DOI: 10.5194/hess-19-2737-2015
Scopus记录号: 2-s2.0-84935008046
论文题名: Large-basin hydrological response to climate model outputs: Uncertainty caused by internal atmospheric variability
作者: Gelfan A ; , Semenov V ; A ; , Gusev E ; , Motovilov Y ; , Nasonova O ; , Krylenko I ; , Kovalev E
刊名: Hydrology and Earth System Sciences
ISSN: 10275606
出版年: 2015
卷: 19, 期: 6 起始页码: 2737
结束页码: 2754
语种: 英语
Scopus关键词: Atmospheric temperature
; Climate change
; Earth atmosphere
; Hydrology
; Ice
; Normal distribution
; Oceanography
; Rain
; Rivers
; Runoff
; Sea ice
; Statistics
; Stochastic systems
; Surface waters
; Uncertainty analysis
; Water management
; Watersheds
; Atmospheric general circulation models
; Atmospheric variability
; Climate change projections
; Hydrological simulations
; Lower boundary conditions
; Sea ice concentration
; Sea surface temperature (SST)
; Spatio-temporal scale
; Climate models
; atmospheric general circulation model
; basin management
; boundary condition
; climate change
; climate forcing
; climate modeling
; ensemble forecasting
; error correction
; flood
; hydrograph
; hydrological response
; runoff
; spatiotemporal analysis
; uncertainty analysis
; Arctic Ocean
; Lena Basin
; Northern Dvina River Basin
; Russian Federation
英文摘要: An approach is proposed to assess hydrological simulation uncertainty originating from internal atmospheric variability. The latter is one of three major factors contributing to uncertainty of simulated climate change projections (along with so-called "forcing" and "climate model" uncertainties). Importantly, the role of internal atmospheric variability is most visible over spatio-temporal scales of water management in large river basins. Internal atmospheric variability is represented by large ensemble simulations (45 members) with the ECHAM5 atmospheric general circulation model. Ensemble simulations are performed using identical prescribed lower boundary conditions (observed sea surface temperature, SST, and sea ice concentration, SIC, for 1979-2012) and constant external forcing parameters but different initial conditions of the atmosphere. The ensemble of bias-corrected ECHAM5 outputs and ensemble averaged ECHAM5 output are used as a distributed input for the ECOMAG and SWAP hydrological models. The corresponding ensembles of runoff hydrographs are calculated for two large rivers of the Arctic basin: the Lena and Northern Dvina rivers. A number of runoff statistics including the mean and the standard deviation of annual, monthly and daily runoff, as well as annual runoff trend, are assessed. Uncertainties of runoff statistics caused by internal atmospheric variability are estimated. It is found that uncertainty of the mean and the standard deviation of runoff has a significant seasonal dependence on the maximum during the periods of spring-summer snowmelt and summer-autumn rainfall floods. Noticeable nonlinearity of the hydrological models' results in the ensemble ECHAM5 output is found most strongly expressed for the Northern Dvina River basin. It is shown that the averaging over ensemble members effectively filters the stochastic term related to internal atmospheric variability. Simulated discharge trends are close to normally distributed around the ensemble mean value, which fits well to empirical estimates and, for the Lena River, indicates that a considerable portion of the observed trend can be externally driven. © Author(s) 2015. CC Attribution 3.0 License. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/78496
Appears in Collections: 气候变化事实与影响
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作者单位: Water Problems Institute of RAS, Moscow, Russian Federation; A. M. Obukhov Institute of Atmospheric Physics of RAS, Moscow, Russian Federation; P. P. Shirshov Institute of Oceanology of RAS, Moscow, Russian Federation; Institute of Geography of RAS, Moscow, Russian Federation; Geographical Department, Moscow State University, Moscow, Russian Federation; GEOMAR Helmholtz Centre for Ocean Research Kiel, Kiel, Germany
Recommended Citation:
Gelfan A,, Semenov V,A,et al. Large-basin hydrological response to climate model outputs: Uncertainty caused by internal atmospheric variability[J]. Hydrology and Earth System Sciences,2015-01-01,19(6)