• Journal of Korean Society of Forest Science
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• v.86 no.1
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• pp.25-34
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• 1997

The optimum global natural vegetation mapping(GNVM) system was selected as a series of the study to estimate potential forest area of the globe. To select the system, three types of GNVM systems which are simple system with Light Climatic Dataset(LCD), altitude-allowed system with LCD and altitude-allowed system with Heavy Climatic Dataset(HCD) were established and compared. The three GNVM systems spherically interpolate such spotty climate data as those observed at weather stations the world over onto $1^{\circ}{\times}1^{\circ}$ grid points, product vegetation type classification, and produce a potential natural vegetation(PNV) map and a PNV area. As a result of comparison with three GNVM systems, altitude-allowed LCD system represented natural vegetation distribution better than other versions. The difference between the simple system versus the one with altitude allowance indicated that the simple version tends to over-represent the warmer climate areas and under-represent cold and hostile climate areas. In the difference between altitude-allowed versions of LCD and HCD, HCD version tended to overestimate moist climate areas and to underestimate dry climate areas.

• Journal of the Korean Geographical Society
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• v.50 no.1
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• pp.1-21
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• 2015

The present study aims to characterize the synoptic climatic patterns of winter extreme low temperature events occurred in different regions of Korea based on daily temperature data observed at 61 weather stations under the supervision of the Korea Meteorological Administation and NCEP/NCAR reanalysis I data for the recent 40 years (1973~2012) period. Analyses of daily maximum and minimum temperatures below 10th percentile thresholds show that high frequencies of winter extreme low temperature events appear across the entire regions of Korea or in either the western or eastern half region divided by major mountain ridges at the 2~7 dayintervals particularly in the first half of the winter period (before mid-January). Composite analyses of surface synoptic climatic data including sea level pressure and wind vector reveal that 13 regional types of winter extreme low temperature events in Korea are closely associated with the relative location and intensity of both the Siberian high pressure and the Aleutian low pressure systems as well as major mountain ridges. Investigations of mid-troposphere (500 hPa) synoptic climatic charts demonstrate that the blocking-like upper troposphere low pressure system advecting the cold air from the Arctic toward the Korean Peninsula may provide favorable synoptic conditions for the outbreaks of winter extreme low temperature events in Korea. These results indicate that the monitoring of synoptic scale climatic systems in East Asia including the Siberian high pressure system, the Aleutian low pressure system and upper level blocking system is critical to the improvement of the predictability of winter extreme low temperature events in Korea.

• Korean Journal of Remote Sensing
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• v.15 no.1
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• pp.9-20
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• 1999

The use of climatic information is essential in the industial society. More specialized weather servies are required to perform better industrial acivities including agriculture. Especially, crop models require daily weather data of crop growing area or cropping zones, where routine weather observations are rare. Estimates of the spatial distribution of daily climates might complement the low density of standard weather observation stations. This study was conducted to estimate the spatial distribution of daily minimum and maximum temperatures in Korean Peninsula. A topoclimatological technique was first applied to produce reasonable estimates of monthly climatic normals based on 1km $\times$ 1km grid cell over study area. Harmonic analysis method was then adopted to convert the monthly climatic normals into daily climatic normals. The daily temperatures for each grid cell were derived from a spatial interpolation procedure based on inverse-distance weighting of the observed deviation from the climatic normals at the nearest 4 standard weather stations. Data collected from more than 300 automatic weather systems were then used to validate the final estimates on several dates in 1997. Final step to confirm accuracy of the estimated temperature fields was comparing the distribution pattern with the brightness temperature fields derived from NOAA/AVHRR. Results show that differences between the estimated and the observed temperatures at 20 randomly selected automatic weather systems(AWS) range from -3.$0^{\circ}C$ to + 2.5$^{\circ}C$ in daily maximum, and from -1.8$^{\circ}C$ to + 2.2$^{\circ}C$ in daily minimum temperature. The estimation errors, RMSE, calculated from the data collected at about 300 AWS range from $1.5^{\circ}C$ to 2.5$^{\circ}C$ for daily maximum/minimum temperatures.

• KIEAE Journal
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• v.7 no.6
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• pp.23-28
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• 2007

Limited fossil fuels and unstable energy supply are considered as one of the critical problems in architecture requiring large amounts of energy. In order to this challenge, environment-friendly architecture design is required. Clear data should be prepared to apply solar energy to architecture aggressively and properly. This study used FS statistical analysis data regarding average daily solar radiation of Seoul observed over 20 years to find out standard year and standard daily solar radiation. This study also aims to compare and evaluate an appropriate method of selecting a standard year which is too close to measurement value through comparison and analysis with daily solar radiation acquired by applying overseas researchers' suggesting weight factor. As a result, the data nearest to measurement value of daily solar radiation was UK CIBSE TRY(TYPE 2) displaying 0.100in t-statistic index. For UK CIBSE TRY(TYPE 2), weight factor was applied to three climatic elements except relative humidity. TYPE 1 and TYPE 3 recorded 0.343 and 0.367, respectively, showing higher record of t-statistic than TYPE 2. TYPE 1 was calculated through FS statistical value of single data about daily solar radiation with other climatic elements excluded. For TYPE 3, relative humidity was added to TYPE 2. In particular, since TYPE 2 was closer to the measurement value compared to the others, it is necessary to consider relationship with other climate elements if other climate elements are added.

• Korean Journal of Agricultural and Forest Meteorology
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• v.17 no.2
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• pp.102-107
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• 2015

This study was conducted to classify agro-climatic zones in Northeast district of China. For agro-climatic zoning, monthly mean temperature and precipitation data from Global Modeling and Assimilation Office (GMAO) of National Aeronautics and Space Administration (NASA, USA) between 1979 and 2010 (http://disc.sci.gsfc.nasa.gov/) were collected. Altitude and vegetation fraction of East Asia from Weather Research and Forecasting (WRF) were also used to classify them. The criteria of agro-climatic classification were altitude (200 m, between 200-800 m, 800 m), vegetation fraction (60%), annual mean temperature ($0^{\circ}C$), temperature in the hottest month ($22^{\circ}C$), and annual precipitation (700 mm). In Northeast district of China, mean annual temperature, annual precipitation, and solar radiation were $3.4^{\circ}C$, 613.2 mm, and $4,414.2MJ/m^2$ between 2009 and 2013, respectively. Twenty-two agro-climatic zones identified in Northeast district of China by metrics classification method, from which the map of agro-climatic zones for Northeast district of China was derived. The results could be useful as information for estimating agro-meteorological characteristics and predicting crop development and crop yield of Northeast district of China as well as those of North Korea.

• Korean Journal of Environmental Agriculture
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• v.38 no.1
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• pp.34-37
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• 2019

BACKGROUND: A region can be divided into agroclimatic zones based on homogeneity in weather variables that have greatest influence on crop growth and yield. The agro-climatic zone has been used to identify yield variability and limiting factors for crop growth. This study was conducted to classify agro-climatic zones in the state of Mato Grosso in Brazil for predicting crop productivity and assessing crop suitability etc. METHODS AND RESULTS: For agro-climatic zonation, monthly mean temperature, precipitation, and solar radiation data from Global Modeling and Assimilation Office (GMAO) of National Aeronautics and Space Administration (NASA, USA) between 1980 and 2010 were collected. Altitude and vegetation fraction of Brazil from Weather Research and Forecasting (WRF) were also used to classify them. The criteria of agro-climatic classification were temperature in the hottest month ($30^{\circ}C$), annual precipitation (600 mm and 1000 mm), and altitude (200 m and 500 m). The state of Mato Gross in Brazil was divided into 9 agro-climatic zones according to these criteria by using matrix classification method. CONCLUSION: The results could be useful as information for estimating agro-meteorological characteristics and predicting crop development and crop yield in the state of Mato Grosso in Brazil.

• Korean Journal of Agricultural and Forest Meteorology
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• v.17 no.2
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• pp.108-125
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• 2015

The agro-climatic index is one of the ways to assess the climate resources of particular agricultural areas on the prospect of agricultural production; it can be a key indicator of agricultural productivity by providing the basic information required for the implementation of different and various farming techniques and practicalities to estimate the growth and yield of crops from the climate resources such as air temperature, solar radiation, and precipitation. However, the agro-climate index can always be changed since the index is not the absolute. Recently, many studies which consider uncertainty of future climate change have been actively conducted using multi-model ensemble (MME) approach by developing and improving dynamic and statistical downscaling of Global Climate Model (GCM) output. In this study, the agro-climatic index of Korean Peninsula, such as growing degree day based on $5^{\circ}C$, plant period based on $5^{\circ}C$, crop period based on $10^{\circ}C$, and frost free day were calculated for assessment of the spatio-temporal variations and uncertainties of the indices according to climate change; the downscaled historical (1976-2005) and near future (2011-2040) RCP climate sceneries of AR5 were applied to the calculation of the index. The result showed four agro-climatic indices calculated by nine individual GCMs as well as MME agreed with agro-climatic indices which were calculated by the observed data. It was confirmed that MME, as well as each individual GCM emulated well on past climate in the four major Rivers of South Korea (Han, Nakdong, Geum, and Seumjin and Yeoungsan). However, spatial downscaling still needs further improvement since the agro-climatic indices of some individual GCMs showed different variations with the observed indices at the change of spatial distribution of the four Rivers. The four agro-climatic indices of the Korean Peninsula were expected to increase in nine individual GCMs and MME in future climate scenarios. The differences and uncertainties of the agro-climatic indices have not been reduced on the unlimited coupling of multi-model ensembles. Further research is still required although the differences started to improve when combining of three or four individual GCMs in the study. The agro-climatic indices which were derived and evaluated in the study will be the baseline for the assessment of agro-climatic abnormal indices and agro-productivity indices of the next research work.

• Journal of The Korean Society of Grassland and Forage Science
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• v.36 no.3
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• pp.205-214
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• 2016

The objective of this study was to construct a forage rye (FR) dry matter yield (DMY) estimation model based on climate data by locations in South Korea. The data set (n = 549) during 29 years were used. Six optimal climatic variables were selected through stepwise multiple regression analysis with DMY as the response variable. Subsequently, via general linear model, the final model including the six climatic variables and cultivated locations as dummy variables was constructed as follows: DMY = 104.166SGD + 1.454AAT + 147.863MTJ + 59.183PAT150 - 4.693SRF + 45.106SRD - 5230.001 + Location, where SGD was spring growing days, AAT was autumnal accumulated temperature, MTJ was mean temperature in January, PAT150 was period to accumulated temperature 150, SRF was spring rainfall, and SRD was spring rainfall days. The model constructed in this research could explain 24.4 % of the variations in DMY of FR. The homoscedasticity and the assumption that the mean of the residuals were equal to zero was satisfied. The goodness-of-fit of the model was proper based on most scatters of the predicted DMY values fell within the 95% confidence interval.

• Solar Energy
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• v.11 no.1
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• pp.3-15
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• 1991

In this study global radiation and global illumination are directly measured and diffuse radiation and diffuse illumination measured utilizing semi-circular shadow ring. By analyzing measured radiation data, clear and overcast sky are classified according to the sky classification method used in Mantes, France. Measured illumination data are analyzed and 1) Clear sky illumination on a horizontal surface as a function of solar altitude. 2) Overcast sky illumination on a horizontal surface as a function of solar altitude, 3) Monthly variation of illumination. 4) Cumulative percentage of illumination, 5) Daylight intensity as a function of hours in a typical day, 6) Average number hours per day of illumination above 10 and 20klx are presented as a climatic data for daylighting design for Seoul, Korea.

• Journal of the Korean Institute of Navigation
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• v.17 no.4
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• pp.43-51
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• 1993

The purposes of this study are to make an analysis the sensible degree in Korea by using the formulas prepared by Watanabe, and to divide the climatic classification by the sensible degree in order to apply in practical life. Most data(air temperature, relative humidity, wind velocity, atmospheric pressure) are extracted from the "Climatic Table of Korea, Volume II(1961~1990)" issued by the Korea Meteorological Administration. As a result of this study, distribution patterns of the sensible degree are similar to isotherms when the wind velocity is zero, and then the sensible degrees are reduced with the increase of latitude. And western coastal and inland regions have larger values than eastern coastal regions in summer. However, the cont-rary distributions are shown in winter. When the wind velocity is not zero, distribution patterns of the sensible degree are influenced by the wind velocity. In summer, the values of central and southern inland regions are especially higher than the coastal regions, and most northern districts and some inland regions (Kangnung, Ulchin, Yongju etc.) have low values in winter. Then, the climate of Korea is divided into four patterns as follows : Yow means the sensible degree when the wind velocity is zero in winter. Yow > 3 : Jeju Island and southern coastal regions Yow = 0~3 : Most southern district and eastern coastal regions of central districts Yow = -3~0 : Most central districts and some eastern coastal regions (Hamheung, Youngheung, Won-san etc.) of northern districts Yow < -3 : Most northern districts and some inland regions(Inje, Hongcheon, Yang-pyeong etc.) of cent-ral districts.districts.