气候变化领域集成服务门户(CCPortal): Technical note: Assessment of observation quality for data assimilation in flood models

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DOI	10.5194/hess-22-3983-2018
	Technical note: Assessment of observation quality for data assimilation in flood models
	Waller J.A.; García-Pintado J.; Mason D.C.; Dance S.L.; Nichols N.K.
发表日期	2018
ISSN	1027-5606
起始页码	3983
结束页码	3992
卷号	22 期号:7
英文摘要	The assimilation of satellite-based water level observations (WLOs) into 2-D hydrodynamic models can keep flood forecasts on track or be used for reanalysis to obtain improved assessments of previous flood footprints. In either case, satellites provide spatially dense observation fields, but with spatially correlated errors. To date, assimilation methods in flood forecasting either incorrectly neglect the spatial correlation in the observation errors or, in the best of cases, deal with it by thinning methods. These thinning methods result in a sparse set of observations whose error correlations are assumed to be negligible. Here, with a case study, we show that the assimilation diagnostics that make use of statistical averages of observation-minus-background and observation-minus-analysis residuals are useful to estimate error correlations in WLOs. The average estimated correlation length scale of 7 km is longer than the expected value of 250 m. Furthermore, the correlations do not decrease monotonically; this unexpected behaviour is shown to be the result of assimilating some anomalous observations. Accurate estimates of the observation error statistics can be used to support quality control protocols and provide insight into which observations it is most beneficial to assimilate. Therefore, the understanding gained in this paper will contribute towards the correct assimilation of denser datasets. © Author(s) 2018.
语种	英语
scopus关键词	Error statistics; Errors; Flood control; Floods; Quality control; Water levels; Correlated errors; Correlation length scale; Data assimilation; Hydrodynamic model; Observation errors; Observation qualities; Spatial correlations; Statistical average; Weather forecasting; assessment method; correlation; data assimilation; data quality; data set; flood; flood forecasting; hydrodynamics; hydrological modeling; quality control; satellite altimetry; two-dimensional modeling; water level
来源期刊	Hydrology and Earth System Sciences
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/159962
作者单位	Waller, J.A., School of Mathematical, Physical and Computational Sciences, University of Reading, Reading, United Kingdom; García-Pintado, J., School of Mathematical, Physical and Computational Sciences, University of Reading, Reading, United Kingdom, MARUM - Center for Marine Environmental Sciences and Department of Geosciences, University of Bremen, Bremen, Germany; Mason, D.C., School of Archaeology, Geography and Environmental Science, University of Reading, Reading, United Kingdom; Dance, S.L., School of Mathematical, Physical and Computational Sciences, University of Reading, Reading, United Kingdom; Nichols, N.K., School of Mathematical, Physical and Computational Sciences, University of Reading, Reading, United Kingdom
推荐引用方式 GB/T 7714	Waller J.A.,García-Pintado J.,Mason D.C.,et al. Technical note: Assessment of observation quality for data assimilation in flood models[J],2018,22(7).
APA	Waller J.A.,García-Pintado J.,Mason D.C.,Dance S.L.,&Nichols N.K..(2018).Technical note: Assessment of observation quality for data assimilation in flood models.Hydrology and Earth System Sciences,22(7).
MLA	Waller J.A.,et al."Technical note: Assessment of observation quality for data assimilation in flood models".Hydrology and Earth System Sciences 22.7(2018).