• Title/Summary/Keyword: 일일기온

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Estimation for the Change of Daily Maxima Temperature (일일 최고기온의 변화에 대한 추정)

  • Ko, Wang-Kyung
    • The Korean Journal of Applied Statistics
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    • v.20 no.1
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    • pp.1-9
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    • 2007
  • This investigation on the change of the daily maxima temperature in Seoul, Daegu, Chunchen, Youngchen was triggered by news items such as the earth is getting warmer and a recent news item that said that Korea is getting warmer due to this climatic change. A statistical analysis on the daily maxima for June over this period in Seoul revealed a positive trend of 1.1190 centigrade over the 45 years, a change of 0.0249 degrees annually. Due to the large variation on these maximum temperatures, one can raise the question on the significance of this increase. To check the goodness of fit of the proposed extreme value model, we shown a Q-Q plot of the observed quantiles against the simulated quantiles and a probability plot. And we calculated statistics each month and a tolerance limit. This is tested through simulating a large number of similar datasets from an Extreme Value distribution which described the observed data very well. Only 0.02% of the simulated datasets showed an increase of this degrees or larger, meaning that the probability is very low for such an event to occur.

A Modeling of Daily Temperature in Seoul using GLM Weather Generator (GLM 날씨 발생기를 이용한 서울지역 일일 기온 모형)

  • Kim, Hyeonjeong;Do, Hae Young;Kim, Yongku
    • The Korean Journal of Applied Statistics
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    • v.26 no.3
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    • pp.413-420
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    • 2013
  • Stochastic weather generator is a commonly used tool to simulate daily weather time series. Recently, a generalized linear model(GLM) has been proposed as a convenient approach to tting these weather generators. In the present paper, a stochastic weather generator is considered to model the time series of daily temperatures for Seoul South Korea. As a covariate, precipitation occurrence is introduced to a relate short-term predictor to short-term predictands. One of the limitations of stochastic weather generators is a marked tendency to underestimate the observed interannual variance of monthly, seasonal, or annual total precipitation. To reduce this phenomenon, we incorporate a time series of seasonal mean temperatures in the GLM weather generator as a covariate.

A stochastic model for winter air-temperature of seoul area (서울지방 겨울철 기온의 확률모델)

  • 김해경;김태수
    • The Korean Journal of Applied Statistics
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    • v.5 no.1
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    • pp.59-80
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    • 1992
  • This paper is concerned with the development and application of a stochastic model for winter air-temperature of Seoul area. The annual and interannual flucturations of the regression trend, periodicity and dependence of the air-temperature are analyzed based on the data during the past 30 years(1959-1989). A statistical procedure for using the stochastic model to predict the air-temperature is proposed. Some statistical characteristics of winter air-temperature including unusual air-temperature and Samhansaon are also discussed.

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Water Temperature Variation of a Stream Entering Soyang Reservoir (소양호 유입지천의 수온변화)

  • Yi, Yong-Kon;Kang, Min-Gu;Lee, Hyun-Seok;Kim, Jin-Young
    • Proceedings of the Korea Water Resources Association Conference
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    • 2006.05a
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    • pp.1063-1067
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    • 2006
  • 소양호의 유입지천 중의 하나인 인북천의 원통수위관측소에 현장용 수온계를 설치하여 수온변화를 분석하고 수온 추정을 위하여 다중회귀분석을 수행하였다. 인북천 원통수위유량관측소지점의 유량이 작은 경우, 수온은 기온의 최고점부근에서 변화하고, 이슬점은 기온의 최저점부근에서 변화하는 것으로 나타났으며, 일일 주기로 변화하는 양상을 보이고, 일교차는 각각 약 $5^{\circ}C,\;15^{\circ}C$$5^{\circ}C$정도로 나타났다. 최대수온과 최대기온은 차이가 거의 없지만 최저수온은 최저기온보다 약 $10^{\circ}C$정도 높은 것으로 나타났다. 인북천 원통수위유량관측소 지점의 유량이 증가하는 경우에는 수온과 기온이 급감하는 것으로 나타났다. 수온추정시 유량이 작은 구간과 큰 경우구간에 대하여 각각 다중회귀분석을 수행하는 것이 추정오차를 낮추는 것으로 나타났다.

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Big Data Analysis of the Correlation between Average Daily Temperature and Batting Power (빅데이터를 활용한 타자의 장타력과 일일 평균 기온 간의 상관관계 분석)

  • Kim, Semin;Shin, Chwacheol
    • Journal of Digital Convergence
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    • v.18 no.8
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    • pp.225-230
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    • 2020
  • The KBO League is held over a long period of time due to the large number of games. Also, Korea has a diverse and distinct climate. Therefore, this study analyzed the relationship between the daily average temperature and the record of batting power such as home runs, triples, doubles, number of bases, batting percentage, and net batting percentage, and a third baseball record was defined. For this study, the correlation between the daily average temperature data and the batter who entered the standard at-bat in the KBO League in 2019 was analyzed through the SEMMA method. From the results of this study, it was found that the average daily temperature had an effect on a batter's hitting power. In particular, it was found that a batter's hitting power decreased on the day of temperatures recorded between 20.0 degrees and 24.9 degrees, and it was discussed that this may have been related to the physical condition of the pitcher the batter was facing. Therefore, it can be expected that players, coaching staff, and the front desk can use them in the game through conditions outside the game. In addition, it is expected that it will be a more useful analysis model by analyzing the records of pitching, base running, and defense as well as subsequent batting records.

Characteristics on the Temperature Distribution in Steel Girder Bridge by using Gauge Measurement (계측에 의한 강거더교의 온도분포 특성)

  • Lee, Seong-Haeng;Cheung, Jin-Hwan;Kim, Kyoung-Nam;Hahm, Hyung-Gil;Jung, Kyoung-Sup
    • Journal of Korean Society of Steel Construction
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    • v.23 no.3
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    • pp.283-294
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    • 2011
  • The variation of temperature in the steel girder bridge by air temperature is measured. A correlation between the daily temperature range, the maximum and minimum temperatures of the day, and the temperature of the bridge are analyzed. With the statistical data from the Korea Meteorological Administration, the temperature correlations analyzed in this study is able to predict temperature variations between the upper flange and the lower flange which calculates the realistic displacement values of a movable support and an expansion joint in design.

Forecasting Daily Demand of Domestic City Gas with Selective Sampling (선별적 샘플링을 이용한 국내 도시가스 일별 수요예측 절차 개발)

  • Lee, Geun-Cheol;Han, Jung-Hee
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.16 no.10
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    • pp.6860-6868
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    • 2015
  • In this study, we consider a problem of forecasting daily city gas demand of Korea. Forecasting daily gas demand is a daily routine for gas provider, and gas demand needs to be forecasted accurately in order to guarantee secure gas supply. In this study, we analyze the time series of city gas demand in several ways. Data analysis shows that primary factors affecting the city gas demand include the demand of previous day, temperature, day of week, and so on. Incorporating these factors, we developed a multiple linear regression model. Also, we devised a sampling procedure that selectively collects the past data considering the characteristics of the city gas demand. Test results on real data exhibit that the MAPE (Mean Absolute Percentage Error) obtained by the proposed method is about 2.22%, which amounts to 7% of the relative improvement ratio when compared with the existing method in the literature.

Development of a Daily Snowmelt Depth Model using Multiple Linear Regression (다중회귀모형을 활용한 일 단위 융설 깊이 예측 모형 개발)

  • Oh, Yeoung Rok;Lee, Gyumin;Shin, Hyungjin;Jun, Kyung Soo
    • Proceedings of the Korea Water Resources Association Conference
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    • 2021.06a
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    • pp.374-374
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    • 2021
  • 최근 우리나라에도 대설로 인한 피해가 발생하고 있으며, 피해의 대부분은 강설 발생 이후 남아 있는 적설량이 주된 원인이 되고 있다. 적설량에 대한 예측은 대설피해에 대응하기 위한 중요한 정보이다. 따라서 본 연구에서는 융설량에 영향을 미칠것으로 판단되는 적설량, 기온, 습도, 일사량을 반영하여 일일 융설량을 모의하는 다중회귀모형을 구성하였다. 모형은 2000년부터 2020년까지의 강설 사상을 대상으로 구축하였으며, 2021년에 발생한 광주, 대관령, 목포, 서산, 전주 지역의 강설 사상에 적용하였다. 분석 대상 지역의 평균 적설량은 7.41 cm로 나타났으며, 평균 RMSE는 1.64 cm가 발생하였다. 오차의 원인으로는 적설량이 1 cm 미만 감소했을 경우, 바람이나 승화의 영향이 상대적으로 크게 작용할 수 있으나, 본 연구에 이용된 함수는 바람과 증발산 등이 고려되지 않았다. 또한, 회귀계수 결정에서 급격한 온도 변화를 능동적으로 반영하기 어려워 급상승한 온도나 매우 낮은 온도에 오차가 더 크게 나타난다. 따라서, 본 함수를 통하여 융설 깊이를 예측하기 위해서는 매우 높은 온도나, 매우 낮은 온도에서의 영향을 통제할 수 있는 변수 또는 상수를 추가할 필요가 있는 것으로 판단된다. 또한 초기 강설 당시의 기온과 습도 등에 따라, 눈의 결정이 달라지고, 이에 따라 융설에도 영향을 미칠 수 있다는 점을 이해하여, 초기 적설에 대한 변수도 고려되어야 할 것이다.

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Developing Korean Forest Fire Occurrence Probability Model Reflecting Climate Change in the Spring of 2000s (2000년대 기후변화를 반영한 봄철 산불발생확률모형 개발)

  • Won, Myoungsoo;Yoon, Sukhee;Jang, Keunchang
    • Korean Journal of Agricultural and Forest Meteorology
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    • v.18 no.4
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    • pp.199-207
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    • 2016
  • This study was conducted to develop a forest fire occurrence model using meteorological characteristics for practical forecasting of forest fire danger rate by reflecting the climate change for the time period of 2000yrs. Forest fire in South Korea is highly influenced by humidity, wind speed, temperature, and precipitation. To effectively forecast forest fire occurrence, we developed a forest fire danger rating model using weather factors associated with forest fire in 2000yrs. Forest fire occurrence patterns were investigated statistically to develop a forest fire danger rating index using times series weather data sets collected from 76 meteorological observation centers. The data sets were used for 11 years from 2000 to 2010. Development of the national forest fire occurrence probability model used a logistic regression analysis with forest fire occurrence data and meteorological variables. Nine probability models for individual nine provinces including Jeju Island have been developed. The results of the statistical analysis show that the logistic models (p<0.05) strongly depends on the effective and relative humidity, temperature, wind speed, and rainfall. The results of verification showed that the probability of randomly selected fires ranges from 0.687 to 0.981, which represent a relatively high accuracy of the developed model. These findings may be beneficial to the policy makers in South Korea for the prevention of forest fires.

Temporal and Spatial Variations in Sea Surface Temperature Around Boryeong off the West Coast of Korea From 2011-2012 (2011-2012년 서해 보령연안 수온의 시공간적 변동)

  • Choo, Hyo-Sang;Yoon, Eun-Chan
    • Journal of the Korean Society of Marine Environment & Safety
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    • v.23 no.5
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    • pp.497-512
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    • 2017
  • Temporal and spatial variations in surface water temperature were studied using data from temperature monitoring buoys deployed at 47 stations around Boryeong from 2011-2012 off the west coast of Korea. Temperature fluctuations are predominant at diurnal and semidiurnal periods for all seasons, and their amplitudes are large in spring and summer but small in autumn. The maximum annual change in air temperature takes place on August 2nd and August 22th for water temperature, which means the phase for air temperature precedes water temperature by 20 days. The diurnal period of water temperature fluctuation is predominant around Daecheon and Muchangpo Harbors, with the semidiurnal period around Wonsan Island, and the shallow water constituent period on the estuary around Daecheon River. On the whole, air and water temperatures fluctuate with wind. Spectral analyses of temperature records show significant peaks at the 0.5, 1 and 15 day marks with 7-10 day periods of predominant fluctuations. Cross-correlation analyses for the temperature fluctuation show that the waters around Boryeong can be classified into four areas: a mixed water zone around the southeast side of Wonsan Island, an off-shore area to the west, an off-shore area to the south and a coastal area along the shore from Song Island to Muchangpo Harbor.