• Journal of the Korean Geographical Society
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• v.40 no.5 s.110
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• pp.584-593
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• 2005

The spatial and temporal variations of heating degree-days (HDDs) and cooling degree-days (CDDs) are closely related with the temperature field. The spatial distribution of 30-year mean HDDs shows that the higher values locates in the northern part of South Korea while the lower values locates in the southern part. The 30-year mean CDDs shows a more randomized distribution than the HDDs. The changing trends of HDDs and CDDs show a different feature: HDDs have a distinct decreasing trend while CDDs have an insignificant change. The decreasing trends of HDDs are consistent over South Korea and most of stations have experienced the statistically significant change. As significant changing areas of HDDs are much broader than those of annual mean temperature, HDDs can be more useful than annual mean temperature to detect the climate change impact on a regional level. In other words, an insignificant change on the mean temperature field can induce the significant change of thermal climatology in a region. The temporal pattern of climatic departure index (CDI) for South Korea HDDs series shows a general decreasing, but a sharp increase during recent years. The drastic decrease of HDDs induces higher CDI indicating larger variability among stations. However, the decrease of South Korea HDDs series cannot totally attribute to the global warming due to urban effects. By the early 1980s, there were no big differences of HDDs between urban and rural series, but later the differences are getting larger. This was expected to be with the intensification of urbanization in South Korea. However, still there is a decreasing trend of HDDs for rural stations.

• Korean Journal of Agricultural and Forest Meteorology
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• v.21 no.2
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• pp.97-109
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• 2019

Degree days have been determined using temperature data measured at nearby weather stations to a site of interest to produce information for supporting decision-making on agricultural production. Alternatively, the data products of Moderate Resolution Imaging Spectroradiometer (MODIS) can be used for estimation of degree days in a given region, e.g., Korean Peninsula. The objective of this study was to develop a simple tool for processing the MODIS product for estimating cooling degree days (CDD), which would help assessment of heat stress conditions for a crop as well as energy requirement for greenhouses. A set of scripts written in R was implemented to obtain temperature profile data for the region of interest. These scripts had functionalities for processing spatial data, which include reprojection, mosaicking, and cropping. A module to extract air temperature at the surface pressure level was also developed using R extension packages such as rgdal and RcppArmadillo. Random forest (RF) models, which estimate mean temperature and CDD with a different set of MODIS data, were trained at 34 sites in South Korea during 2009 - 2018. Then, the values of CDD were calculated over Korean peninsula during the same period using those RF models. It was found that the CDD estimates using the MODIS data explained >74% of the variation in the CDD measurements at the weather stations in North Korea as well as South Korea. These results indicate that temperature data derived from the MODIS atmospheric products would be useful for reliable estimation of CDD. Our results also suggest that the MODIS data can be used for preparation of weather input data for other temperature-based agro-ecological models such as growing degree days or chill units.

• Journal of Climate Change Research
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• v.4 no.2
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• pp.141-158
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• 2013

In this study, the projection of future heating and cooling degree days (HDDs and CDDs) has been conducted over South Korea for the period 1996~2005 with 2046~2055 and 2091~2100, using CCSM3 and MM5 simulations driven by the six IPCC SRES emission scenarios (A2, A1B, A1FI, A1T, B1, and B2). Annual mean surface air temperature increases by $1.2{\sim}3.4^{\circ}C$ at the end of the 21st century comparing to the present-day (1996~2005) in South Korea. HDDs decrease by 8~25% and CDDs increase up to 242~1,448% with corresponding changes in temperature. These increases and decreases also change the duration of HDDs and CDDs. HDDs duration decreases by 1 month, while the expansion of CDDs duration is much longer than 2 months. Thus, projected future HDDs and CDDs changes appear that cooling energy demand in summer season would increase and heating energy demand in winter would decrease in the future. Especially, these remarkable changes would be obvious at high mountain area, Gangwon-do and at south area, Jeju island. In the sense of future energy supply and policy, electrical energy for cooling in summer could be getting much more its importance rather than fossil energy used for heating in winter.

• Journal of the Korean Solar Energy Society
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• v.38 no.6
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• pp.15-26
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• 2018

It is difficult to check the exact building energy consumption reduction such as when green remodeling of buildings, because it is due to outdoor air temperature over the years. And in Korea although Big Data of building energy consumption is collected and managed through "The Information System of the Building Energy and Greenhouse Gases" it is underutilized because of non calibration of outdoor air temperature change. Therefore, this study aims to develope calibration method of building energy consumption by outdoor air temperature according to micro climates, and building use types. As a result of analysis, Regression equations of Building energy consumption and $HDD_m/CDD_m$ are derived and calibration method is developed by Regression coefficient.

• Proceedings of the KGS Conference
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• 2005.05a
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• pp.80-81
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• 2005

• Proceedings of The Korean Society of Agricultural and Forest Meteorology Conference
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• 2019.08a
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• pp.157-158
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• 2019

• Journal of the Korean Solar Energy Society
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• v.40 no.1
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• pp.15-24
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• 2020

Building energy consumption generally depends on living patterns of residents and outdoor air temperature changes. Although outdoor air temperature changes effect on building energy consumption, there is no calibration method for the comparison before and after Green Remodeling or BEMS installation etc., Big data of building energy consumption are collected and managed by 『National Integrated Management System of Building Energy』 in Korea, and they are utilized for the development of a calibration method for individual buildings as shown as the calibration method for small-area building stocks in the previous research. This study aims to develope a calibration method using big data of building energy consumption of individual buildings and outdoor air temperature changes, and to propose application of appropriate calibration methods for individual buildings or small-area building stocks according to the calibration purpose and conditions.

• Journal of the Korean Solar Energy Society
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• v.40 no.5
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• pp.47-58
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• 2020

Ministry of Land, Infrastructure and Transport(MOLIT) has increased reduction rate from 18.1% to 32.7% in Building sector compared to BAU of the national greenhouse gas emission according to the 2030 Greenhouse Gas Reduction Road map Amendment. For this purpose, MOLIT has been activating the green remodeling projects for existing buildings. Considering that 15 year old buildings after completion are 74% (5.25 million buildings) among about 7 million existing building stocks in Korea, reduction of building energy consumption by green remodeling is urgently needed, However, it is a major difficulty of activation for green remodeling projects because there are few case studies on Before and After building energy consumption of actual green remodeling projects. Considering that building energy performance and value increase after green remodeling through previous researches, additional studies of the energy consumption assessment on actual green remodeling projects are essential. Therefore, this study aims to propose results on Before and After building energy consumption of actual green remodeling projects.

• KIEAE Journal
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• v.9 no.4
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• pp.11-16
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• 2009

To act and respond to the climate changes and to bring about power-saving in buildings, the changes in the atmospheric data in Korea are recorded and assessed. For the two regions representative of Korea, the data obtained from HadCM3 and actual data are compared and analyzed so as to concretely evaluate and confirm the changes taking place in the cooling and heating degree days in Korea. For the past 40 years, from 1996 to 2005, the number of heating degree days was on the decline and in the two representative regions, between 1980's and 1990's, the number of decrease in the heating degree days had been quite large. The number of cooling degree days showed a trend of increase since the 1970's and just as in the case of heating degree days, the extent of increase was quite large between the 1980's and the 1990's. The results of comparison of the number of heating and cooling degree days, one obtained from the "Korea Meteorological Administration" and another from the HadCM3 data (E127.5,N37.5,E127.5,N35), which is one of the ways of predicting the climate, showed similar trends in the number of heating degree days in the Yeosu area. However, in the case of the number of heating degree days in Seoul and the number of cooling degree days both in Seoul and Yeosu, the differences in the number ranged from a minimum of 300 days to a maximum of 1500 days. This could be attributed to the grid points used in the HadCM3, the differences in the values of latitudes and longitudes of these two locations considered in this study, topographical differences, heat island effect caused by population density etc. and while using the HadCM3, these variables factors must be taken into consideration.

• Proceedings of the Korea Water Resources Association Conference
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• 2010.05a
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• pp.1575-1579
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• 2010

본 연구에서는 우리나라 6개 지점(강릉, 서울, 인천, 대구, 부산, 목포)에서 관측한 약 100년간(1912-2009년, 단 1950-1953년 제외)의 일최고/최저기온 및 일강수 자료를 이용하여 각 지점별로 다양한 기후지수를 산출하고 이들의 변화를 살펴보았다. 기온 관련 기후지수로는 여름일수, 영하일수, 결빙일수, 서리일수, 열대야일수, 냉방도일, 난방도일, 일교차, 식물성장일수, 일최고/최저기온의 월최고값 및 월최저값 등을 분석하였으며, 강수 관련 기후지수로 강수량, 강수일수, 강수강도, 호우일수, 미우일수, 최고 일강수 및 5일 연속 최고 강수량, 연속건조일수 및 연속습윤일수, 극한 강수일의 강수량 등을 계산하였다. 다음은 6개 지점의 기후지수를 평균한 결과이다. 6개 지점 모두에서 최저기온의 상승률이 최고기온의 상승률보다 크게 나타남에 따라 분석기간 동안 일교차는 점차 줄어드는 경향($-0.12^{\circ}C$/10년)을 보였고, 최저기온에 근거한 기후지수인 서리일수 (최저기온이 $-5^{\circ}C$ 미만, -2.6일/10년), 영하일수(최고기온이 $0^{\circ}C$ 미만, -1.0일/10년) 등의 감소와 평균기온의 상승에 따른 성장계절길이(growing season length)의 증가(+3.53일/10년)가 뚜렷하게 나타났다. 일강수와 관련된 주요변화로 미우일수(일강수량이 1 $mmday^{-1}$ 이하)는 감소(-0.75일/10년)했지만, 10 $mmday^{-1}$ (+0.32일/10년), 20 $mmday^{-1}$ (+0.27일/10년), 30 $mmday^{-1}$ (+0.25일/10년), 50 $mmday^{-1}$ (+0.17일/10년), 80 $mmday^{-1}$(+0.09일/10년) 이상 내린 강수일수는 증가하였다. 강수강도(강수량이 1 $mmday^{-1}$ 이상일 때의 강수량과 강수일수 기준)는 0.23 $mmday^{-1}$/10년로 증가했다.