• Proceedings of The Korean Society of Agricultural and Forest Meteorology Conference
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• 2001.06a
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• pp.139-142
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• 2001

국지기온 결정인자 가운데 특히 고도의 영향이 현저하므로 비관측점과 공간내삽에 사용되는 주변 관측점간 표고편차를 기온감율에 의해 보정해주는 간단한 방법은 상대적으로 복잡한 다른 기법들에 비해 우수한 결과를 보인다 (Nalder and Wein, 1998). 지구대기의 건조단열감율은 -0.0098$^{\circ}C$m$^{-1}$로 상수이지만, 수증기로 포화된 대기의 기온감율은 지표 부근의 -0.004$^{\circ}C$m$^{-1}$부터 대류권 중간의 -0.007$^{\circ}C$m$^{-1}$를 거쳐 권계면 부근에서는 건조단열감율과 거의 같아진다 (Wallace and Hobbs, 1997).(중략)

• Korean Journal of Agricultural and Forest Meteorology
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• v.5 no.1
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• pp.43-47
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• 2003

Air temperature was continuously measured in hilly pear orchards at 4 sites with elevations of 10, 49, 104 and 253 m above sea level. The mean air temperature, averaged over the 10-month period from August 2001 to June 2002, decreased as the site elevation increased by 0.2$^{\circ}C$ per 100 m. This weak lapse condition was amplified during daytime by sun-slope geometry. But on most days an inversion condition began by sunset and persisted until the next sunrise. During the observation period, daily minimum temperature at the valley bottom was lower than that of the hilltop on 67% of the days, and the average temperature difference was 1.4$^{\circ}C$. Inversion of daily minimum temperature under clear sky conditions was stronger in spring and autumn than in winter with a maximum of 6$^{\circ}C$. Lapse condition was predominant in daily minimum temperature on rainy days, and the lapse rate was strongest in winter.

• Journal of Korean Society for Geospatial Information Science
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• v.19 no.2
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• pp.19-27
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• 2011

The objective of this study was to suggest technical approaches for preparation and down scaling of climate data used for predicting the potential forest distribution. To predict the forest distribution, we employed a Korean-specific forest distribution model, so-called the TAG(Thermal Analogy Group), and defined the PFT(Plant Functional Types) based on the HyTAG(Hydrological and Thermal Analogy Group). The climate data with 20km spatial resolution were interpolated to fit on the input data format with 1km spatial resolution. Two potential forest distribution maps were estimated using climate data constructed by kriging, one of the interpolation and down-scaling approaches, with and without lapse rate considered. Through the verification process by comparing two potential maps with the actual vegetation map, the forest distribution using the lapse rate was proven to be 38% more accurate.

• Korean Journal of Agricultural and Forest Meteorology
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• v.3 no.2
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• pp.96-104
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• 2001

Usage of ecosystem models has been extended to landscape scales for understanding the effects of environmental factors on natural and agro-ecosystems and for serving as their management decision tools. Accurate prediction of spatial variation in daily temperature is required for most ecosystem models to be applied to landscape scales. There are relatively few empirical evaluations of landscape-scale temperature prediction techniques in mountainous terrain such as Korean Peninsula. We derived a periodic function of seasonal lapse rate fluctuation from analysis of elevation effects on daily temperatures. Observed daily maximum and minimum temperature data at 63 standard stations in 1999 were regressed to the latitude, longitude, distance from the nearest coastline and altitude of the stations, and the optimum models with $r^2$ of 0.65 and above were selected. Partial regression coefficients for the altitude variable were plotted against day of year, and a numerical formula was determined for simulating the seasonal trend of daily lapse rate, i.e., partial regression coefficients. The formula in conjunction with an inverse distance weighted interpolation scheme was applied to predict daily temperatures at 267 sites, where observation data are available, on randomly selected dates for winter, spring and summer in 2000. The estimation errors were smaller and more consistent than the inverse distance weighting plus mean annual lapse rate scheme. We conclude that this method is simple and accurate enough to be used as an operational temperature interpolation scheme at landscape scale in Korea and should be applicable to elsewhere.

• Journal of the Korean Association of Geographic Information Studies
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• v.16 no.4
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• pp.29-38
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• 2013

This study is to construe the spatio-temporal characteristics of temperature in cities and the changes of climatical regions by analyzing a climate change in Korea peninsular. We used daily mean air temperature data which were collected in South and North climate stations for the past 34 years from 1974 to 2007. We created temperature maps of 500m resolution with Inverse Distance Weight in application with adiabatic lapse rate per month in linear relation with height and temperature. In the urbanization area, the data analyzed population in comparison with temperature changes by the year. The south climate region in Korea by the Warmth index was expanded to the middle climate region by the latitude after 1990s. A rise of mean temperature was $0.5{\sim}1.2^{\circ}C$ in urban areas such as Seoul, metropolitan and cities which had a rapid urbanization and industrialization with the population increase between 1980s and 1990s. In case of North Korea, cities such as Pyeongyang, Anju, Gaecheon, and Hesan had the same pattern.

• Korean Journal of Agricultural and Forest Meteorology
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• v.2 no.4
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• pp.175-182
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• 2000

Spatial interpolation of daily temperature forecasts and observations issued by public weather services is frequently required to make them applicable to agricultural activities and modeling tasks. In contrast to the long term averages like monthly normals, terrain effects are not considered in most spatial interpolations for short term temperatures. This may cause erroneous results in mountainous regions where the observation network hardly covers full features of the complicated terrain. We developed a spatial interpolation model for daily minimum temperature which combines inverse distance squared weighting and elevation difference correction. This model uses a time dependent function for 'mountain slope lapse rate', which can be derived from regression analyses of the station observations with respect to the geographical and topographical features of the surroundings including the station elevation. We applied this model to interpolation of daily minimum temperature over the mountainous Korean Peninsula using 63 standard weather station data. For the first step, a primitive temperature surface was interpolated by inverse distance squared weighting of the 63 point data. Next, a virtual elevation surface was reconstructed by spatially interpolating the 63 station elevation data and subtracted from the elevation surface of a digital elevation model with 1 km grid spacing to obtain the elevation difference at each grid cell. Final estimates of daily minimum temperature at all the grid cells were obtained by applying the calculated daily lapse rate to the elevation difference and adjusting the inverse distance weighted estimates. Independent, measured data sets from 267 automated weather station locations were used to calculate the estimation errors on 12 dates, randomly selected one for each month in 1999. Analysis of 3 terms of estimation errors (mean error, mean absolute error, and root mean squared error) indicates a substantial improvement over the inverse distance squared weighting.

• Journal of the Korean Association of Geographic Information Studies
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• v.14 no.3
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• pp.136-149
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• 2011

The aim of this study is to develop future climate scenario by downscaling the regional climate model (RCM) from global climate model (GCM) based on IPCC A1B scenario. To this end, the study first resampled the KMA-RCM(Korea meteorological administration-regional climate model) from spatial resolution of 27km to 1km. Second, observed climatic data of temperature and rainfall through 1971-2000 were processed to reflect the temperature lapse rate with respect to the altitude of each meteorological observation station. To optimize the downscaled results, Co-kriging was used to calculate temperature lapse-rate; and IDW was used to calculate rainfall lapse rate. Fourth, to verify results of the study we performed correlation analysis between future climate change projection data and observation data through the years 2001-2010. In this study the past climate data (1971-2000), future climate change scenarios(A1B), KMA-RCM(Korea meteorological administration-regional climate model) results and the 1km DEM were used. The research area is entire South Korea and the study period is from 1971 to 2100. Monthly mean temperatures and rainfall with spatial resolution of 1km * 1km were produced as a result of research. Annual average temperature and precipitation had increased by $1.39^{\circ}C$ and 271.23mm during 1971 to 2100. The development of downscaling method using GIS and verification with observed data could reduce the uncertainty of future climate change projection.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.33 no.6
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• pp.2237-2244
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• 2013

In this study, physics based K-DRUM(K-water Distributed RUnoff Model) using GIS spatial hydrologic data as input data was developed to account for the temperature variation according to the altitude change considering snow melt and cover. The model was applied for Pakistan Kunhar River Basin($2,500km^2$) to calculate long-term discharge considering snow melt and cover. Time series analysis of the temperature and rainfall data reveals that temperature and rainfall of the river basin differs significantly according to altitude change compared to domestic basin. Thus, applying temperature and altitude lapse rate during generate input data generation. As a result, calculated discharge shows good agreement with observed ones considering snow melt and accumulation characteristic which has the difference of 4,000 meter elevation above sea level. In addition, the simulated discharge strongly showed snow melting effect associated with temperature rise during the summer season.

• Journal of The Geomorphological Association of Korea
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• v.15 no.2
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• pp.85-94
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• 2008

This study is to construe spatio-temporal characteristics of temperature in cities and changes of climatical regions in analyzing a change of Korea Peninsular climate. We used daily mean air temperature data which was collected in South and North Korea for the past 34 years from 1974 to 2007. We created temperature map of 500m resolution using Inverse Distance Weight in application with adiabatic lapse rate per month in linear relation with height and temperature. In the urbanization area, the data analyzed population in comparison with temperature changes by the year. An annual rising rate of temperature was calculated $0.0056^{\circ}C$, and the temperature was increased $2.14^{\circ}C$ from 1974 to 2107. The south climate region in Korea by the Warmth index was expanded to the middle climate region by the latitude after 1990s. A rise of urban area in mean temperature was $0.5-1.2^{\circ}C$, Seoul, metropolitan and cities which were high density of urbanization and industrialization with the population increase between 1980s and 1990s. In case of North Korea, Cities were Pyeongyang, Anju, Gaecheon, Hesan. A rise in cities areas in mean temperature has influence on vegetation, especially secondary growth such as winter buds of pine trees appears built-up area and outskirts in late Autumn. Finally, nowaday we confront diverse natural events over climatical changes, We need a long-term research to survey and analyze an index on the climatical changes to present a systematic approach and solution in the future.

• Korean Journal of Agricultural and Forest Meteorology
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• v.4 no.2
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• pp.95-102
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• 2002

Spatial interpolation has become a common procedure in converting temperature forecasts and observations at irregular points for use in regional scale ecosystem modeling and the model based decision support systems for resource management. Neglection of terrain effects in most spatial interpolations for short term temperatures may cause erroneous results in mountainous regions, where the observation network hardly covers full features of the complicated terrain. A spatial interpolation model for daytime hourly temperature was formulated based on error analysis of unsampled site with respect to the site topography. The model has a solar irradiance correction scheme in addition to the common backbone of the lapse rate - corrected inverse distance weighting. The solar irradiance scheme calculates the direct, diffuse and reflected components of shortwave radiation over any surfaces based on the sun-slope geometry and compares the sum with that over a reference surface. The deviation from the reference radiation is used to calculate the temperature correction term by an empirical conversion formula between the solar energy and the air temperature on any sloped surfaces at an hourly time scale, which can be prepared seasonally for each land cover type. When this model was applied to a 14 km by 22 km mountainous region at a 10 m horizontal resolution, the estimated hourly temperature surfaces showed a better agreement with the observed distribution than those by a conventional method.