• Title/Summary/Keyword: weather interpolation

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Calculation of Optical Flow Vector Based on Weather Radar Images Using a Image Processing Technique (영상처리기법을 활용한 기상레이더 영상기반 광학흐름 벡터 산출에 관한 연구)

  • Mo, Sunjin;Gu, Ji-Young;Ryu, Geun-Hyeok
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2021.05a
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    • pp.67-69
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    • 2021
  • Weather radar images can be used in a variety of ways because of their high visibility in terms of visuals. In other words it has the advantage of being able to grasp the flow of weather phenomena using not only the raw data of the weather radar, but also the change characteristics between consecutive images. In particular image processing techniques are gradually expanding in the field of meteorological research, and in the case of image data having high resolution such as weather radar images it is expected to produce useful information through a new approach called image processing techniques. In this study the weather phenomena flow was calculated as a vector from the change of the weather radar image according to time interval with the optical flow method, one of the image processing techniques. The characteristics of the weather phenomena to be analyzed were derived through vector analysis resolution suitable for the scale of weather, vector interpolation in regions where no radar echo exists, and the removal of relative flow vectors to distinguish the flow of specific weather and the entire atmosphere. Through this study, it is expected that not only the use of raw data of weather radar, but also the widening of the application area of weather radar, such as the use of unique characteristics of image data, and the active use of image processing techniques in the field of meteorology in the future.

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A Study of Spatial Interpolation Impact on Large Watershed Rainfall Considering Elevation (고도를 고려한 공간보간기법이 대유역 강우량 산정시 미치는 영향 연구)

  • Jung, Hyuk;Shin, Hyung-Jin;Park, Jong-Yoon;Jung, In-Kyun;Kim, Seong-Joon
    • Journal of The Korean Society of Agricultural Engineers
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    • v.53 no.6
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    • pp.23-29
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    • 2011
  • This study was conducted to identify the effect of lapse rate application according to elevation on the estimation of large scale watershed rainfall. For the Han river basin (26,018 $km^2$), the 11 years (2000-2010) daily rainfall data from 108 AWS (Automatic Weather Station) were collected. Especially, the 11 heavy rain and typhoon events from 2004 to 2009 were selected for trend analysis. The elevation effect by IDW (Inverse Distance Weights) interpolation showed the change up to +62.7 % for 1,200~1,600m elevation band. The effect based on 19 subbasins of WAMIS (Water Resources Management Information System) water resources unit map, the changes of IDW and Thiessen were -8.0 % (Downstream of Han river)~ +19.7 % (Upstream of Namhan river) and -5.7 %~+15.9 % respectively. It showed the increase trend as the elevation increases. For the 11 years rainfall data analysis, the lapse rate effect of IDW and Thiessen showed increase of 9.7 %~15.5 % and 6.6 %~9.6 % respectively.

Spatial Interpolation of Rainfall by Areal Reduction Factor (ARF) Analysis for Hancheon Watershed

  • Kar, Kanak Kanti;Yang, Sung Kee;Lee, Junho
    • Proceedings of the Korea Water Resources Association Conference
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    • 2015.05a
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    • pp.427-427
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    • 2015
  • The storm water management and drainage relation are the key variable that plays a vital role on hydrological design and risk analysis. These require knowledge about spatial variability over a specified area. Generally, design rainfall values are expressed from the fixed point rainfall, which is depth at a specific location. Concurrently, determine the areal rainfall amount is also very important. Therefore, a spatial rainfall interpolation (point rainfall converting to areal rainfall) can be solved by areal reduction factor (ARF) estimation. In mainland of South Korea, for dam design and its operation, public safety, other surface water projects concerned about ARF for extreme hydrological events. In spite of the long term average rainfall (2,061 mm) and increasing extreme rainfall events, ARF estimation is also essential for Jeju Island's water control structures. To meet up this purpose, five fixed rainfall stations of automatic weather stations (AWS) near the "Hancheon Stream Watershed" area has been considered and more than 50 years of high quality rainfall data have been analyzed for estimating design rainfall. The relationship approach for the 24 hour design storm is assessed based on ARF. Furthermore, this presentation will provide an outline of ARF standards that can be used to assist the decision makers and water resources engineers for other streams of Jeju Island.

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Development of Global Natural Vegetation Mapping System for Estimating Potential Forest Area (全球의 潛在的 森林面積을 推定하기 위한 植生圖 製作시스템 開發)

  • Cha, Gyung Soo
    • The Korean Journal of Ecology
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    • v.19 no.5
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    • pp.403-416
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    • 1996
  • Global natural vegetation mapping (GNVM) system was developed for estimating potential forest area of the globe. With input of monthly mean temperature and monthly precipitation observed at weather stations, the system spherically interpolates them into 1°×1°grid points on a blobe, converts them into vegetation types, and produces a potential vegetation map and a potenital vegetation area. The spherical interpolation was based on negative exponential function fed from the constant radius stations with oval weighing method which is latitudinally elongated weighing in temperature and longitudinally elongated weighing in precipitation. The temperature values were corrected for altitude by applying a linear lapse-rate (0.65℃ / 100m) with reference to a built-in digital terrain map of the globe. The vegetation classification was based upon Koppen’s sKDICe. The potential forest area is estimated for 6.96 Gha (46.24%) of the global land area (15.05 Gha).

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Distribution Analysis of Land Surface Temperature about Seoul Using Landsat 8 Satellite Images and AWS Data (Landsat 8 위성영상과 AWS 데이터를 이용한 서울특별시의 지표면 온도 분포 분석)

  • Lee, Jong-Sin;Oh, Myoung-Kwan
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.20 no.1
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    • pp.434-439
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    • 2019
  • Recently, interest in urban temperature change and ground surface temperature change has been increasing due to weather phenomenon due to global warming, heat island phenomenon caused by urbanization in urban areas. In Korea, weather data such as temperature and precipitation have been collected since 1904. In recent years, there are 96 ASOS stations and 494 AWS weather observation stations. However, in the case of terrestrial networks, terrestrial meteorological data except measurement points are predicted through interpolation because they provide point data for each installation point. In this study, to improve the resolution of ground surface temperature measurement, the surface temperature using satellite image was calculated and its applicability was analyzed. For this purpose, the satellite images of Landsat 8 OLI TIRS were obtained for Seoul Metropolitan City by seasons and transformed to surface temperature by applying NASA equation to the thermal bands. The ground measurement data was based on the temperature data measured by AWS. Since the AWS temperature data is station based point data, interpolation is performed by Kriging interpolation method for comparison with Landsat image. As a result of comparing the satellite image base surface temperature with the AWS temperature data, the temperature difference according to the season was calculated as fall, winter, summer, based on the RMSE value, Spring, in order of applicability of Landsat satellite image. The use of that attribute and AWS support starts at $2.11^{\circ}C$ and RMSE ${\pm}3.84^{\circ}C$, which reflects information from the extended NASA.

Analysis of Air Temperature Change Distribution that Using GIS technique (GIS 기법을 이용한 대기온도 변화 분포 분석)

  • Jung, Gyu-Young;Kang, In-Joon;Kim, Soo-Gyum;Joo, Hong-Sik
    • Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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    • 2010.04a
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    • pp.395-397
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    • 2010
  • AWS that exist in Pusan is watching local meteorological phenomena established in place that the weather observatory does not exist by real time, and is used usefully to early input data of numerical weather forecasting model. I wished to display downtown of Pusan and air temperature change of peripheral area using this AWS data. Analyzed volatility using AWS observation data for 5 years to recognize air temperature change of Pusan area through data about temperature among them. Drew air temperature distribution chart by season of recapitulative Pusan area applying IDW linear interpolation with this.

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Virtual-Implemented Solar Cell System with New Cell Model (새로운 태양전지 모델을 이용한 태양전지 가상구현 시스템)

  • Jeong, Byung-Hwan;Lee, Sang-Yong;Oh, Bang-Won;Jeon, Yoon-Suk;Choe, Gyu-Ha
    • Proceedings of the KIEE Conference
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    • 2003.07b
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    • pp.1374-1376
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    • 2003
  • The output of solar cell or array depends on the weather conditions such as cell temperature and insolation level. If the output of the photovoltaic system would be regularly generated under any weather conditions, it is so easy to develop the inverter, its related system, and also control algorithm. This can be performed by the VISC(virtual-implemented solar cell) system studied in this paper. And a few I-V curves are provided by the manufacturers, and so any I-V value between the given curves is unknown. The new model for solar cell is proposed which is based on the interpolation. Both simulation and experiment are executed to show the validity of the proposed VISC system.

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Development of Convective Cell Identification and Tracking Algorithm using 3-Dimensional Radar Reflectivity Fields (3차원 레이더 반사도를 이용한 대류세포 판별과 추적 알고리즘의 개발)

  • Jung, Sung-Hwa;Lee, GyuWon;Kim, Hyung-Woo;Kuk, BongJae
    • Atmosphere
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    • v.21 no.3
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    • pp.243-256
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    • 2011
  • This paper presents the development of new algorithm for identifying and tracking the convective cells in three dimensional reflectivity fields in Cartesian coordinates. First, the radar volume data in spherical coordinate system has been converted into Cartesian coordinate system by the bilinear interpolation. The three-dimensional convective cell has then been identified as a group of spatially consecutive grid points using reflectivity and volume thresholds. The tracking algorithm utilizes a fuzzy logic with four membership functions and their weights. The four fuzzy parameters of speed, area change ratio, reflectivity change ratio, and axis transformation ratio have been newly defined. In order to make their membership functions, the normalized frequency distributions are calculated using the pairs of manually matched cells in the consecutive radar reflectivity fields. The algorithms have been verified for two convective events in summer season. Results show that the algorithms have properly identified storm cells and tracked the same cells successively. The developed algorithms may provide useful short-term forecasting or nowcasting capability of convective storm cells and provide the statistical characteristics of severe weather.

24-Hour Load Forecasting For Anomalous Weather Days Using Hourly Temperature (시간별 기온을 이용한 예외 기상일의 24시간 평일 전력수요패턴 예측)

  • Kang, Dong-Ho;Park, Jeong-Do;Song, Kyung-Bin
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.65 no.7
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    • pp.1144-1150
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    • 2016
  • Short-term load forecasting is essential to the electricity pricing and stable power system operations. The conventional weekday 24-hour load forecasting algorithms consider the temperature model to forecast maximum load and minimum load. But 24-hour load pattern forecasting models do not consider temperature effects, because hourly temperature forecasts were not present until the latest date. Recently, 3 hour temperature forecast is announced, therefore hourly temperature forecasts can be produced by mathematical techniques such as various interpolation methods. In this paper, a new 24-hour load pattern forecasting method is proposed by using similar day search considering the hourly temperature. The proposed method searches similar day input data based on the anomalous weather features such as continuous temperature drop or rise, which can enhance 24-hour load pattern forecasting performance, because it uses the past days having similar hourly temperature features as input data. In order to verify the effectiveness of the proposed method, it was applied to the case study. The case study results show high accuracy of 24-hour load pattern forecasting.

Effects of Network Density on Gridded Horizontal Distribution of Meteorological Variables in the Seoul Metropolitan Area (관측망 밀도가 기상 자료의 격자형 수평 분포에 미치는 영향)

  • Kang, Minsoo;Park, Moon-Soo;Chae, Jung-Hoon;Min, Jae-Sik;Chung, Boo Yeon;Han, Seong Eui
    • Atmosphere
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    • v.29 no.2
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    • pp.183-196
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    • 2019
  • High-quality and high-resolution meteorological information is essential to reduce damages due to disastrous weather phenomena such as flash flood, strong wind, and heat/cold waves. There are many meteorological observation stations operated by Korea Meteorological Administration (KMA) in Seoul Metropolitan Area (SMA). Nonetheless, they are still not enough to represent small-scale weather phenomena like convective storm cells due to its poor resolution, especially over urban areas with high-rise buildings and complex land use. In this study, feasibilities to use additional pre-existing networks (e.g., operated by local government and private company) are tested by investigating the effects of network density on the gridded horizontal distribution of two meteorological variables (temperature and precipitation). Two heat wave event days and two precipitation events are chosen, respectively. And the automatic weather station (AWS) networks operated by KMA, local-government, and SKTechX in Incheon area are used. It is found that as network density increases, correlation coefficients between the interpolated values with a horizontal resolution of 350 m and observed data also become large. The range of correlation coefficients with respect to the network density shows large in nighttime rather than in daytime for temperature. While, the range does not depend on the time of day, but on the precipitation type and horizontal distribution of convection cells. This study suggests that temperature and precipitation sensors should be added at points with large horizontal inhomogeneity of land use or topography to represent the horizontal features with a resolution higher than 350 m.