• 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.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.27 no.11
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• pp.574-580
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• 2015

Climatic zone in building code is an administrative district classification reflecting regional climatic characteristics. Use of Degree-Days is a fundamental method that can be used in various building design codes, analysis of building energy performance, and establishment of minimum thermal transmittance of building envelopes. Many foreign countries, such as the USA, the EU, Australia, Italy, India, China, etc., have already adapted climatic zone classification with degree-days, precipitation or amount of water vapor based on the characteristics of their own country's climate. In Korea, however, the minimum requirements for regional thermal transmittance are classified separately for the Jungbu area, Nambu area and Jeju Island with no definite criterion. In this study, degree-days of 255 Korean cities were used for climatic zone classification. Outdoor dry-bulb temperature data from the Korea Meteorological Administration for 1981~2010 was used to calculate degree-days. ArcGIS and the calculated degree-days were utilized to analyze and visualize climatic zone classification. As a result, depending on the distribution and distinctive differences in degree-days, four climatic zones were derived : 1) Central area, 2) Mountain area of Gyeonggi and Gangwon provinces, 3) Southern area, and 4) Jeju Island. The climatic zones were suggested per administrative district for easy public understanding and utilization.

• 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.11 no.6
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• pp.81-86
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• 2011

By strengthening the insulation performance of a building, a great deal of energy can be saved and a comfortable indoor environment can be offered to people. On the other hand, the climate, which has a great influence on the indoor environment, is changed by global warming. Therefore, in planning building envelope structure and design, climate change should be considered. In this paper, the optimal insulation thickness of exterior walls was calculated by an economic assessment method using heating degree-days. Additionally, how much influence climate change has on planning building insulation was investigated. The examination showed that heating degree-days have decreased by about 10% due to climate change in the past few decades. It was also shown that the optimal insulation thickness of exterior walls was thin, at about 6%, in three representative Korean cities (Seoul, Daejeon, Jeju).

• 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.

• KIEAE Journal
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• v.13 no.4
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• pp.43-48
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• 2013

The effect of climate change has influenced humanity and ecosystem with tremendous changes in temperature. For the past 150 years, the national annual average temperature is 0.6 degree increased and the heating degree day reduced from April to November. However, December to January, the climate change was generated and the heating degree day increased. The blackout occured in 2011 and 2012 by increasing electricity consumption of heating and cooling equipment to the effects of climate change. That is because heating load accounted for 20% of building electric use. In this study, strengthening measures to reduce heating energy consumption is presented due to climate change in winter since 1980 to prevent blackout and reliable power supply for the building energy-saving design standards by Meteorological data provided by the National Weather Service were calculated using the heating degree days in order to present eighteen cities from 1980 to 2012. Insulation standards are presented to prevent black-out by the heating degree days. the heating energy demand was reduced almost 6% including 10% in Central, 5% in South and Jeju area based on strengthening of the insulation. It is applied to the entire country an annual economic effect of 250 billion won, and black-out can be prevented.

• The Journal of Sustainable Design and Educational Environment Research
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• v.11 no.2
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• pp.19-27
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• 2012

This study was carried out in order to establish the estimation equation for school power consumption using regression analysis based on collected power consumption for two years of weather data and schools are located in Central Changwon and Masan district in Changwon city. (1) The power consumption estimation equation for Heating and cooling is calculated using power consumption per unit volume, the difference between actual power consumption and results of estimation equations is 4.1%. (2) The power consumption estimation equation for heating load is showed 2.6% difference compared to actual power consumption in Central Changwon and is expressed 2.9% difference compared to that in Masan district. Therefore, the power consumption prediction for each school using the power consumption estimation equation is possible. (3) The power consumption estimation equation for cooling load is showed 8.0% difference compared to actual power consumption in Central Changwon and is expressed 2.9% compared to that in Masan district. As the power consumption estimation equation for cooling load is expressed difference compared to heating load, it needs to investigate influence for cooling load.

• Journal of the Korean Solar Energy Society
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• v.36 no.6
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• pp.61-69
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• 2016

In this study, we analyzed five-year(2011~2015) data for D high school in Seoul area to analyze energy consumption characteristics in high school. The results are summarized as follows. (1) In the result of comparison analysis about 2015 energy consumption by usage, based on primary energy, 18% of energy was consumed in cafeteria, and 82% was consumed in main building. In the case of main building, base and constant load excepting hot water supply in restroom took 40%, heating including freeze protection took 20%, hot water supply in restroom took 14%, and cooling took 8% in order. (2) In the 2015 total energy consumption in D high school based on primary energy, heating energy takes 28%. The range and limit of energy savings coming from the reinforcement of insulation and window performance could be estimated. (3) To introduce new & renewable energy system in high school, electricity-based system is suitable than heat-based system because usage of electric energy is larger than that of heat energy in high school. (4) Five-year energy consumption unit according to heating degree-day showed a linearly increasing trend, and the coefficient of determination(R2) was 0.9763, which means high correlation.

• Journal of the Korean Solar Energy Society
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• v.26 no.3
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• pp.119-125
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• 2006

The impacts of climate changes on building energy demand were investigated by means of the degree-days method. Future trends for the 21st century was assessed based on climate change scenarios with 7 global climate models(GCMs). We constructed hourly weather data from monthly temperatures by Trnsys 16. A procedure to estimate heating degree-days (HDD) and cooling degree-days (CDD) from monthly temperature data was developed and applied to three scenarios for Inchon. In the period 1995-2080, HDD would fall by up to 70%. A significant increase in cooling energy demand was found to occur between 1995-2004(70% based on CDD). During 1995-2080, CDD would Increase by up to 120%. Our analysis shows widely varying shifts in future energy demand depending on season. Heating costs in winter will significantly decrease whereas more expensive electrical cooling energy will be needed.