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기상조절 및 기상장비 기술개발 연구

  • 주관연구기관

    국립기상연구소

  • 연구책임자

    조천호

  • 참여연구자

    장기호   차주완   정재원   배진영   정진임   양하영   서성규   강선영   김유철   김연희   김기훈   ...  

  • 보고서유형

    최종보고서

  • 발행국가

    대한민국

  • 언어

    한국어

  • 발행년월

    2009-12

  • 주관부처

    기상청

  • 사업 관리 기관

    한국연구재단

  • 등록번호

    TRKO201000000779

  • DB 구축일자

    2013-04-18

  • 초록 


    In 2008, National Institute of Meteorological Research(NIMR) has conducted the first airborne target (Yongpyeong) cloud seeding e...

    In 2008, National Institute of Meteorological Research(NIMR) has conducted the first airborne target (Yongpyeong) cloud seeding experiment. The experiment was conducted three times on March 3, 4 and 14, 2008 to enhance snowfall at Yongpyeong areas, Gangwon. In short, in spite of the first airborne target snow enhancement experiment, two of them were successful. Especially, the 35 GHz Ka-band airborne radar (Millisys Inc.) on-board the aircraft has been first used to validate the effect of airborne cloud seeding.
    Recently March in 2009, NIMR has conducted the airborne target cloud seeding experiment for the scientific reproducibility. The experiment was conducted three times on February 23, March 23, and March 30, 2009 to enhance the precipitation over areas of Yongpyeong and Gwangdong dam, Gangwon. The cloud seeding seeding experimental results are analyzed by an observation network composed of the Microwave Radiometer (MWR), Micro Rain Radar (MRR), the optical disdrometer (PARSIVEL), and the 35 GHz Ka-band airborne radar on-board the aircraft has been used to validate the effect of airborne cloud seeding. After seeding, the airborne radar reflectivity change had been detected by scanning along the wind direction before and after cloud seeding, and then the ground snow increment was observed at the target region in two experiments of six AgI seeding ones. We suggest that this rapid validation of airborne radar for the cloud seeding is useful for such as the feasibility study before large-scale cloud seeding project.
    We have developed automatic sky condition observation system which is able to observe fractional sky cover and cloud-base height. This instrument is equipped with imaging camera and its cover and washing, drying, and heating system, ventilation, allowing to be applicable to environment of heavy snowfall, rainfall, heat, wind, and Asian dust. Fractional sky cover retrieval has the processes of pre-processing to remove solar signals and marker extraction to merge the pixels in uncertain areas and determine them with hierarchical queue. Cloud-base height retrieval is based on the measurement of distance between the instrument and target cloud with two stereo cameras. Capability of the automatic sky condition observation system installed at Daegwanryeong Cloud Physics Observation Station (CPOS) were evaluated through comparison of cloud-base heights with those from ceilometer at Daegwanryeong Meteorological Station 4 km off from CPOS.
    Cloud-base heights from our automatic sky condition observation system exhibit high consistency with those from ceilometer: About 80% of them data were within 20% of those from ceilometer. They also exhibit 91% accuracy in the comparison with WMO CODE. The performance tests validate the capability of the automatic sky condition observation system and suggest that long term tests in diverse meterological environments will improve the accuracy of the retrievals of sky cover and cloud-base height.
    In this study, we can get the intercomparisons site for comparison of different snow depth observation systems. Especially, this study can give the pivotal information about objective and accurate snow depth observation type using by intensive comparisons of ultra sonic, laser, video, and weight type.


    국립기상연구소는 2008년 국내에서는 처음으로 강원도 평창군에 위치한 용평스키장을 목표로하여 인공강우 비행실험을 실시하였다. 비행실험은 2008년 3월 3일, 4일, 14일 총 세 차례에 걸쳐 실시되었다. 2008년 비행실험에서 총...

    국립기상연구소는 2008년 국내에서는 처음으로 강원도 평창군에 위치한 용평스키장을 목표로하여 인공강우 비행실험을 실시하였다. 비행실험은 2008년 3월 3일, 4일, 14일 총 세 차례에 걸쳐 실시되었다. 2008년 비행실험에서 총 세 차례 비행실험 중 두 차례에 걸쳐 인공증설 실험에 성공하였다. 특히 2008년 실험은 인공강우 비행실험에 광주과기원 벤처기업인 (주)밀리시스에서 개발한 35GHz Ka-밴드 항공레이더를 이용한 검증방법을 세계에서 처음으로 시도하여 총 세 차례 실험 중 한차례에 걸쳐 인공강우 비행실험의 물리적 효과를 확인하였다.
    최근 국립기상연구소는 2008년 비행실험의 과학적 재현성 확보를 위한 인공강우 목표지역 비행실험을 실시하였다. 2009년 비행실험은 2009년 2월 23일, 3월 23일, 3월 30일 총 세 차례에 걸쳐 실시되었고, 단일 목표지역을 용평과 강원도 태백에 위치한 광동댐으로 이중 목표지역으로 하여 실험을 수행하였다. 2009년 인공강우 목표지역 비행실험의 시딩효과를 검증하기 위해 Ka-밴드 항공레이더를 비행기 동체하단에 설치하여 시딩 전 후의 구름변화를 관측하였다. 또 한 지상에 광학 강수입자측정기(Disdrometer PARSIVEL), 연직강우레이더(Micro Rain Radar, MRR) 그리고 라디오미터(MicroWave Radiometer, MWR)을 설치하여 시딩 전 후를 관측 비교 분석하였다. 2009년 비행실험은 총 세 차례 실시되어 요오드화은 6회 실험 중 2회에 걸쳐 인공강우 실험에 성공하였다.
    운량, 운고 등의 하늘상태관측을 할 수 있는 자동화된 시스템을 개발하였다. 하늘상태관측시스템은 폭염, 혹한, 눈, 비, 강풍 , 황사 등의 상황에서도 현장 적용이 가능하도록, 카메라 보호 구조물, 세척장치, 건조장치, 환기장치, 히팅시스템 등을 가지고 있다. 운량 추출알고리즘은 전처리과정에서 태양영역을 제거하였으며, 2차 우선 순위에 기반한 불확실 영역 화소들의 병합 하였고, 계층적 큐를 이용하여 구현하였다. 운저추출은 두 대의 카메라(Stereo Camera)를 가지고 한 지점의 목표물(구름)을 관측하여 거리를 측정하는 원리이며 이것은 사람이 물체에 대한 거리감을 측정할 수 있는 원리로 설명될 수 있다. 성능실험은 구대관령기상대와 부산에서 실시되었는데, 목측결과와 비교하기에는 목측결과에 대한 신뢰성 검토의 필요성이 제기되었다. 그리하여 보다 신뢰성이 확보되는 실로메터와 비교하였는데 실로메터의 높이 값과 20% 오차안에 드는 경우가 83% 였다. WMO CODE 와 비교한 경우는 91% 의 정확도를 보였다. 실험을 통하여 하늘상태 자동 관측시스템의 유용성을 확인할 수 있었으며, 이러한 실험은 보다 실제, 환경에 설치하여 장기간에 걸쳐서 다양한 환경에 적용하여 실시할 필요가 있음을 확인하였다.
    국립기상연구소는 대관령 구름물리 관측소에 적설 자동관측을 위한 다양한 방식에 대한 시범 및 비교 관측지점을 확보하였다. 특히 이 연구에서는 초음파식, 레이저식, 영상식, 무게식에 대한 집증적인 비교를 통해 향후에 보다 객관적이고 정확도 높은 적설방식을 개발 할 수 있는 주요한 자료 제공이 가능할 것이다.


  • 목차(Contents) 

    1. 제 1 장 서론 ...16
    2. 제 2 장 인공강우 목표지역 비행실험 ...18
    3. 제 1 절 서론 ...18
    4. 제 2 절 실험설계 ...20
    5. 1. 실험일의 종관조건 ...20
    6. 2. 비행실험 개념도 ...22
    7. 3. 비행실험 실시 흐름도 ...23...
    1. 제 1 장 서론 ...16
    2. 제 2 장 인공강우 목표지역 비행실험 ...18
    3. 제 1 절 서론 ...18
    4. 제 2 절 실험설계 ...20
    5. 1. 실험일의 종관조건 ...20
    6. 2. 비행실험 개념도 ...22
    7. 3. 비행실험 실시 흐름도 ...23
    8. 4. 실험 장비 및 재료 ...24
    9. 제 3 절 실험 결과 ...27
    10. 1. 1차 비행실험 (2월 23일) ...27
    11. 2. 2차 비행실험 (3월 23일) ...31
    12. 3. 3차 비행실험 (3월 30일) ...36
    13. 제 4 절 요약 및 결론 ...43
    14. 제 3 장 하늘상태 자동 관측시스템 개발 ...45
    15. 제 1 절 서론 ...45
    16. 제 2 절 하늘상태 자동 관측시스템 개발 개념 ...45
    17. 제 3 절 하늘상태 자동 관측시스템 개발 ...46
    18. 1. 개발 개요 ...46
    19. 2. 주요 기기장치 및 관련기술 ...47
    20. 3. 운용 소프트웨어 개발 ...49
    21. 제 4 절 구름정보 추출을 위한 영상처리 알고리즘 개발 ...50
    22. 1. 운량추출 ...50
    23. 2. 운저(고)추출 ...51
    24. 제 5 절 하늘상태 자동 관측시스템 성능실험 ...52
    25. 1. 운량추출 ...52
    26. 2. 운저(고)추출 ...58
    27. 3. 종합적 성능평가 ...62
    28. 제 6 절 요약 및 결론 ...63
    29. 제 4 장 적설 관측 자동화 시험 시스템 개발 기반연구 ...65
    30. 제 1 절 서론 ...65
    31. 제 2 절 관측방식에 따른 적설계 특성 ...66
    32. 1. 영상적설계 ...67
    33. 2. 초음파 적설계 ...68
    34. 3. 레이저 적설계 ...69
    35. 4. 무게식 적설계 ...70
    36. 제 3 절 초음파 적설계와 CCTV 목측적설과의 비교 ...71
    37. 제 4 절 신영상적설계 개발 ...73
    38. 제 5 장 결론 ...75
    39. 참고문헌 ...76
    40. 첨부자료 ...78
    41. LIST OF FIGURES
    42. Fig. 2.1.1 Results of the experiment on March 4, 2008: (a), (b) vertical and horizontal schematic design of the experiment, (c), (d) ka-band airborne radar reflectivity before and after seeding, (e) reflectivity of optical disdrometer ...19
    43. Fig. 2.2.1 Surface weather chart at 00 UTC on February 23, 2009 ...21
    44. Fig. 2.2.2 Surface weather chart at 15 UTC on March 22, 2009 ...21
    45. Fig. 2.2.3 Surface weather chart at 12 UTC on March 30, 2009 ...22
    46. Fig. 2.2.4 Schematic design of the airborne target cloud seeding experiment in 2009 ...23
    47. Fig. 2.2.5 Flow chart of the airborne target cloud seeding experiment in 2009 ...24
    48. Fig. 2.2.6 Cessna 206 ...26
    49. Fig. 2.2.7 35 GHz ka-band airborne radar; installed in the aircraft fuselage lower part ...26
    50. Fig. 2.2.8 Condensation particle counter ...27
    51. Fig. 2.2.9 (left) AgI flare rack and (right) $LN_2$ (351) jet pod ...27
    52. Fig. 2.3.1 Cloud conditions of the experiment region at 10:20 on Feb. 23, 200 ...28
    53. Fig. 2.3.2 Flight route, seeding path and airborne radar scan path at Yongpyeong region by airborne GPS on Feb. 23, 2009 ...28
    54. Fig. 2.3.3 Reflectivity of surface weather radar over Gwangduk mountain (10:00~12:00, LST) ...29
    55. Fig. 2.3.4 Ka-band airborne radar reflectivity of the airborne target cloud seeding experiment in 23 Feb. 2009: (up) before seeding and (down) after seeding ...29
    56. Fig. 2.3.5 Time series of CPC in airspace of Yongpyeong: (up) LN2 seeding experiments, (down) AgI seeding experiments: black line is flight route by airborne GPS on Feb. 23, 2009 ...30
    57. Fig. 2.3.6 Time series of the Yongpyeong PARSIVEL on Feb. 23, 2009 ...31
    58. Fig. 2.3.7 LWC of MRR (a)Eoheul-ri , (b) Daegwalleyong, (c) Yongpyeong ...31
    59. Fig. 2.3.8 Flight route, seeding path and airborne radar scan path at Yongpyeong region by airborne GPS on March 23, 2009 ...32
    60. Fig. 2.3.9 Reflectivity of surface weather radar in Gwangduk mountain (00:00~01:40, LST) ...32
    61. Fig. 2.3.10 Ka-band airborne radar reflectivity of the airborne target(Yongpyeong) cloud seeding experiment on March 23, 2009: (up) before seeding and (down) after seeding ...33
    62. Fig. 2.3.11 Time series of the CPC in airspace of Yongpyeong: black line is flight route by airborne GPS in 23 March 2009 ...33
    63. Fig. 2.3.12 Time series of Yongpyeong PARSIVEL on March 23, 2009 ...33
    64. Fig. 2.3.13 Time series of Yongpyeong MRR reflectivity on March 23, 2009. ...34
    65. Fig. 2.3.14 Plight route, seeding path and airborne radar scan path at Gwangdong darn by airborne GPS on March 23, 2009 ...34
    66. Fig. 2.3.15 Reflectivity of surface weather radar in Gwangduk mountain (00:50~02:00, LST) ...35
    67. Fig. 2.3.16 Ka-band airborne radar reflectivity of the airborne target(Gwangdong dam in Taeback) cloud seeding experiment on March 23, 2009: (up) before seeding and (down) after seeding ...35
    68. Fig. 2.3.17 Time series of 0.5 mm raingauge at Sinki region on March 23, 2009 ...36
    69. Fig. 2.3.18 Time series of the CPC in airspace of Gwangdong dam: black line is flight route by airborne GPS on March 23, 2009 ...36
    70. Fig. 2.3.19 Plight route, seeding path and airborne radar scan path at Yongpyeong region by airborne GPS on March 30, 2009 ...37
    71. Fig. 2.3.20 Reflectivity of surface weather radar in Gwangduk mountain (21:30~22:40, LST) ...38
    72. Fig. 2.3.21 Ka-band airborne radar reflectivity of the airborne target(Yongpyeong) cloud seeding experiment on March 30, 2009: (up) before seeding (down) after seeding ...38
    73. Fig. 2.3.22 Time series of Gangneung Windprofiler and Yongpyeong MRR on March 30, 2009 ...39
    74. Fig. 2.3.23 Time series of Yongpyeong PARSIVEL on March 30, 2009 ...39
    75. Fig. 2.3.24 Time series of the CPC in Yongpyeong: black line is flight route by airborne GPS on March 30, 2009 ...39
    76. Fig. 2.3.25 Flight route, seeding path and airborne radar scan path at Gwangdong dam by airborne GPS on March 30, 2009 ...40
    77. Fig. 2.3.26 Ka-band airborne radar reflectivity of the airborne target(Gwangdong dam) cloud seeding experiment on March 30, 2009: (up) before seeding and (down) after seeding ...41
    78. Fig. 2.3.27 Reflectivity of surface weather radar in Gwangduk mountain (30, 22:50 - 31, 00:50, LST) ...41
    79. Fig. 2.3.28 Time series of 0.5 mm raingauge at Hajang region on March 30, 2009 ...42
    80. Fig. 2.3.29 Time series of the CPC in Gwangdong dam: black line is flight route by airborne GPS on March 30, 2009 ...42
    81. Fig. 3.2.1 Schematic of development of automatic sky condition observation system ...46
    82. Fig. 3.3.1 Prototypes of automatic sky condition observation system ...47
    83. Fig. 3.3.2 Main components of automatic sky condition observation system ...48
    84. Fig. 3.3.3 Control software of automatic sky condition observation system ...49
    85. Fig. 3.3.4 Learning software for automatic sky condition observation system ...49
    86. Fig. 3.4.2 Concept of cloud-base height observation ...51
    87. Fig. 3.4.3 Flow chart of cloud-base height. retrieval ...52
    88. Fig. 3.5.1 Conversion of color image (left) to gray tone image (right) ...53
    89. Fig. 3.5.2 Removal of solar scope from the original image (left) ...53
    90. Fig. 3.5.3 Three levels of cloud brightness observed at night ...54
    91. Fig. 3.5.4 Observed image with cloud fraction 0% in the daytime ...54
    92. Fig. 3.5.5 Observed image with cloud fraction <30% in the daytime ...55
    93. Fig. 3.5.6 Observed image with cloud fraction 30-70% in the daytime ...55
    94. Fig. 3.5.7 Observed image with cloud fraction 100% in the daytime ...56
    95. Fig. 3.5.8 Observed image with high cloud fraction at night ...56
    96. Fig. 3.5.9 Observed image with low cloud fraction at night ...57
    97. Fig. 3.5.10 Left and right images used in cloud-base hight retrievals ...59
    98. Fig. 3.5.11 Areas to be used in image matching ...59
    99. Fig. 3.5.12 Examples of areas for image matching after preprocessing ...59
    100. Fig. 3.5.13 Images observed by the automatic sky condition observation system and retrieved cloud-based heights at Daegwanryeong Cloud Physics Observation Station on June 21. The cloud-based height observed at Daegwanryeong Meteorological Station by ceilometer at 16:00 on June 21 is 1128 m ...60
    101. Fig. 3.5.14 Images observed by the automatic sky condition observation system and retrieved cloud-based heights at Daegwanryeong Cloud Physics Observation Station on June 21. The cloud-based height observed at Daegwanryeong Meteorological Station by ceilometer at 19:00 on June 21 is 6463 m ...61
    102. Fig. 4.1.1 Testbed of automatic snow depth observation system ...65
    103. Fig. 4.2.1 Example of video snow depth observation system ...67
    104. Fig. 4.2.2 Laser snow depth observation system ...69
    105. Fig. 4.3.1 Comparison of snow depth measured by Ultrsonic and CCTV snow depth observation systems at 16, 17, 20 Dec. in Buan.((초): 초음파, (관): CCTV) ...71
    106. Fig. 4.3.2 Comparison of snow depth measured by Ultrsonic and CCTV snow depth observation systems at 16 17, 20 Dec. in Haenam(초: 초음파, (관): CCTV) ...72
    107. Fig. 4.3.3 Comparison of snow depth measured by Ultrsonic and CCTV snow depth observation systems at 16, 17, 20 Dec. in Imsil.((초): 초음파, (관): CCTV) ...72
    108. Fig. 4.3.4 Comparison of snow depth measured by Ultrsonic and CCTV snow depth observation systems at 16, 17, 20 Dec. in Jinan.((초): 초음파, (관): CCTV) ...73
    109. Fig. 4.3.5 Example of CCTV snow depth observation image (광주기상청 제공, 2009.12.31) ...73
    110. LIST OF TABLES
    111. Table 2.2.1 Ground-based observation equipment ...25
    112. Table 2.4.1 Summary of the airborne target cloud seeding experiment in 2009 ...43
    113. Table 2.5.1 Sucess rate of cloud fraction observations by automatic observation system of sky conditions ...58
    114. Table 3.5.2 Comparion of cloud heights observed by automatic sky condition observation system (ASCOS) at Cloud Physics Observation Station and ceilometer and eye-measurement at Daegwanryeong Meteorological Station ...62
    115. Table 2.5.3 Evaluation on performance of automatic sky condition observation system ...63
    116. Table 4.2.1 Comparison of the automatic snow depth observation systems ...66
    117. Table 4.2.2 Comparison of specifications of Ultra sonic snow depth observation system ...68
    118. Table 4.2.3 Specifications of loadcell (CAS SPL-50) (2009, 이부용, 김현철) ...71
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