지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
초록· 키워드
오류제보하기
Although the Radar-AWS Rainrate (RAR) calculation system operated by Korea Meteorological Administration estimated precipitation using 2-dimensional composite components of single polarization radars, this system has several limitations in estimating the precipitation accurately. To to overcome limitations of the RAR system, the Korea Meteorological Administration developed and operated the RMQ (Radar-based Multi-sensor Quantitative Precipitation Estimation) system, the improved version of NMQ (National Mosaic and Multi-sensor Quantitative Precipitation Estimation) system of NSSL (National Severe Storms Laboratory) for the Korean Peninsula. This study introduced the RMQ system domestically for the first time and verified the precipitation estimation performance of the RMQ system. The RMQ system consists of 4 main parts as the process of handling the single radar data, merging 3D reflectivity, QPE, and displaying result images. The first process (handling of the single radar data) has the pre-process of a radar data (transformation of data format and quality control), the production of a vertical profile of reflectivity and the correction of bright-band, and the conduction of hydrid scan reflectivity. The next process (merger of 3D reflectivity) produces the 3D composite reflectivity field after correcting the quality controlled single radar reflectivity. The QPE process classifies the precipitation types using multi-sensor information and estimates quantitative precipitation using several Z-R relationships which are proper for precipitation types. This process also corrects the precipitation using the AWS position with local gauge correction technique. The last process displays the final results transformed into images in the web-site. This study also estimated the accuracy of the RMQ system with five events in 2012 summer season and compared the results of the RAR (Radar-AWS Rainrate) and RMQ systems. The RMQ system (2.36 mm hr<SUP>?1</SUP> in RMSE on average) is superior to the RAR system (8.33 mm hr<SUP>?1</SUP> in RMSE) and improved by 73.25% in RMSE and 25.56% in correlation coefficient on average. The precipitation composite field images produced by the RMQ system are almost identical to the AWS (Automatic Weather Statioin) images. Therefore, the RMQ system has contributed to improve the accuracy of precipitation estimation using weather radars and operation of the RMQ system in the work field in future enables to cope with the extreme weather conditions actively.
목차
Abstract
1. 서론
2. 레이더기반 다중센서활용 강수추정 시스템
3. 레이더기반 다중센서활용 강수추정시스템의 검증
4. 결론
REFERENCES
참고문헌 (19)
참고문헌 신청
1. [학술대회논문] - Cha, J. -W. / 2013 / Improvement of the Radar-AWS Rainrate calculation system using the Local Gauge Correction (LGC) method / Proceedings of the 2013Spring Meeting of Korea Meteorological Society : 104 ~ 105
2. [학술대회논문] - Chung, C.-K. / 2007 / Improvement of the Radar-AWS Rainrate calculation system using the dual fit method / Proceedings of the 2007 Autumn Meeting of Korea Meteorological Society : 114 ~ 115
3. [학술지(정기간행물)] - Fulton, R. A. / 1998 / The WSR-88D rainfall algorithm / Wea. Forecasting 13 : 377 ~ 395
4. [보고서] - Korea Meteorological Administration / 2012 / Development of radar-based multi-sensors quantitative precipitation estimation technical report
5. [학술지(정기간행물)] - Lakshmanan, V. / 2010 / A technique to censor biological echoes in weather radar images / J. Appl. Meteor. Climatol. 49 : 453 ~ 462
2. [학술대회논문] - Chung, C.-K. / 2007 / Improvement of the Radar-AWS Rainrate calculation system using the dual fit method / Proceedings of the 2007 Autumn Meeting of Korea Meteorological Society : 114 ~ 115
3. [학술지(정기간행물)] - Fulton, R. A. / 1998 / The WSR-88D rainfall algorithm / Wea. Forecasting 13 : 377 ~ 395
4. [보고서] - Korea Meteorological Administration / 2012 / Development of radar-based multi-sensors quantitative precipitation estimation technical report
5. [학술지(정기간행물)] - Lakshmanan, V. / 2010 / A technique to censor biological echoes in weather radar images / J. Appl. Meteor. Climatol. 49 : 453 ~ 462
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UCI(KEPA) : I410-ECN-0101-2015-450-002731605