Global S&T Development Trend Analysis Platform of Resources and Environment
DOI | 10.1002/2017JD027531 |
Hydrometeorology as an Inversion Problem: Can River Discharge Observations Improve the Atmosphere by Ensemble Data Assimilation? | |
Sawada, Yohei1,2; Nakaegawa, Tosiyuki2; Miyoshi, Takemasa1,3,4 | |
2018-01-27 | |
发表期刊 | JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES
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ISSN | 2169-897X |
EISSN | 2169-8996 |
出版年 | 2018 |
卷号 | 123期号:2页码:848-860 |
文章类型 | Article |
语种 | 英语 |
国家 | Japan; USA |
英文摘要 | We examine the potential of assimilating river discharge observations into the atmosphere by strongly coupled river-atmosphere ensemble data assimilation. The Japan Meteorological Agency's Non-Hydrostatic atmospheric Model (JMA-NHM) is first coupled with a simple rainfall-runoff model. Next, the local ensemble transform Kalman filter is used for this coupled model to assimilate the observations of the rainfall-runoff model variables into the JMA-NHM model variables. This system makes it possible to do hydrometeorology backward, i.e., to inversely estimate atmospheric conditions from the information of river flows or a flood on land surfaces. We perform a proof-of-concept Observing System Simulation Experiment, which reveals that the assimilation of river discharge observations into the atmospheric model variables can improve the skill of the short-term severe rainfall forecast. |
英文关键词 | strongly coupled data assimilation hydrometeorology river discharge ensemble Kalman filter |
领域 | 气候变化 |
收录类别 | SCI-E |
WOS记录号 | WOS:000425520200014 |
WOS关键词 | TRANSFORM KALMAN FILTER ; NONHYDROSTATIC MESOSCALE MODEL ; SOIL-MOISTURE OBSERVATIONS ; SEVERE WEATHER PREDICTION ; BIG DATA ASSIMILATION ; INTERMEDIATE AGCM ; FORECAST SYSTEM ; TIBETAN PLATEAU ; ECMWF MODEL ; RAINFALL |
WOS类目 | Meteorology & Atmospheric Sciences |
WOS研究方向 | Meteorology & Atmospheric Sciences |
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/33148 |
专题 | 气候变化 |
作者单位 | 1.RIKEN, Adv Inst Computat Sci, Kobe, Hyogo, Japan; 2.Japan Meteorol Agcy, Meteorol Res Inst, Tsukuba, Ibaraki, Japan; 3.Univ Maryland, Dept Atmospher & Ocean Sci, College Pk, MD 20742 USA; 4.Japan Agcy Marine Earth Sci & Technol, Yokohama, Kanagawa, Japan |
推荐引用方式 GB/T 7714 | Sawada, Yohei,Nakaegawa, Tosiyuki,Miyoshi, Takemasa. Hydrometeorology as an Inversion Problem: Can River Discharge Observations Improve the Atmosphere by Ensemble Data Assimilation?[J]. JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES,2018,123(2):848-860. |
APA | Sawada, Yohei,Nakaegawa, Tosiyuki,&Miyoshi, Takemasa.(2018).Hydrometeorology as an Inversion Problem: Can River Discharge Observations Improve the Atmosphere by Ensemble Data Assimilation?.JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES,123(2),848-860. |
MLA | Sawada, Yohei,et al."Hydrometeorology as an Inversion Problem: Can River Discharge Observations Improve the Atmosphere by Ensemble Data Assimilation?".JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES 123.2(2018):848-860. |
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