Global S&T Development Trend Analysis Platform of Resources and Environment
DOI | 10.1029/2019GL084771 |
Rainfall Estimation From Ground Radar and TRMM Precipitation Radar Using Hybrid Deep Neural Networks | |
Chen, Haonan1,2; Chandrasekar, V1; Tan, Haiming1; Cifelli, Robert2 | |
2019-09-11 | |
发表期刊 | GEOPHYSICAL RESEARCH LETTERS |
ISSN | 0094-8276 |
EISSN | 1944-8007 |
出版年 | 2019 |
文章类型 | Article;Early Access |
语种 | 英语 |
国家 | USA |
英文摘要 | Remote sensing of precipitation is critical for regional, continental, and global water and climate research. This study develops a deep learning mechanism to link between point-wise rain gauge measurements, ground-based, and spaceborne radar reflectivity observations. Two neural network models are designed to construct a hybrid rainfall system, where the ground radar is used to bridge the scale gaps between rain gauge and satellite. The first model is trained for ground radar using rain gauge data as target labels, whereas the second model is for spaceborne Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar (PR) using ground radar estimates as training labels. Data from 1 year of observations in Florida during 2009 are utilized to illustrate the application of this hybrid rainfall system. Validation using independent data in 2009, as well as 2-year comparison against the standard PR products, demonstrates the promising performance and generality of this innovative rainfall algorithm. |
英文关键词 | rain gauge ground radar TRMM PR neural network hybrid system rainfall estimation |
领域 | 气候变化 |
收录类别 | SCI-E |
WOS记录号 | WOS:000486264400001 |
WOS关键词 | ALGORITHM ; VALIDATION ; FRAMEWORK |
WOS类目 | Geosciences, Multidisciplinary |
WOS研究方向 | Geology |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://119.78.100.173/C666/handle/2XK7JSWQ/186989 |
专题 | 气候变化 |
作者单位 | 1.Colorado State Univ, Dept Elect & Comp Engn, Ft Collins, CO 80523 USA; 2.NOAA, Earth Syst Res Lab, Boulder, CO 80305 USA |
推荐引用方式 GB/T 7714 | Chen, Haonan,Chandrasekar, V,Tan, Haiming,et al. Rainfall Estimation From Ground Radar and TRMM Precipitation Radar Using Hybrid Deep Neural Networks[J]. GEOPHYSICAL RESEARCH LETTERS,2019. |
APA | Chen, Haonan,Chandrasekar, V,Tan, Haiming,&Cifelli, Robert.(2019).Rainfall Estimation From Ground Radar and TRMM Precipitation Radar Using Hybrid Deep Neural Networks.GEOPHYSICAL RESEARCH LETTERS. |
MLA | Chen, Haonan,et al."Rainfall Estimation From Ground Radar and TRMM Precipitation Radar Using Hybrid Deep Neural Networks".GEOPHYSICAL RESEARCH LETTERS (2019). |
条目包含的文件 | 条目无相关文件。 |
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