DOI: 10.5194/hess-23-2541-2019
论文题名: Observation operators for assimilation of satellite observations in fluvial inundation forecasting
作者: Cooper E.S. ; Dance S.L. ; García-Pintado J. ; Nichols N.K. ; Smith P.J.
刊名: Hydrology and Earth System Sciences
ISSN: 1027-5606
出版年: 2019
卷: 23, 期: 6 起始页码: 2541
结束页码: 2559
语种: 英语
Scopus关键词: Backscattering
; Floods
; Forecasting
; Radar imaging
; Space-based radar
; Water levels
; Computational hydrodynamics
; Conventional approach
; Data assimilation
; Ensemble Kalman filtering
; Observation operator
; Physical mechanism
; Satellite observations
; Synthetic experiments
; Synthetic aperture radar
; backscatter
; data assimilation
; flood
; flood forecasting
; forecasting method
; hydrodynamics
; instrumentation
; Kalman filter
; observational method
; satellite imagery
; synthetic aperture radar
英文摘要: Images from satellite-based synthetic aperture radar (SAR) instruments contain large amounts of information about the position of floodwater during a river flood event. This observational information typically covers a large spatial area but is only relevant for a short time if water levels are changing rapidly. Data assimilation allows us to combine valuable SAR-derived observed information with continuous predictions from a computational hydrodynamic model and thus to produce a better forecast than using the model alone. In order to use observations in this way, a suitable observation operator is required. In this paper we show that different types of observation operators can produce very different corrections to predicted water levels; this impacts the quality of the forecast produced. We discuss the physical mechanisms by which different observation operators update modelled water levels and introduce a novel observation operator for inundation forecasting. The performance of the new operator is compared in synthetic experiments with that of two more conventional approaches. The conventional approaches both use observations of water levels derived from SAR to correct model predictions. Our new operator is instead designed to use backscatter values from SAR instruments as observations; such an approach has not been used before in an ensemble Kalman filtering framework. Direct use of backscatter observations opens up the possibility of using more information from each SAR image and could potentially speed up the time taken to produce observations needed to update model predictions. We compare the strengths and weaknesses of the three different approaches with reference to the physical mechanisms with which each of the observation operators allow data assimilation to update water levels in synthetic twin experiments in an idealised domain. © Author(s) 2019. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/162960
Appears in Collections: 气候变化与战略
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作者单位: Cooper, E.S., Department of Meteorology, University of Reading, Reading, United Kingdom; Dance, S.L., Department of Meteorology, University of Reading, Reading, United Kingdom, Department of Mathematics and Statistics, University of Reading, Reading, United Kingdom; García-Pintado, J., MARUM Center for Marine Environmental Sciences, Department of Geosciences, University of Bremen, Bremen, Germany; Nichols, N.K., Department of Meteorology, University of Reading, Reading, United Kingdom, Department of Mathematics and Statistics, University of Reading, Reading, United Kingdom; Smith, P.J., Department of Meteorology, University of Reading, Reading, United Kingdom
Recommended Citation:
Cooper E.S.,Dance S.L.,García-Pintado J.,et al. Observation operators for assimilation of satellite observations in fluvial inundation forecasting[J]. Hydrology and Earth System Sciences,2019-01-01,23(6)