DOI: 10.1002/2017JD027531
Scopus记录号: 2-s2.0-85042214712
论文题名: Hydrometeorology as an Inversion Problem: Can River Discharge Observations Improve the Atmosphere by Ensemble Data Assimilation?
作者: Sawada Y. ; Nakaegawa T. ; Miyoshi T.
刊名: Journal of Geophysical Research: Atmospheres
ISSN: 2169897X
出版年: 2018
卷: 123, 期: 2 起始页码: 848
结束页码: 860
语种: 英语
英文关键词: ensemble Kalman filter
; hydrometeorology
; river discharge
; strongly coupled data assimilation
Scopus关键词: atmosphere
; atmospheric modeling
; data assimilation
; data inversion
; ensemble forecasting
; hydrometeorology
; Kalman filter
; rainfall
; rainfall-runoff modeling
; river discharge
; simulation
; transform
; Japan
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. ©2017. American Geophysical Union. All Rights Reserved. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/114670
Appears in Collections: 气候减缓与适应
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作者单位: RIKEN Advanced Institute for Computational Science, Kobe, Japan; Meteorological Research Institute, Japan Meteorological Agency, Tsukuba, Japan; Department of Atmospheric and Oceanic Science, University of Maryland, College Park, MD, United States; Japan Agency for Marine-Earth Science and Technology, Yokohama, Japan
Recommended Citation:
Sawada Y.,Nakaegawa T.,Miyoshi T.. Hydrometeorology as an Inversion Problem: Can River Discharge Observations Improve the Atmosphere by Ensemble Data Assimilation?[J]. Journal of Geophysical Research: Atmospheres,2018-01-01,123(2)