• Title/Summary/Keyword: hourly data

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Atmospheric Stability Evaluation at Different Time Intervals for Determination of Aerial Spray Application Timing

  • Huang, Yanbo;Thomson, Steven J.
    • Journal of Biosystems Engineering
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    • v.41 no.4
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    • pp.337-341
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    • 2016
  • Purpose: Evaluation of atmospheric conditions for proper timing of spray application is important to prevent off-target movement of crop protection materials. Susceptible crops can be damaged downwind if proper application procedure is not followed. In our previous study, hourly data indicated unfavorable conditions, primarily between evening 18:00 hrs in the evening and 6:00 hrs next morning, during clear conditions in the hot summer months in the Mississippi delta. With the requirement of timely farm operations, sub-hourly data are required to provide better guidelines for pilots, as conditions of atmospheric stability can change rapidly. Although hourly data can be interpolated to some degree, finer resolution for data acquisition of the order of 15 min would provide pilots with more accurate recommendations to match the data recording frequency of local weather stations. Methods: In the present study, temperature and wind speed data obtained at a meteorological tower were re-sampled to calculate the atmospheric stability ratio for sub-hour and hourly recommendations. High-precision evaluation of temperature inversion periods influencing atmospheric stability was made considering strength, time of occurrence, and duration of temperature inversion. Results and Discussion: The results indicated that atmospheric stability could be determined at different time intervals providing consistent recommendations to aerial applicators, thereby avoiding temperature inversion with minimal off-target drift of the sprayed liquid.

Hourly Rainfall Surface Prediction with Meteorological Radar Data (기상레이더 자료를 이용한 시우량곡면 예측)

  • 정재성;이재형
    • Water for future
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    • v.29 no.3
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    • pp.187-195
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    • 1996
  • In this study, a methodology for the hourly prediction of rainfall surfaces was applied to the Pyungchang river basin at the upstream of South Han river with meteorological radar and ground rainfall data. The methods for the exclusion of abnormal echoes, and suppression of ground clutter, and the augmentation of attenuation effects associated with rainfall phenomena were reviewed, and the relationship between radar reflectivity (Z) and rainfall rate (R) was analyzed. The transformation of augmented radar reflectivities into the rdar rainfall surfaces was carried out, and afterward they were synthesized with the ground rainfall data generating the hourly rainfall surfaces. For the prediction of hourly rainfall surface, the moving factors of rainfall field estimated by the cross correlation coefficient method and the temporal variation of radar rainfall intensities were considered. The synthesized hourly rainfall surfaces were used to predict the hourly rainfall surfaces up to 3 hours in advance and subsequently the results were compared with the measured and the synthesized. It seems that the prediction method need to be verified with more data and be complemented further to consider the physical characteristics of rainfall field and the topography of the basin.

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A Stochastic Simulation Model for the Precipitation Amounts of Hourly Precipitation Series (시간강수계열의 강수량 모의발생을 위한 추계학적 모형)

  • Lee, Jung-Sik;Lee, Jae-joon;Park, Jong-Young
    • Journal of Korea Water Resources Association
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    • v.35 no.6
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    • pp.763-777
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    • 2002
  • The objective of this study is to develop computer simulation model that produces precipitation patterns from stochastic model. The hourly precipitation process consists of the precipitation occurrence and precipitation amounts. In this study, an event cluster model developed by Lee and Lee(2002) is used to describe the occurrence process of events, and the hourly precipitation amounts within each event is described by a nonstationary form of a first-order autoregressive process. The complete stochastic model for hourly precipitation is fitted to historical precipitation data by estimating the model parameters. An analysis of historical and simulated hourly precipitation data for Seoul indicates that the stochastic model preserves many of the features of historical precipitation. The autocorrelation coefficients of the historical and simulated data are nearly identical except for lags more than about 3 hours. The precipitation intensity, duration, marginal distributions, and conditional distributions for event characteristics for the historical and simulated data showed in general good agreement with each other.

Analysis and Calculation of Global Hourly Solar Irradiation Based on Sunshine Duration for Major Cities in Korea (국내 주요도시의 일조시간데이터를 이용한 시간당전일사량 산출 및 분석)

  • Lee, Kwan-Ho;Sim, Kwang-Yeal
    • Journal of the Korean Solar Energy Society
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    • v.30 no.2
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    • pp.16-21
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    • 2010
  • Computer simulation of buildings and solar energy systems are being used increasingly in energy assessments and design. This paper discusses the possibility of using sunshine duration data instead of global hourly solar irradiation (GHSI) data for localities with abundant data on sunshine duration. For six locations in South Korea where global radiation is currently measured, the global radiation was calculated using Sunshine Duration Radiation Model (SDRM), compared and analyzed. Results of SDRM has been compared with the measured data on the coefficients of determination (R2), root-mean-square error (RMSE) and mean bias error (MBE). This study recommends the use of sunshine duration based irradiation models if measured solar radiation data is not available.

Development of Short-Term Load Forecasting Algorithm Using Hourly Temperature (시간대별 기온을 이용한 전력수요예측 알고리즘 개발)

  • Song, Kyung-Bin
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.63 no.4
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    • pp.451-454
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    • 2014
  • Short-term load forecasting(STLF) for electric power demand is essential for stable power system operation and efficient power market operation. We improved STLF method by using hourly temperature as an input data. In order to using hourly temperature to STLF algorithm, we calculated temperature-electric power demand sensitivity through past actual data and combined this sensitivity to exponential smoothing method which is one of the STLF method. The proposed method is verified by case study for a week. The result of case study shows that the average percentage errors of the proposed load forecasting method are improved comparing with errors of the previous methods.

Determination of Driving Rain Index by Using Hourly Weather Data for Developing a Good Design of Wooden Buildings

  • Ra, Jong Bum
    • Journal of the Korean Wood Science and Technology
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    • v.46 no.6
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    • pp.627-636
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    • 2018
  • This research was performed to supplement the previous research about the driving rain index (DRI) for Korea determined by using daily weather data for 30 years. The average annual driving rain index (AADRI) was calculated from the hourly weather data, and the magnitude of DRI was investigated according to wind directions. The hourly climate data were obtained from the Korea Meteorological Administration (KMA) for the period 2009 to 2017. Of 82 locations investigated, seven were classified into regions where the level of exposure of walls to rain was high. The result showed quite a difference from the previous results, in which no high exposure regions were observed. Since the hourly-based and the daily-based annual driving rain index (ADRI) values showed only a slight difference, the result may be explained by the length of the periods used in both studies. The change of DRI according to wind directions showed that there was a certain range of wind directions in which driving rain easily approached building walls. It suggests that the consideration of wind directions with high DRI would be useful to develop a good design of wooden buildings from the point of wood preservation and maintenance.

Application of Neural Networks to Short-Term Load Forecasting Using Electrical Load Pattern (전력부하의 유형별 단기부하예측에 신경회로망의 적용)

  • Park, Hu-Sik;Mun, Gyeong-Jun;Kim, Hyeong-Su;Hwang, Ji-Hyeon;Lee, Hwa-Seok;Park, Jun-Ho
    • The Transactions of the Korean Institute of Electrical Engineers A
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    • v.48 no.1
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    • pp.8-14
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    • 1999
  • This paper presents the methods of short-term load forecasting Kohonen neural networks and back-propagation neural networks. First, historical load data is divided into 5 patterns for the each seasonal data using Kohonen neural networks and using these results, load forecasting neural network is used for next day hourly load forecasting. Next day hourly load of weekdays and weekend except holidays are forecasted. For load forecasting in summer, max-temperature and min-temperature data as well as historical hourly load date are used as inputs of load forecasting neural networks for a better forecasting accuracy. To show the possibility of the proposed method, it was tested with hourly load data of Korea Electric Power Corporation(1994-95).

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Spatiotemporal distribution of downscaled hourly precipitation for RCP scenarios over South Korea and its hydrological responses

  • Lee, Taesam;Park, Taewoong;Park, Jaenyoung
    • Proceedings of the Korea Water Resources Association Conference
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    • 2015.05a
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    • pp.247-247
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    • 2015
  • Global Climate Model (GCM) is too coarse to apply at a basin scale. The spatial downcsaling is needed to used to permit the assessment of the hydrological changes of a basin. Furthermore, temporal downscaling is required to obtain hourly precipitation to analyze a small or medium basin because only few or several hours are used to determine the peak flows after it rains. In the current study, the spariotemporal distribution of downscaled hourly precipitation for RCP4.5 and RCP8.5 scenarios over South Korea is presented as well as its implications over hydrologica responses. Mean hourly precipitation significantly increases over the southern part of South Korea, especially during the morning time, and its increase becomes lower at later times of day in the RCP8.5 scenario. However, this increase cannot be propagated to the mainland due to the mountainous areas in the southern part of the country. Furthermore, the hydrological responses employing a distributed rainfall-runoff model show that there is a significant increase in the peak flow for the RCP8.5 scenario with a slight decrease for the RCP4.5 scenario. The current study concludes that the employed temporal downscaling method is suitable for obtaining the hourly precipitation data from daily GCM scenarios. In addition, the rainfall runoff simulation through the downscaled hourly precipitation is useful for investigating variations in the hydrological responses as related to future scenarios.

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A Study on the Emission Characteristics and Prediction of VOCs (Volatile Organic Compounds) using Small Chamber Method (소형챔버법을 이용한 휘발성유기화합물(VOCs) 방출특성 및 예측에 관한 연구)

  • Pang, Seung-Ki;Sohn, Jang-Yeul;Lee, Kwang-Ho
    • KIEAE Journal
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    • v.4 no.4
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    • pp.11-18
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    • 2004
  • In this study, the measurement system was developed for the measurement of pollutants from building materials, and specimens were made with concrete, gypsum board, mortar and wall paper. Characteristics of VOCs and TVOC concentration and Emission Factor as a function of time were assessed, and the conclusion was drawn as follows. (1) From predicting TVOC concentration decrease of specimen 7 with the wall paper attached to the concrete, the graph may become linear by converting the value of y-axis into the log function, and the prediction equation can be expressed as $y=34906{\ast}e^{-0.0093{\ast}time}$. Moreover, chi-square value was 0.83 which is relatively high value, indicating that TVOC concentration can be properly predicted if the same materials are used indoors. (2) From predicting VOCs Emission Factor decrease of specimen 7, the prediction equation can be expressed as $EF=15111{\ast}e^{-0.0093{\ast}time}$, and chi-square value was 0.83. (3) From predicting TVOC concentration decrease of specimen 7, prediction equation can be considered to be $y=254323{\ast}(1-e^{-0.1046{\ast}time})$, and chi-square was 0.994 which is significantly high value, indicating that indoor TVOC concentration can be properly predicted if the same materials are used indoors. Furthermore, the prediction of concentration decrease using cumulative value of hourly measured concentration is considered to be more accurate than that using just hourly measured value directly. (4) From predicting Emission Factor decrease with cumulative hourly data of Emission Factor, chi-square appeared to be higher than that by just using hourly data of Emission Factor directly. Therefore, the prediction of Emission Factor with cumulative hourly data can provide more reliable prediction equation than the case by using just hourly concentration directly.

Hourly Average Wind Speed Simulation and Forecast Based on ARMA Model in Jeju Island, Korea

  • Do, Duy-Phuong N.;Lee, Yeonchan;Choi, Jaeseok
    • Journal of Electrical Engineering and Technology
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    • v.11 no.6
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    • pp.1548-1555
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    • 2016
  • This paper presents an application of time series analysis in hourly wind speed simulation and forecast in Jeju Island, Korea. Autoregressive - moving average (ARMA) model, which is well in description of random data characteristics, is used to analyze historical wind speed data (from year of 2010 to 2012). The ARMA model requires stationary variables of data is satisfied by power law transformation and standardization. In this study, the autocorrelation analysis, Bayesian information criterion and general least squares algorithm is implemented to identify and estimate parameters of wind speed model. The ARMA (2,1) models, fitted to the wind speed data, simulate reference year and forecast hourly wind speed in Jeju Island.