• Title/Summary/Keyword: ASOS

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Adaptive Directional Filtering Techniques for Image Sequences (동영상을 위한 적응 방향성 필터링 기술)

  • 고성제
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.18 no.7
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    • pp.922-934
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    • 1993
  • In this paper, statistical properties of the spatiotemporal center weighted median(CWM) filter for image sequences are investigated. It is statistically shown that the CWM filter preserves image structures under motion at the expense of noise suppression. To improve the CWM filter, a filter which can be effectively used in image sequence processing, the adaptive directional center weighted median filter (ADCWM), is proposed. This filter utilizes a multistage filtering structure based on adaptive symmetric order statistic(ASOS) operators which produce a pall of order statistics symmetric about the median. The ASOS's are selected by using adaptive parameters adjusted by local image statistics. It is shown experimentally that the proposed filter can preserve image structures while attenuating noise without the use of motion estimation.

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Evaluation of Seasonal Characteristic of Precipitation Data in Korea by Applying CSEOF analysis (CSEOF 분석을 이용한 국내 강수의 계절적 순환 특성 평가)

  • Cho, Eunsaem;Song, Sung-uk;Na, Wooyoung;Yoo, Chulsang
    • Proceedings of the Korea Water Resources Association Conference
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    • 2019.05a
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    • pp.21-21
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    • 2019
  • 본 연구에서는 국내 주요 종관기상관측장비(Automated Surface Observing System; ASOS)의 강수 자료에 CSEOF 분석(Cyclo-stationary Empirical Orthogonal Function Analysis)을 적용하여 주요 성분(principle component)을 추출한 후 이를 분석하여 국내 강수의 계절적 순환 특성을 평가고자 하였다. ASOS 자료로는 전국 131개의 ASOS 중에 40년 이상의 월 강수량 자료가 구축되어 있는 47개 지점의 자료를 이용하였다. 수집한 자료의 기간은 1978년부터 2018년까지이다. 강수 자료의 월별 공간적인 강수 분포 특성을 파악하기 위해 시간적인 순환성을 고려한 CSEOF 분석을 수행하였다. 강수자료의 주성분을 추출해본 결과, CSEOF 분석의 경우 첫 번째 CSEOF 외의 다른 CSEOF들의 원자료 설명 비율 또한 작지 않게 나타나 다양한 강수 변동 특성을 평가할 수 있음을 확인하였다. 8월의 2nd CSEOF는 한반도 전체의 강수가 감소하는 것으로 나타났으며, 이는 라니냐가 7-8월 한반도 강수에 미치는 영향과 유사하다. 아울러 9월의 2nd CSEOF 결과 또한 남부를 중심으로 전체적으로 감소하는 경향이 나타남. 이는 엘리뇨 발생 시 9월의 강수 패턴과 비슷한 것으로 확인되었다. 뿐만 아니라, 우리나라에 영향을 미친 주요 태풍과 CSEOF의 상관관계도 검증할 수 있었으며, 장마와의 관계도 발견할 수 있었다. 향후, CSEOF 분석 결과에 해석방법이 개발된다면, 보다 다각적인 측면에서의 강수 계절적 순환 특성 평가가 이루어 질 수 있을 것으로 기대한다.

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Correlation Analysis of UA Using Wind Data of AWS/ASOS and SST in Summer in the East Sea (AWS/ASOS 바람자료를 이용한 여름철 동해 연안역의 용승지수와 수온과의 상관성)

  • Kim, Ju-Yeon;Han, In-Seong;Ahn, Ji-Suk
    • Journal of the Korean Society of Marine Environment & Safety
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    • v.24 no.6
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    • pp.773-784
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    • 2018
  • In this study, we examined the UA (upwelling age) using wind data of AWS/ASOS in the East Sea coast and the correlation between UA and SST (sea surface temperature) from May to August in 1995 to 2016. The data used the 6 observations of the wind data of AWS/ASOS and the SST data of the COD/RISA provided by the National Institute and Fisheries Science near the East Sea coast. The UA was calculated quantitatively low but it rose when the actual cold water mass occurred. Correlation analysis between UA and SST showed the negative (-) r (correlation coefficient) predominately. At the time of cold-water mass in June to August 2013, the r had a very high negative value of -0.65 to -0.89 in the 6 observations. It proved that as the UA increases, the SST is lower. By knowing the UA, we were able to evaluate the trend of upwelling in the cold-water mass of the East Sea coast in the long term and it will contribute to minimizing the damage to aquatic organisms according to the size and intensity of the upwelling.

Comparison and Analysis of Drought Index based on MODIS Satellite Images and ASOS Data for Gyeonggi-Do (경기도 지역에 대한 MODIS 위성영상 및 지점자료기반 가뭄지수의 비교·분석)

  • Yu-Jin, KANG;Hung-Soo, KIM;Dong-Hyun, KIM;Won-Joon, WANG;Han-Eul, LEE;Min-Ho, SEO;Yun-Jae, CHOUNG
    • Journal of the Korean Association of Geographic Information Studies
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    • v.25 no.4
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    • pp.1-18
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    • 2022
  • Currently, the Korea Meteorological Administration evaluates the meteorological drought by region using SPI6(standardized precipitation index 6), which is a 6-month cumulative precipitation standard. However, SPI is an index calculated only in consideration of precipitation at 69 weather stations, and the drought phenomenon that appears for complex reasons cannot be accurately determined. Therefore, the purpose of this study is to calculate and compare SPI considering only precipitation and SDCI (Scaled Drought Condition Index) considering precipitation, vegetation index, and temperature in Gyeonggi. In addition, the advantages and disadvantages of the station data-based drought index and the satellite image-based drought index were identified by using results calculated through the comparison of SPI and SDCI. MODIS(MODerate resolution Imaging Spectroradiometer) satellite image data, ASOS(Automated Synoptic Observing System) data, and kriging were used to calculate SDCI. For the duration of precipitation, SDCI1, SDCI3, and SDCI6 were calculated by applying 1-month, 3-month, and 6-month respectively to the 8 points in 2014. As a result of calculating the SDCI, unlike the SPI, drought patterns began to appear about 2-month ago, and drought by city and county in Gyeonggi was well revealed. Through this, it was found that the combination of satellite image data and station data increased efficiency in the pattern of drought index change, and increased the possibility of drought prediction in wet areas along with existing dry areas.

Generation and Verification on the Synthetic Precipitation/Temperature Data

  • Oh, Jai-Ho;Kang, Hyung-Jeon
    • Proceedings of The Korean Society of Agricultural and Forest Meteorology Conference
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    • 2016.09a
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    • pp.25-28
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    • 2016
  • Recently, because of the weather forecasts through the low-resolution data has been limited, the demand of the high-resolution data is sharply increasing. Therefore, in this study, we restore the ultra-high resolution synthetic precipitation and temperature data for 2000-2014 due to small-scale topographic effect using the QPM (Quantitative Precipitation Model)/QTM (Quantitative Temperature Model). First, we reproduce the detailed precipitation and temperature data with 1km resolution using the distribution of Automatic Weather System (AWS) data and Automatic Synoptic Observation System (ASOS) data, which is about 10km resolution with irregular grid over South Korea. Also, we recover the precipitation and temperature data with 1km resolution using the MERRA reanalysis data over North Korea, because there are insufficient observation data. The precipitation and temperature from restored current climate reflect more detailed topographic effect than irregular AWS/ASOS data and MERRA reanalysis data over the Korean peninsula. Based on this analysis, more detailed prospect of regional climate is investigated.

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A Study on the Method for Estimating the 30 m-Resolution Daily Temperature Extreme Value Using PRISM and GEV Method (PRISM과 GEV 방법을 활용한 30 m 해상도의 격자형 기온 극값 추정 방법 연구)

  • Lee, Joonlee;Ahn, Joong-Bae;Jeong, Ha-Gyu
    • Atmosphere
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    • v.26 no.4
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    • pp.697-709
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    • 2016
  • This study estimates and evaluates the extreme value of 30 m-resolution daily maximum and minimum temperatures over South Korea, using inverse distance weighting (IDW), parameter-elevation regression on independent slopes model (PRISM) and generalized extreme value (GEV) method. The three experiments are designed and performed to find the optimal estimation strategy to obtain extreme value. First experiment (EXP1) applies GEV firstly to automated surface observing system (ASOS) to estimate extreme value and then applies IDW to produce high-resolution extreme values. Second experiment (EXP2) is same as EXP1, but using PRISM to make the high-resolution extreme value instead of IDW. Third experiment (EXP3) firstly applies PRISM to ASOS to produce the high-resolution temperature field, and then applies GEV method to make high resolution extreme value data. By comparing these 3 experiments with extreme values obtained from observation data, we find that EXP3 shows the best performance to estimate extreme values of maximum and minimum temperatures, followed by EXP1 and EXP2. It is revealed that EXP1 and EXP2 have a limitation to estimate the extreme value at each grid point correctly because the extreme values of these experiments with 30 m-resolution are calculated from only 60 extreme values obtained from ASOS. On the other hand, the extreme value of EXP3 is similar to observation compared to others, since EXP3 produces 30m-resolution daily temperature through PRISM, and then applies GEV to that result at each grid point. This result indicates that the quality of statistically produced high-resolution extreme values which are estimated from observation data is different depending on the combination and procedure order of statistical methods.

Development of gap filling technique for statistical downscaling of cimate change scenario data (기후변화 시나리오 자료의 통계적 상세화를 위한 결측자료 보정 기법 개발)

  • Cho, Jaepil;Kim, Kwang-Hyung;Park, Jihoon
    • Proceedings of the Korea Water Resources Association Conference
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    • 2019.05a
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    • pp.16-16
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    • 2019
  • 기후변화 시나리오 및 계절예측 자료를 포함한 기후정보를 수자원 분야에 활용하기 위해서는 기후정보의 시 공간적인 상세화(donwscaling)을 필요로 한다. 상세화의 경우 역학적 상세화와 통계학적 상세화로 구분될 수 있으며, 통계학적 상세화를 위해서는 대상 지역의 기후특성을 대표할 수 있는 장기 관측 자료의 확보가 중요하다. 국내의 경우에는 자동기상관측장비(Automatic Weather System, AWS)와 종관기상관측장비(Automatic Synoptic Observation System, ASOS)로 부터 수집된 기상관측자료를 사용할 수 있으나 기후변화 시나리오의 통계적 상세화를 위해서는 30년 이상의 자료 기간을 포함하는 ASOS 자료가 적합하다. 하지만 개발도상국과 같이 기상관측기반이 열악한 지역에서는 잦은 결측 등으로 인하여 품질이 좋은 관측자료의 획득이 어려운 상황이다. 따라서 본 연구에서는 측이 포함된 장기 기상관측 자료로부터 대상 지역의 기후특성을 재현할 수 있도록 기본적인 QC(Quality Control)을 거쳐 결측 자료를 보완할 수 있는 기법 및 R 기반패키지를 개발하여 적용성을 평가하였다. 개발된 기법의 적용성 평가를 위해서 기상청에서 QC를 통해 제공하고 있는 60개 ASOS 지점의 관측자료 중 강수량과 기온 변수를 사용하였다. 최대 50%까지의 현실적인 결측 패턴을 임의로 생성하기 위해 실제 개발도상국 관측자료의 일단위 결측 패턴을 이용하였다. 자료의 QC는 관측일 누락/중복 및 문자형 관측값 등 기본적인 오류 검사, 기온의 경우 물리적 허용 범위에 대한 검사, 최고기온과 최저기온의 비교 및 계측기 오작동에 의한 동일한 값의 반복 등을 포함한 내적 일치성 검사를 우선적으로 수행한다. 이후 결측값에 대해서 인근 기상관측소와의 상관성 분석 결과를 기반으로 결측값을 채우고, 최종적으로는 다양한 위성자료 및 재분석 자료 중에서 일단위 기후특성의 재현성 평가를 통해 선정된 격자형 자료와의 상관성 분석 결과를 기반으로 결측값을 보정하였다. 기온의 경우는 결측률이 높더라도 월평균 기후특성에 큰 영향을 미치지 않았지만 강수의 경우에는 5% 이상의 결측이 발생하는 경우 월평균 강수량에 영향을 미쳐 지역의 강수량을 과소 추정하는 결과를 보였다. 개발된 QC 기법을 강수 자료에 적용한 결과 월평균 기후특성을 잘 복원하는 결과를 보였지만, 일단위 강우 사상의 재현에 있어서는 미흡한 결과를 보였다.

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Statistical Analyses of the Flowering Dates of Cherry Blossom and the Peak Dates of Maple Leaves in South Korea Using ASOS and MODIS Data

  • Kim, Geunah;Kang, Jonggu;Youn, Youjeong;Chun, Junghwa;Jang, Keunchang;Won, Myoungsoo;Lee, Yangwon
    • Korean Journal of Remote Sensing
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    • v.38 no.1
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    • pp.57-72
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    • 2022
  • In this paper, we aimed to examine the flowering dates of cherry blossom and the peak dates of maple leaves in South Korea, by the combination of temperature observation data from ASOS (Automated Surface Observing System) and NDVI (Normalized Difference Vegetation Index) from MODIS (Moderate Resolution Imaging Spectroradiometer). The more recent years, the faster the flowering dates and the slower the peak dates. This is because of the impacts of climate change with the increase of air temperature in South Korea. By reflecting the climate change, our statistical models could reasonably predict the plant phenology with the CC (Correlation Coefficient) of 0.870 and the MAE (Mean Absolute Error) of 3.3 days for the flowering dates of cherry blossom, and the CC of 0.805 and the MAE of 3.8 for the peak dates of maple leaves. We could suppose a linear relationship between the plant phenology DOY (day of year) and the environmental factors like temperature and NDVI, which should be inspected in more detail. We found that the flowering date of cherry blossom was closely related to the monthly mean temperature of February and March, and the peak date of maple leaves was much associated with the accumulated temperature. Amore sophisticated future work will be required to examine the plant phenology using higher-resolution satellite images and additional meteorological variables like the diurnal temperature range sensitive to plant phenology. Using meteorological grid can help produce the spatially continuous raster maps for plant phenology.

Accuracy Assessment of Precipitation Products from GPM IMERG and CAPPI Ground Radar over South Korea

  • Imgook Jung;Sungwon Choi;Daeseong Jung;Jongho Woo;Suyoung Sim;Kyung-Soo Han
    • Korean Journal of Remote Sensing
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    • v.40 no.3
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    • pp.269-274
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    • 2024
  • High-quality precipitation data are crucial for various industries, including disaster prevention. In South Korea, long-term high-quality data are collected through numerous ground observation stations. However, data between these stations are reprocessed into a grid format using interpolation methods, which may not perfectly match actual precipitation. A prime example of real-time observational grid data globally is the Integrated Multi-satellite Retrievals for Global Precipitation Measurement (GPM IMERG) from National Aeronautics and Space Administration (NASA), while in South Korea, ground radar data are more commonly used. GPM and ground radar data exhibit distinct differences due to their respective processing methods. This study aims to analyze the characteristics of GPM and Constant Altitude Plan Position Indicator(CAPPI),representative real-time grid data, by comparing them with ground-observed precipitation data. The study period spans from 2021 to 2022, focusing on hourly data from Automated Synoptic Observing System (ASOS) sites in South Korea. The GPM data tend to underestimate precipitation compared to ASOS data, while CAPPI shows errors in estimating low precipitation amounts. Through this comparative analysis, the study anticipates identifying key considerations for utilizing these data in various applied fields, such as recalculating design rainfall, thereby aiding researchers in improving prediction accuracy by using appropriate data.

Calculation of Soil Moisture and Evapotranspiration of KLDAS applying Ground-Observed Meteorological Data (지상관측 기상자료를 적용한 KLDAS(Korea Land Data Assimilation System)의 토양수분·증발산량 산출)

  • Park, Gwangha;Kye, Changwoo;Lee, Kyungtae;Yu, Wansik;Hwang, Eui-ho;Kang, Dohyuk
    • Korean Journal of Remote Sensing
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    • v.37 no.6_1
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    • pp.1611-1623
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    • 2021
  • Thisstudy demonstratessoil moisture and evapotranspiration performance using Korea Land Data Assimilation System (KLDAS) under Korea Land Information System (KLIS). Spin-up was repeated 8 times in 2018. In addition, low-resolution and high-resolution meteorological data were generated using meteorological data observed by Korea Meteorological Administration (KMA), Rural Development Administration (RDA), Korea Rural Community Corporation (KRC), Korea Hydro & Nuclear Power Co.,Ltd. (KHNP), Korea Water Resources Corporation (K-water), and Ministry of Environment (ME), and applied to KLDAS. And, to confirm the degree of accuracy improvement of Korea Low spatial resolution (hereafter, K-Low; 0.125°) and Korea High spatial resolution (hereafter, K-High; 0.01°), soil moisture and evapotranspiration to which Modern-Era Retrospective analysis for Research and Applications, version 2 (MERRA-2) and ASOS-Spatial (ASOS-S) used in the previous study were applied were evaluated together. As a result, optimization of the initial boundary condition requires 2 time (58 point), 3 time (6 point), and 6 time (3 point) spin-up for soil moisture. In the case of evapotranspiration, 1 time (58 point) and 2 time (58 point) spin-ups are required. In the case of soil moisture to which MERRA-2, ASOS-S, K-Low, and K-High were applied, the mean of R2 were 0.615, 0.601, 0.594, and 0.664, respectively, and in the case of evapotranspiration, the mean of R2 were 0.531, 0.495, 0.656, and 0.677, respectively, indicating the accuracy of K-High was rated as the highest. The accuracy of KLDAS can be improved by securing a large number of ground observation data through the results of this study and generating high-resolution grid-type meteorological data. However, if the meteorological condition at each point is not sufficiently taken into account when converting the point data into a grid, the accuracy is rather lowered. For a further study, it is expected that higher quality data can be produced by generating and applying grid-type meteorological data using the parameter setting of IDW or other interpolation techniques.