to heat waves, and low water temperature due to cold waves were expected. Pearson correlation analysis was conducted based on meteorological data and the operating data of a water purification plant. Heavy rain resulted in 13 days of high turbidity, and the subsequent low turbidity conditions required 3 days of high coagulant dosage. This insight is expected to help inform the design of operation manuals for waterworks in response to climate change.

Investigation on the Temperature Characteristics of CWR for the Climate Change (기후변화에 대비한 장대레일 온도특성 연구)

  • Choi, Jin-Yu;Lee, Gyu-Sei;Bae, Hyun-Ung;Park, Beom-Ho;Lim, Nam-Hyoung
    • Journal of the Korean Society for Railway
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    • v.13 no.2
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    • pp.179-185
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    • 2010
  • In order to secure safety for the buckling and fracture of continuous welded rail and improve the efficiency of maintenance work, it is very important that grasp the characteristics of rail temperature. Recently, the maximum air temperature in summer season rises gradually and the minimum air temperature in winter season is decreasing gradually due to the climate change. Therefore, these phenomenon influences in the change amount of yearly rail temperature and can cause change of laying and maintenance temperature. In this study, actual measurement of rail temperature including climatic factors is carried out by constructing the temperature and climate measurement system as realistic as possible. Through the intensive investigation of actual data, it is founded that the existing prediction formulas for rail temperature may be used only in certain climatic conditions (certain combination of climatic factors). It may be more reasonable that the rail temperature considering actual climatic factors in site is predicted on probabilistic approach.

Climate Change Impact Assessment of Abies nephrolepis (Trautv.) Maxim. in Subalpine Ecosystem using Ensemble Habitat Suitability Modeling (서식처 적합모형을 적용한 고산지역 분비나무의 기후변화 영향평가)

  • Choi, Jae-Yong;Lee, Sang-Hyuk
    • Journal of the Korean Society of Environmental Restoration Technology
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    • v.21 no.1
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    • pp.103-118
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    • 2018
  • Ecosystems in subalpine regions are recognized as areas vulnerable to climatic changes because rainfall and the possibility of flora migration are very low due to the characteristics of topography in the regions. In this context, habitat niche was formulated for representative species of arbors in subalpine regions in order to understand the effects of climatic changes on alpine arbor ecosystems. The current potential habitats were modeled as future change areas according to the climatic change scenarios. Based on the growth conditions and environmental characteristics of the habitats, the study was conducted to identify direct and indirect causes affecting the habitat reduction of Abies nephrolepis. Diverse model algorithms for explanation of the relationship between the emergence of biological species and habitat environments were reviewed to construct the environmental data suitable for the six models(GLM, GAM, RF, MaxEnt, ANN, and SVM). Weights determined through TSS were applied to the six models for ensemble in an attempt to minimize the uncertainty of the models. Based on the current climate determined by averaging the climates over the past 30years(1981~2010) and the HadGEM-RA model was applied to fabricate bioclimatic variables for scenarios RCP 4.5 and 8.5 on the near and far future. The results of models of the alpine region tree species studied were put together and evaluated and the results indicated that a total of eight national parks such as Mt. Seorak, Odaesan, and Hallasan would be mainly affected by climatic changes. Changes in the Baekdudaegan reserves were analyzed and in the results, A. nephrolepis was predicted to be affected the most in the RCP8.5. The results of analysis as such are expected to be finally utilizable in the survey of biological species in the Korean peninsula, restoration and conservation strategies considering climatic changes as the analysis identified the degrees of impacts of climatic changes on subalpine region trees in Korean peninsula with very high conservation values.

Estimating the Yield of Potato Non-Mulched Using Climatic Elements (기상자료를 이용한 무피복 재배 감자의 수량 예측)

  • Choi, Sung-Jin;Lee, An-Soo;Jeon, Shin-Jae;Kim, Kyeong-Dae;Seo, Myeong-Cheol;Jung, Woo-Suk;Maeng, Jin-Hee;Kim, In-Jong
    • 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).

Altitudinal patterns and determinants of plant species richness on the Baekdudaegan Mountains, South Korea: common versus rare species

  • Lee, Chang-Bae;Chun, Jung-Hwa;Um, Tae-Won;Cho, Hyun-Je
    • Journal of Ecology and Environment
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    • v.36 no.3
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    • pp.193-204
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    • 2013
  • Altitudinal patterns of plant species richness and the effects of area, the mid-domain effect, climatic variables, net primary productivity and latitude on observed richness patterns along the ridge of the Baekdudaegan Mountains, South Korea were studied. Data were collected from 1,100 plots along a 200 to 1,900 m altitudinal gradient on the ridge. A total of 802 plant species from 97 families and 342 genera were recorded. Common and rare species accounted for 91% and 9%, respectively, of the total plant species. The altitudinal patterns of species richness for total, common and rare plants showed distinctly hump-shaped patterns, although the absolute altitudes of the richness peaks varied somewhat among plant groups. The mid-domain effect was the most powerful explanatory variable for total and common species richness, whereas climatic variables were better predictors for rare plant richness. No effect of latitude on species richness was observed. Our study suggests that the mid-domain effect is a better predictor for wide-ranging species such as common species, whereas climatic variables are more important factors for range-restricted species such as rare species. The mechanisms underlying these richness patterns may reflect fundamental differences in the biology and ecology of different plant groups.

A Study on the Climatic Type in Korea by the Characteristics of Temperature Distribution (기온분포의 특성에 의한 우리나라의 기후형에 관한 연구)

  • 민병언
    • Journal of the Korean Institute of Navigation
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    • v.3 no.1
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    • pp.29-46
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    • 1979
  • The climate of a given region is determined by the combination of the various climatic elements. But among them, the temperature is the most important element to classify the climatic type. The author attempted to classify the climatic types in Korea by making a analysis of the characteristics of temperature distribution. To accomplish the study, the author analyzed the daily and yearly range of temperature, the warmest and coldest months, continentality and oceanicity, thermal anomaly, and relative temperature, etc. The data of 153 weather stations are used for the analysis of the above five criteria. As a result of the study, the climate of Korea can be divided into three types, namely, the continental, coastal and intermediate(or transitional) type. The Pronounced continental type is appeared in the northern part of highland area. And the coastal type is limited to the east and south coast areas, and the southern part of the west coast area. The continentality is larger, and the oceanicity smaller, than those of Siberia, Mongolia and the inland area of China where the continental climate is most remarkable in the world. The reason why the west coast area is more continental than the east coast area may be due to the terrain effect and the warm current going north along the east coastline.

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