An Improved Bright Band Identification Algorithm Based on GPM-DPR Ku-Band Reflectivity Profiles
文献类型：期刊论文
| 作者 | Zhu, Ziwei1,2; Qi, Youcun1,2; Zhao, Zhanfeng1,2 |
| 刊名 | IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
 |
| 出版日期 | 2022 |
| 卷号 | 60页码:9 |
| 关键词 | Bright band (BB) identification dual-frequency precipitation radar (DPR) Global Precipitation Measurement mission (GPM) vertical profile of reflectivity (VPR) |
| ISSN号 | 0196-2892 |
| DOI | 10.1109/TGRS.2022.3208892 |
| 通讯作者 | Qi, Youcun(youcun.qi@igsnrr.ac.cn) ; Zhao, Zhanfeng(zhaozhanfeng@igsnrr.ac.cn) |
| 英文摘要 | Bright band (BB) is a layer of enhanced radar reflectivity due to hydrometeor melting and coalescence. BB identification is of high importance in radar quantitative precipitation estimation (QPE) and other applications. The dual-frequency precipitation radar (DPR) onboard the core satellite of the Global Precipitation Measurement mission (GPM) enables new investigations of BB characteristics on a global scale. However, the GPM-DPR operational BB identification algorithm based on the vertical profile of reflectivity (VPR) from single-frequency (SF; Ku-band) or dual-frequency (DF; Ku- and Ka-band) observations still has room for improvement. In the current study, an improved GPM-DPR SF BB identification algorithm is presented based on the detection of inflection points within a given range in a VPR. The improved GPM-DPR SF BB identification algorithm decreases the overestimation (underestimation) error of the BB bottom (top) height identified by the GPM-DPR SF algorithm, from 322 m (-345 m) to 182 m (-211 m), compared to the identifications by the GPM-DPR DF algorithm. The GPM-DPR SF will misestimate the depth of the melting layer, and the reflectivity difference between BB bottom (top) and BB peak to about 1.5 (3.5) dB, which will lead to misunderstanding the vertical physical variation of the precipitation particles. The validation through beta(HV) derived from WSR-88D observations in the conterminous United States (CONUS) demonstrates that the GPM-DPR DF algorithm is of higher accuracy, and the improved GPM-DPR SF algorithm performs better than the GPM-DPR SF algorithm. The new algorithm will contribute to hydrometeor phase classification and the studies on BB characteristics. |
| WOS关键词 | RADAR QPE ERRORS ; MELTING-LAYER ; CLASSIFICATION ALGORITHM ; VERTICAL PROFILES ; PRECIPITATION ; ONBOARD ; RAIN |
| 资助项目 | National Key Research and Development Project[2018YFC1507505] ; Strategic Priority Research Program of Chinese Academy of Sciences[XDA2006040101] ; Hundred Talent Program |
| WOS研究方向 | Geochemistry & Geophysics ; Engineering ; Remote Sensing ; Imaging Science & Photographic Technology |
| 语种 | 英语 |
| WOS记录号 | WOS:000866495000008 |
| 出版者 | IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC |
| 资助机构 | National Key Research and Development Project ; Strategic Priority Research Program of Chinese Academy of Sciences ; Hundred Talent Program |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/185605]  |
| 专题 | 中国科学院地理科学与资源研究所 |
| 通讯作者 | Qi, Youcun; Zhao, Zhanfeng |
| 作者单位 | 1.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Key Lab Water Cycle & Related Land Surface Proc, Beijing 100101, Peoples R China 2.Univ Chinese Acad Sci, Coll Resources & Environm, Beijing 100049, Peoples R China |
| 推荐引用方式 GB/T 7714 | Zhu, Ziwei,Qi, Youcun,Zhao, Zhanfeng. An Improved Bright Band Identification Algorithm Based on GPM-DPR Ku-Band Reflectivity Profiles[J]. IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING,2022,60:9. |
| APA | Zhu, Ziwei,Qi, Youcun,&Zhao, Zhanfeng.(2022).An Improved Bright Band Identification Algorithm Based on GPM-DPR Ku-Band Reflectivity Profiles.IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING,60,9. |
| MLA | Zhu, Ziwei,et al."An Improved Bright Band Identification Algorithm Based on GPM-DPR Ku-Band Reflectivity Profiles".IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING 60(2022):9. |
入库方式： OAI收割
来源：地理科学与资源研究所
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