• Korean Journal of Agricultural and Forest Meteorology
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• v.14 no.4
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• pp.277-282
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• 2012

When wind speed exceeds a certain threshold, daily minimum temperature does not drop as predicted by the geospatial model in a cold pooling catchment. A linear regression equation was derived to explain the warming effect of wind speed on daily minimum temperature by analyzing observations at a low lying location within an enclosed catchment. The equation, Y=2X+0.4 ($R^2$=0.76) where Y stands for the warming ($^{\circ}C$) and X for the mean horizontal wind speed (m/s) at 2m height, was combined to an existing model to predict daily minimum temperature across an enclosed catchment on cold pooling days. The adjusted model was applied to 3 locations submerged in a cold air pool to predict daily minimum temperature on 25 cold pooling days with the input of simulated wind speed at each location. Results showed that bias (mean error) was reduced from -1.33 to -0.37 and estimation error (RMSE) from 1.72 to 1.20, respectively, in comparison with those from the unadjusted model.

• Journal of Bio-Environment Control
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• v.9 no.2
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• pp.107-114
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• 2000

We constructed climagraphs for 16 regions of Korea by using the average monthly minimum air temperature, maximum air temperature and global radiation. We characterized the outside climate requirements corresponding to the climate requirements of crops in greenhouses. The climagraphs allow to decide the appropriate climate periods for greenhouse cultivation without heating and cooling equipment. These graphs may be used for analyzing climatic characteristic of a given area, selecting the suitable region and greenhouse and making a rational plan for greenhouse cropping in Korea. We found difficulty in deciding the beginning and end of greenhouse heating and cooling period due to insufficient references.

• Proceedings of the Korea Water Resources Association Conference
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• 2021.06a
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• pp.390-390
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• 2021

본 연구에서는 통계적 방법에 의해 예측된 미래기간의 기온정보와 기온기반의 기준증발산량 산정방법을 연계하여 한강권역을 대상으로 최대 12개월의 미래기간에 대한 기준증발산량을 전망하였다. 기온정보는 Kim et al. (2020)의 연구와 같이 글로벌 기후지수와의 원격상관성을 기반으로 개발된 다중회귀모형을 이용하여 미래기간(예측시점 기준 1~12개월)에 대해 월 평균기온을 예측하고 이를 상세화하여 한강권역 내 주요 ASOS 지점별로 최고/최저기온을 도출하였다. 기준증발산량은 Hamon 방법(Hamon, 1960, 1963)을 기반으로 각 지점별로 상세화된 최고/최저기온을 이용하여 동일한 미래기간(1~12개월)에 대해 산정하였다. 한강권역 전체에 대해 2015년 1월~2020년 12월의 월별 평균기온과 각 지점별 산정한 기준증발산량을 활용하여 기온 및 기준증발산량에 대한 예측성을 분석하였다. 한강권역 전체에 대해 예측된 월별 평균기온의 경우 실제 관측값과 비교하였을 때, PBIAS 4.2~6.4%, R² 0.97~0.98, NSE 0.97~0.98 등으로 매우 높은 예측성을 보였다. 지점별로 상세화된 기온정보를 이용하여 산정한 기준증발산량을 실제 기온으로부터 산정한 기준증발산량과 비교한 결과는 PBIAS 5.0~6.8%, R² 0.97~0.98, NSE 0.96~0.97로 기온에 대한 예측성과 유사하게 나타났다. 기온과 기준증발산량 모두 일부 월이나 일부 지점에서 관측값과 비교했을 때 다소 차이를 보이는 경우도 있었으나, 대상유역 전반적으로는 매우 안정적인 예측결과를 확인할 수 있었다. 기준증발산량에 대한 예측결과(미래 1~12개월)는 계절 및 월 단위의 유역 수자원 전망에 유용하게 활용될 수 있을 것으로 판단된다.

• 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.

• Korean Journal of Agricultural and Forest Meteorology
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• v.13 no.1
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• pp.28-34
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• 2011

This study was carried out to estimate monthly mean of daily maximum and minimum temperature across North Korea at a 30 m grid spacing for a climatological normal year (1971-2000) and the 4 decadal averages (1971-1980, 1981-1990, 1991-2000, and 2001-2010). A geospatial climate interpolation method, which has been successfully used to produce the so-called 'High-Definition Digital Climate Maps' (HD-DCM), was used in conjunction with the 27 North Korean and 17 South Korean synoptic data. Correction modules including local effects of cold air drainage, thermal belt, ocean, solar irradiance and urban heat island were applied to adjust the synoptic temperature data in addition to the lapse rate correction. According to the final temperature estimates for a normal year, North Korean winter is expected colder than South Korean winter by $7^{\circ}C$ in average, while the spatial mean summer temperature is lower by $3^{\circ}C$ than that for South Korea. Warming trend in North Korea for the recent 40 years (1971-2010) was most remarkable in spring and fall, showing a 7.4% increase in the land area with 15 or higher daily maximum temperature for April.

• Korean Journal of Agricultural and Forest Meteorology
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• v.3 no.2
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• pp.105-113
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• 2001

This study was conducted to reveal the effects of local climatic conditions on the vegetative growth in a mature stand of Korean white pine based on climatic estimates. For this, the annual increments of stand variables such as DBH, height, basal area and volume were measured and estimated for seven years from 1974 to 1980. The local climatic conditions in the study site were also estimated by both a topoclimatological method and a spatial statistical technique. The local climatic conditions were then correlated with and regressed on the growth factors to reveal the relationships between the climatic estimates and the growth. It is found that relatively high temperatures had positive effects on the diameter growth. The yearly diameter growth increased when each of mean, maximum, and minimum temperature during the growing season was high. Height growth showed positively significant correlation with three climatic variables. The most important variable influencing height growth was the average of maximum temperature for 10 months from January to October. It means that the higher the average of maximum temperature for 10 months from January to October is, the more height growth of Korean white pine increases. Other climatic variables related to height growth were average of minimum temperature for 3 months in the early growing season and mean relative humidity for the growing season. Six climatic variables related to temperature had effects on basal area increment and all of them were positively correlated with basal area increment. Especially, temperatures from January to March were important factors affecting the basal area increment. In volume increment, high correlation was also recognized with most of temperature variables. This tendency was the same as the results in diameter and hight increments. This means that the volume growth increases when temperatures during the growing season are relatively high.

• Journal of the Korean Geographical Society
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• v.34 no.4
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• pp.385-393
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• 1999

본 연구에서는 한라산의 고도별, 사면별, 계절별 기온(일평균, 일최고, 일최저) 분포와 고산식물의 수직적 분포역을 기초로 고산식물별 온도적 범위를 분석한 후 제주도의 온난화에 따른 한라산 고산식물의 미래를 논의하였다. 아울러 고산지에서의 고도별 기온 분포와 수직적 기온 체감이 환산되어 산악지역에서의 기온 분포를 이해하는데 중요한 자료가 확보되었다. 한라산에서의 100m당 기온체감율은 일평균기온이 -0.58$^{\circ}C$, 일최고기온이 -0.53$^{\circ}C$ 범위내에서 분포가 주로 결정되어, 상대적으로 낮은 최고기온 체감율이 고산식물의 생존에 유리하게 작용한 것으로 보인다. 본 연구에서 얻어진 결과는 온난화에 따른 생태계 변화의 모니터링과 경관 보전 측면에서 유용한 생태적 정보를 축적하여, 한라산에 분포하는 희귀하거나, 멸종위기 상태에 있는 고산식물들의 보전과 관련된 지식이 수립될 수 있다.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.31 no.3
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• pp.383-386
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• 1986

To Study the relationships between rapeseed yield and meteorogical elements, the investigation into the important agronomic characters of Yudal cultivar and climate factors such as precipitation, and temperature from 1975 to 1984 was made. Yearly variation of C. V.(%) were highly significant for yield and the important agronomic character. Correlation coefficients between precipitation of May and Yield or agronomic character were significantly positive. Regression equations between the precipitation of Mayor minimum temperature of February and yield were Y=210.914+1.719X and Y=245.560-1.720X, respectively. Low temperature of February affected rapeseed yield reduction significantly.

• Journal of Bio-Environment Control
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• v.27 no.1
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• pp.64-70
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• 2018

In this study, eleven major coastal areas were selected and the climate environment and the greenhouse direction were analyzed. This research investigates the greenhouse heat loss according to the wind environment at target areas. The target areas were selected based on heated greenhouse cultivation area and wind environment standard. Temperature, wind speed, and wind direction among weather data for 30 years were collected and analyzed. The data were divided into the minimum, average, and maximum temperatures and the Meteorological Agency criteria applied to the weather and wind direction criteria. Data were collected in the range of $0{\sim}180^{\circ}$ considering the symmetry of the shape of the greenhouse. In addition, the wind direction is different for each region and the applied wind direction can be different when referring to the longitudinal direction of the greenhouse and the data are collected in the range of $0{\sim}90^{\circ}$. The results of this study are expected to be used to calculate the heating load of greenhouse installed in places wind speed high.

• Journal of the Korean Association of Geographic Information Studies
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• v.22 no.4
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• pp.197-214
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• 2019

In this study, the correlation analysis was conducted between observed air temperature (maximum, minimum, and mean air temperature) and the daytime and nighttime data of Terra/Aqua MODIS LST(Moderate Resolution Imaging Spectroradiometer Land Surface Temperature) for 86 weather stations. All the data of the recent 11 years from 2008 to 2018 were prepared with daily base. In particular, the characteristics of the cold and heat waves incidence period in 2018 were analyzed. The correlation analysis was performed using the Pearson correlation coefficient(R) and root mean square error(RMSE). As a result of time series analysis, the trend between observed air temperature and MODIS LST were similar, showing the correlation above 0.9 in maximum temperature, above 0.8 in mean and minimum temperature. Especially, the maximum temperature was found to have the highest accuracy with Terra MODIS LST daytime, and the minimum temperature had the highest correlation with Terra MODIS LST nighttime. During the cold wave period, both Terra and Aqua MODIS LST showed higher correlations with nighttime data than daytime data. For the heat wave period, the Aqua MODIS LST daytime data was good, but the overall R was below 0.5. Additional analysis is necessary for further study considering such as land cover and elevation characteristics.