Abstract
Abstract. 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.
Highlights
In river basin hydrology, two groups of approaches are usually applied to assess the impact of changing climate on river runoff
We have presented an analysis of large-basin hydrological response uncertainty originating from internal atmospheric variability that was for the first time performed with such a large (45 members) ensemble of climate model simulations
In the presented simulations, the role of internal atmospheric variability is most visible for the timescales from years to first decades and for the regional spatial scales (e.g., Hawkins and Sutton, 2009), i.e., over spatio-temporal scales of water management in large river basins
Summary
Two groups of approaches are usually applied to assess the impact of changing climate on river runoff. We have tried to assess, using physically based hydrological models, the uncertainty in simulated river runoff characteristics of large river basins taking into consideration internal variability of the atmosphere The latter was simulated in a large (45 members) ensemble of GCM realizations of the current climate period (1979–2012) initialized under different initial conditions but using identical boundary forcing (sea surface temperatures and sea ice concentrations). The forcing data can be taken from meteorological observations or GCM outputs Both models were applied earlier for simulating runoff hydrographs based on multi-year hydrometeorological observations in the Lena and Northern Dvina River basins and demonstrated good performance of simulations (Motovilov and Gelfan, 2013; Gusev et al, 2011, 2015; Krylenko et al, 2014). Uncertainty in trends in annual runoff is calculated and discussed
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