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      KCI등재 SCIE SCOPUS

      McGill Algorithm for Precipitation Nowcasting by Lagrangian Extrapolation (MAPLE) Applied to the South Korean Radar Network. Part I: Sensitivity Studies of the Variational Echo Tracking (VET) Technique

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      https://www.riss.kr/link?id=A103795903

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      다국어 초록 (Multilingual Abstract)

      A Variational Echo Tracking (VET) technique has been applied to four months of archived data from the South Korean radar network in order to examine the influence of the various user-selectable parameters on the skill of the resulting 20-min to 4-h nowcasts. The latter are computed over a (512 × 512) array at 2-km resolution. After correcting the original algorithm to take into account the motion of precipitation across the boundaries of such a smaller radar network,we concluded that the set of default input parameters initially assumed is very close to the optimum combination. Decreasing to (5 × 5) or increasing to (50 × 50) the default vector density of (25 × 25), using two or three maps for velocity determination, varying the relative weights for the constraints of conservation of reflectivity and of the smoothing of the velocity vectors, and finally the application of temporal smoothing all had only marginal effects on the skill of the forecasts. The relatively small sensitivity to significant variations of the VET default parameters is a direct consequence of the fact that the major source of the loss in forecast skill cannot be attributed to errors in the forecast motion, but to the unpredictable nature of the storm growth and decay. Changing the time interval between maps, from 20to 10 minutes, and significantly increasing the reflectivity threshold from 15 to 30 dBZ had a more noticeable reduction on the forecast skill. Comparisons with the Eulerian “zero velocity” forecast and with a "single" vector forecast have also been performed in order to determine the accrued skill of the VET algorithm. Because of the extensive stratiform nature of the precipitation areas affecting the Korean peninsula, the increased skill is not as large as may have been anticipated. This can be explained by the greater extent of the precipitation systems relative to the size of the radar coverage domain
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      A Variational Echo Tracking (VET) technique has been applied to four months of archived data from the South Korean radar network in order to examine the influence of the various user-selectable parameters on the skill of the resulting 20-min to 4-h no...

      A Variational Echo Tracking (VET) technique has been applied to four months of archived data from the South Korean radar network in order to examine the influence of the various user-selectable parameters on the skill of the resulting 20-min to 4-h nowcasts. The latter are computed over a (512 × 512) array at 2-km resolution. After correcting the original algorithm to take into account the motion of precipitation across the boundaries of such a smaller radar network,we concluded that the set of default input parameters initially assumed is very close to the optimum combination. Decreasing to (5 × 5) or increasing to (50 × 50) the default vector density of (25 × 25), using two or three maps for velocity determination, varying the relative weights for the constraints of conservation of reflectivity and of the smoothing of the velocity vectors, and finally the application of temporal smoothing all had only marginal effects on the skill of the forecasts. The relatively small sensitivity to significant variations of the VET default parameters is a direct consequence of the fact that the major source of the loss in forecast skill cannot be attributed to errors in the forecast motion, but to the unpredictable nature of the storm growth and decay. Changing the time interval between maps, from 20to 10 minutes, and significantly increasing the reflectivity threshold from 15 to 30 dBZ had a more noticeable reduction on the forecast skill. Comparisons with the Eulerian “zero velocity” forecast and with a "single" vector forecast have also been performed in order to determine the accrued skill of the VET algorithm. Because of the extensive stratiform nature of the precipitation areas affecting the Korean peninsula, the increased skill is not as large as may have been anticipated. This can be explained by the greater extent of the precipitation systems relative to the size of the radar coverage domain

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      참고문헌 (Reference)

      1 Turner, B. J., "redictability of precipitation from continental radar images. Part III: Operational nowcasting implementation (MAPLE)" 43 : 231-248, 2004

      2 Ebert, E. E., "Verification of nowcasts from the WWRP Sydney 2000 Forecast Demonstration Project" 19 : 73-96, 2004

      3 Pierce, C. E., "The nowcasting of precipitation during Sydney 2000: An appraisal of the QPF algorithms" 19 : 7-21, 2004

      4 Bellon, A., "The evaluation of two years of realtime operation of a short-term precipitation forecasting procedure (SHARP)" 17 : 1778-1787, 1978

      5 Bellon, A., "The accuracy of short-term radar rainfall forecasts" 70 : 35-49, 1984

      6 Dixon, M. J., "TITAN: Thunderstorm Identification, Tracking, Analysis, and Nowcasting – A radar-based methodology" 10 : 785-797, 1993

      7 Wilson, J. W., "Sydney 2000 Forecast Demonstration Project: Convective storm nowcasting" 19 : 131-150, 2004

      8 Germann, U., "Scale-dependence of the predictability of precipitation from continental radar images. Part II: Probability forecasts" 43 : 74-89, 2004

      9 Germann, U., "Scale-dependence of the predictability of precipitation from continental radar images. Part I: Description of the methodology" 130 : 2859-2873, 2002

      10 Laroche, S., "Retrievals of horizontal winds from single-Doppler clear-air data by methods of cross-correlation and variational analysis" 12 : 721-738, 1995

      1 Turner, B. J., "redictability of precipitation from continental radar images. Part III: Operational nowcasting implementation (MAPLE)" 43 : 231-248, 2004

      2 Ebert, E. E., "Verification of nowcasts from the WWRP Sydney 2000 Forecast Demonstration Project" 19 : 73-96, 2004

      3 Pierce, C. E., "The nowcasting of precipitation during Sydney 2000: An appraisal of the QPF algorithms" 19 : 7-21, 2004

      4 Bellon, A., "The evaluation of two years of realtime operation of a short-term precipitation forecasting procedure (SHARP)" 17 : 1778-1787, 1978

      5 Bellon, A., "The accuracy of short-term radar rainfall forecasts" 70 : 35-49, 1984

      6 Dixon, M. J., "TITAN: Thunderstorm Identification, Tracking, Analysis, and Nowcasting – A radar-based methodology" 10 : 785-797, 1993

      7 Wilson, J. W., "Sydney 2000 Forecast Demonstration Project: Convective storm nowcasting" 19 : 131-150, 2004

      8 Germann, U., "Scale-dependence of the predictability of precipitation from continental radar images. Part II: Probability forecasts" 43 : 74-89, 2004

      9 Germann, U., "Scale-dependence of the predictability of precipitation from continental radar images. Part I: Description of the methodology" 130 : 2859-2873, 2002

      10 Laroche, S., "Retrievals of horizontal winds from single-Doppler clear-air data by methods of cross-correlation and variational analysis" 12 : 721-738, 1995

      11 Germann, U., "Predictability of precipitation from continental radar images. Part IV: Limits to prediction" 63 : 2092-2108, 2006

      12 Browning, K. A., "On the forecasting of frontal rain using a weather radar network" 110 : 534-552, 1982

      13 Wilson, J. W., "Nowcasting thunderstorms: A status report" 79 : 2079-2099, 1998

      14 Golding, B. W., "Nimrod: A system for generating automated very short range forecasts" 5 : 1-16, 1998

      15 Collier, C. G., "NIMROD- A system for nowcasting and initialization for modeling using regional observational data. Preprints" 21-24, 1991

      16 Mueller, C., "NCAR Auto-Nowcaster System" 18 : 545-561, 2003

      17 Pierce, C. E., "GANDOLF: A system for generating automated nowcasts of convective precipitation" 7 : 341-360, 2000

      18 Navon, I. M., "Conjugate-gradient method for largescale minimization in meteorology" 115 : 1479-1502, 1987

      19 Tsonis, A. A., "An evaluation of extrapolation techniques for the short-term prediction of rain amounts" 19 : 54-65, 1981

      20 Rinehart, R. E., "A pattern recognition technique for use with conventional weather radar to determine internal storm motions" 13 : 119-134, 1981

      21 Seed, A. W., "A dynamic and spatial scaling approach to advection forecasting" 42 : 381-388, 2003

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      학술지 이력

      학술지 이력
      연월일 이력구분 이력상세 등재구분
      2023 평가예정 해외DB학술지평가 신청대상 (해외등재 학술지 평가)
      2020-11-03 학술지명변경 한글명 : 한국기상학회지 -> Asia-Pacific Journal of Atmospheric Sciences KCI등재
      2020-01-01 평가 등재학술지 유지 (해외등재 학술지 평가) KCI등재
      2011-01-01 평가 등재학술지 유지 (등재유지) KCI등재
      2009-01-01 평가 등재학술지 유지 (등재유지) KCI등재
      2008-02-05 학술지명변경 외국어명 : 미등록 -> Asia-Pacific Journal of Atmospheric Sciences KCI등재
      2007-08-13 학술지명변경 한글명 : 한국기상학회지 -> Journal of the Korean Meteorological Society(한국기상학회지) KCI등재
      2007-01-01 평가 등재학술지 유지 (등재유지) KCI등재
      2005-01-01 평가 등재학술지 유지 (등재유지) KCI등재
      2002-01-01 평가 등재학술지 선정 (등재후보2차) KCI등재
      1999-07-01 평가 등재후보학술지 선정 (신규평가) KCI등재후보
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      학술지 인용정보

      학술지 인용정보
      기준연도 WOS-KCI 통합IF(2년) KCIF(2년) KCIF(3년)
      2016 1.81 0.51 1.31
      KCIF(4년) KCIF(5년) 중심성지수(3년) 즉시성지수
      1.11 0.95 0.771 0.32
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