• 제목/요약/키워드: Daily meteorological data

검색결과 442건 처리시간 0.028초

대구의 여름철 야간 냉각량과 기상요소와의 관련성 연구 (A Study on the Relationship between the Summertime Night Cooling Rate and Meteorological Elements in Daegu)

  • 김하영;김해동
    • 한국환경과학회지
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    • 제30권10호
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    • pp.821-831
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    • 2021
  • The relationship between night cooling rate and meteorological elements was investigated over the past five years (2016-2020), using weather data from the new (Daegu(143)) and old (Shinam(860)) Daegu Regional Meteorological Agency located in the suburban and urban regions, respectively. There was a correlation between the total daily amount of solar radiation (Stot) and the night cooling rate in the both regions. However, a higher correlation was observed at the new Daegu Regional Meteorological Agency station (Daegu(143)). In particular, data from the new Daegu Regional Meteorological Administration's observatory, which experiences a low thermal storage effect caused by artificial structures, showed a higher correlation between nighttime cooling and weather factors. The reason for this is that the lesser the heat storage effect caused by the artificial structures, the better the effect of surface radiation cooling on temperature reduction. These findings confirm that the correlation between night cooling and weather factors can be used to assess the impact of artificial structures in cities.

증발량 산정을 위한 입사태양복사식 비교 (Comparison of incoming solar radiation equations for evaporation estimation)

  • 임창수
    • 농업과학연구
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    • 제38권1호
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    • pp.129-143
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    • 2011
  • In this study, to select the incoming solar radiation equation which is most suitable for the estimation of Penman evaporation, 12 incoming solar radiation equations were selected. The Penman evaporation rates were estimated using 12 selected incoming solar radiation equations, and the estimated Penman evaporation rates were compared with measured pan evaporation rates. The monthly average daily meteorological data measured from 17 meteorological stations (춘천, 강능, 서울, 인천, 수원, 서산, 청주, 대전, 추풍령, 포항, 대구, 전주, 광주, 부산, 목포, 제주, 진주) were used for this study. To evaluate the reliability of estimated evaporation rates, mean absolute bias error(MABE), root mean square error(RMSE), mean percentage error(MPE) and Nash-Sutcliffe equation were applied. The study results indicate that to estimate pan evaporation using Penman evaporation equation, incoming solar radiation equation using meteorological data such as precipitation, minimum air temperature, sunshine duration, possible duration of sunshine, and extraterrestrial radiation are most suitable for 11 study stations out of 17 study stations.

우리나라 강풍의 기후학적 시공간 변화 특성 (Climatological Spatio-Temporal Variation of Strong Wind in Korea)

  • 김현욱;김백조;남형구;정종혁;심재관
    • 대기
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    • 제30권1호
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    • pp.47-57
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    • 2020
  • In this study, the climatological spatio-temporal variation of strong wind and gust wind in Korea during the period from 1993 to 2018 was analyzed using daily maximum wind speed and daily maximum instantaneous wind speed data recorded at 61 observations. Strong wind and gust wind were defined as 14 m s-1 and 20 m s-1, which are the same as the KMA's criteria of special weather report. The frequency of strong wind and gust wind occurrence was divided into regions with the higher 25 percent (Group A) and the lower 75 percent (Group B). The annual frequency of strong wind and gust wind occurrence tended to be decreased in most parts of the Korean peninsula. In Group A with stations located at coastal region, strong wind and gust wind occurred most frequently in winter with higher frequency at 1200~1600 LST and 2300~2400 LST due to influence of East Asian winter monsoon. In addition, a marked decreasing trend throughout the four seasons was shown at Daegwallyeong, Gunsan and Wando observations. In contrast, it can be found in Group B that the monthly frequency of strong wind and wind gust occurrence was higher in August and September by effect of typhoon and hourly frequency was higher from 1200 LST to 1800 LST.

Application of Hidden Markov Chain Model to identify temporal distribution of sub-daily rainfall in South Korea

  • Chandrasekara, S.S.K;Kim, Yong-Tak;Kwon, Hyun-Han
    • 한국수자원학회:학술대회논문집
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    • 한국수자원학회 2018년도 학술발표회
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    • pp.499-499
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    • 2018
  • Hydro-meteorological extremes are trivial in these days. Therefore, it is important to identify extreme hydrological events in advance to mitigate the damage due to the extreme events. In this context, exploring temporal distribution of sub-daily extreme rainfall at multiple rain gauges would informative to identify different states to describe severity of the disaster. This study proposehidden Markov chain model (HMM) based rainfall analysis tool to understand the temporal sub-daily rainfall patterns over South Korea. Hourly and daily rainfall data between 1961 and 2017 for 92 stations were used for the study. HMM was applied to daily rainfall series to identify an observed hidden state associated with rainfall frequency and intensity, and further utilized the estimated hidden states to derive a temporal distribution of daily extreme rainfall. Transition between states over time was clearly identified, because HMM obviously identifies the temporal dependence in the daily rainfall states. The proposed HMM was very useful tool to derive the temporal attributes of the daily rainfall in South Korea. Further, daily rainfall series were disaggregated into sub-daily rainfall sequences based on the temporal distribution of hourly rainfall data.

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Analysis of Time Series Models for Ozone Concentrations at the Uijeongbu City in Korea

  • Lee, Hoon-Ja
    • Journal of the Korean Data and Information Science Society
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    • 제19권4호
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    • pp.1153-1164
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    • 2008
  • The ozone data is one of the important environmental data for measurement of the atmospheric condition of the country. In this article, the Autoregressive Error (ARE) model have been considered for analyzing the ozone data at the northern part of the Gyeonggi-Do, Uijeongbu monitoring site in Korea. The result showed that both overall and monthly ARE models are suited for describing the ozone concentration. In the ARE model, seven meteorological variables and four pollution variables are used as the as the explanatory variables for the ozone data set. The seven meteorological variables are daily maximum temperature, wind speed, relative humidity, rainfall, dew point temperature, steam pressure, and amount of cloud. The four air pollution explanatory variables are Sulfur dioxide(SO2), Nitrogen dioxide(NO2), Cobalt(CO), and Promethium 10(PM10). Also, the high level ozone data (over 80ppb) have been analyzed four ARE models, General ARE, HL ARE, PM10 add ARE, Temperature add ARE model. The result shows that the General ARE, HL ARE, and PM10 add ARE models are suited for describing the high level of ozone data.

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Status of PM10 as an air pollutant and prediction using meteorological indexes in Shiraz, Iran

  • Masoudi, Masoud;Poor, Neda Rajai;Ordibeheshti, Fatemeh
    • Advances in environmental research
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    • 제7권2호
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    • pp.109-120
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    • 2018
  • In the present study research air quality analyses for $PM_{10}$, were conducted in Shiraz, a city in the south of Iran. The measurements were taken from 2011 through 2012 in two different locations to prepare average data in the city. The averages concentrations were calculated for every 24 hours, each month and each season. Results showed that the highest concentration of $PM_{10}$ occurs generally in the night while the least concentration was found at the afternoon. Monthly concentrations of $PM_{10}$ showed highest value in August, while least value was found in January. The seasonal concentrations showed the least amounts in autumn while the highest amounts in summer. Relations between the air pollutant and some meteorological parameters were calculated statistically using the daily average data. The wind data (velocity, direction), relative humidity, temperature, sunshine periods, evaporation, dew point and rainfall were considered as independent variables. The relationships between concentration of pollutant and meteorological parameters were expressed by multiple linear regression equations for both annual and seasonal conditions SPSS software. RMSE test showed that among different prediction models, stepwise model is the best option.

STOCHASTIC SIMULATION OF DAILY WEATHER VARIABLES

  • Lee, Ju-Young;Kelly brumbelow, Kelly-Brumbelow
    • Water Engineering Research
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    • 제4권3호
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    • pp.111-126
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    • 2003
  • Meteorological data are often needed to evaluate the long-term effects of proposed hydrologic changes. The evaluation is frequently undertaken using deterministic mathematical models that require daily weather data as input including precipitation amount, maximum and minimum temperature, relative humidity, solar radiation and wind speed. Stochastic generation of the required weather data offers alternative to the use of observed weather records. The precipitation is modeled by a Markov Chain-exponential model. The other variables are generated by multivariate model with means and standard deviations of the variables conditioned on the wet or dry status of the day as determined by the precipitation model. Ultimately, the objective of this paper is to compare Richardson's model and the improved weather generation model in their ability to provide daily weather data for the crop model to study potential impacts of climate change on the irrigation needs and crop yield. However this paper does not refer to the improved weather generation model and the crop model. The new weather generation model improved will be introduced in the Journal of KWRA.

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동절기 기후인자와 염해 오손간의 상관관계 분석 (Analysis on the Correlation between the Meteorological Factors of the Winter Season and the Salt Pollution)

  • 김재훈;김도영;김주한;김필환;한상옥;박강식
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 2004년도 하계학술대회 논문집 C
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    • pp.1802-1804
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    • 2004
  • In seashore, outdoor insulators are polluted due to salty wind and the pollution causes the flashover and failure of electric equipments. As well known, the pollution has a close relation with meteorological factors such as wind velocity, precipitation, wind direction, relative humidity, dew point, etc. In this paper we statistically analyzed the correlation between the pollution and the meteorological factors including snowfall and freezing. The multiple regression analysis was used for the statistical analysis; daily measured equivalent salt deposit density(dependent variable) and the meteorological data(independent variable) were used. From the results of this investigation, we verified the influence of snowfall and freezing on the ESDD, which has been overlooked in the preceding investigation.

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PM10 연속자동측정기(β-ray) 등가성평가 및 비교관측 연구 (PM10 β-ray attenuation samplers (β-ray absorption method) equivalence evaluation and comparatively observed study)

  • 정원석;고희정;서원익;정지영;오상민;부경온
    • 한국입자에어로졸학회지
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    • 제19권1호
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    • pp.13-20
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    • 2023
  • The Asian dust observation network operates β-ray attenuation samplers to measure PM10 concentrations. In addition, equivalence evaluation and accuracy inspection(Precision Tests) are conducted every year for the reliability of data. β-ray attenuation samplers(16 units) were comparatively observed from May to June 2020 and from July to December 2021. During the observation period, the average daily temperature was the lowest at 6.4℃ in December and the highest at 27.3℃ in August. The average daily humidity ranged from 60% to 100%, but the average daily humidity was over 75% from July to September. The minimum value of the PM10 Gravimetric method was 5.0 ㎍/m3, the maximum value was 53.4 ㎍/m3, and the average value was 17.8 ㎍/m3. The equivalence evaluation results of the PM10 Gravimetric method and β-ray attenuation samplers satisfied the criteria (slope: 1±0.1, intercept: 0±0.5). A relative error analysis between the PM10 Gravimetric method and β-ray attenuation samplers equipment showed that the relative error increased when the concentration was low and the temperature and humidity were high. In addition, in the β-ray attenuation samplers 5-minute interval observation data in May 2020, a relatively large Standard devication was shown as an average maximum ±23.4 ㎍/m3 and a minimum ±15.2 ㎍/m3. At standard deviations of 10% and 90%, equipment with high variability (deviation) was measured at 6 ㎍/m3and 61 ㎍/m3, and equipment with low variability was measured at 12 ㎍/m3 and 47 ㎍/m3. It was confirmed that concentration differences occurred due to differences in variability for each equipment.

대구시의 고농도 오존 발생 일에 나타나는 기상학적 특성 (Meteorological Characteristics of High-Ozone Episode Days in Daegu, Korea)

  • 손임영;김희종;윤일희
    • 한국지구과학회지
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    • 제23권5호
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    • pp.424-435
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    • 2002
  • 이 연구에서는 1997년부터 1999년 3년 간 대구광역시의 시간별 O$_3$ 농도 자료와 기상자료를 분석하여, 대구시의 고농도 오존 발생 일에 나타나는 기상학적 특성을 알아보고자 한다. 고농도 오존 발생 일의 선정은 우리나라 환경기준치인 1시간 평균 오존 농도 100ppb를 초과한 지점이 대구시의 6개 측정 지점 중 한 지점이라도 있는 경우로 정했다. 고농도 오존 발생 일은 13일이었으며, 5월과 9월이 가장 그 빈도가 높았다. 고농도 오존 발생 일의 하루 평균 최대 오존 농도는 81.6ppb이었으며, 8시간 평균 농도는 58.6ppb이었다. 이는 대구의 오존 오염이 연속적으로 그리고 광범위하게 일어났고 있음을 의미한다. 하루 최고 오존 농도는 일사량, 최고 온도와 양의 상관을 보였으며, 상대 습도, 풍속, 구름양과는 음의 상관을 보였다. 일사량과의 상관계수가 0.45로 가장 높았다. 고농도 오존 발생 일의 기상 값과 그 날을 포함하는 월평균 값과의 차이를 보면, +1.58hPa(해면 기압), +3.45${\circ}$C(최고 기온), -5.69%(상대 습도), -0.46ms$^{-1}$(풍속), -1.79(구름양), +3.97MJm$^{-2}$(일사량)을 각각 보였다. 이는 0700${\sim}$1100LST사이의 높은 일사량, 낮은 풍속, 무강수가 고농도 예측의 중요특징임을 나타낸다. 이는 이 시간의 정체와도 연관이 있다.