[1] The quantification of uncertainties in projections of climate impacts on river streamflow is highly important for climate adaptation purposes. In this study, we present a methodology to separate uncertainties arising from the climate model (CM), the statistical postprocessing (PP) scheme, and the hydrological model (HM). We analyzed ensemble projections of hydrological changes in the Alpine Rhine (Eastern Switzerland) for the near-term and farterm scenario periods 2024-2050 and 2073-2099 with respect to 1964-1990. For the latter scenario period, the model ensemble projects a decrease of daily mean runoff in summer (À32.2%, range [À45.5% to À8.1%]) and an increase in winter (þ41.8%, range [þ4.8% to þ81.7%]). We applied an analysis of variance model combined with a subsampling procedure to assess the importance of different uncertainty sources. The CMs generally are the dominant source in summer and autumn, whereas, in winter and spring, the uncertainties due to the HMs and the statistical PP gain importance and even partly dominate. In addition, results show that the individual uncertainties from the three components are not additive. Rather, the associated interactions among the CM, the statistical PP scheme, and the HM account for about 5%-40% of the total ensemble uncertainty. The results indicate, in distinction to some previous studies, that none of the investigated uncertainty sources are negligible, and some of the uncertainty is not attributable to individual modeling chain components but rather depends upon interactions.Citation: Bosshard, T., M. Carambia, K. Goergen, S. Kotlarski, P. Krahe, M. Zappa, and C. Sch€ ar (2013), Quantifying uncertainty sources in an ensemble of hydrological climate-impact projections, Water Resour. Res., 49, 1523Res., 49, -1536

Publication informationAtmospheric Research, 100 (2-3): 150-167Publisher Elsevier This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. A C C E P T E D M A N U S C R I P T ACCEPTED MANUSCRIPT A C C E P T E D M A N U S C R I P T ACCEPTED MANUSCRIPT AbstractQuantifying uncertainty in flood forecasting is a difficult task, given the multiple and strongly nonlinear model components involved in such a system. Much effort has been and is being invested in the quest of dealing with uncertain precipitation observations and forecasts and the propagation of such uncertainties through hydrological and hydraulic models predicting river discharges and risk for inundation. The COST 731 Action is one of these and constitutes a European initiative which deals with the quantification of forecast uncertainty in hydro-meteorological forecast systems.COST 731 addresses three major lines of development: (1) combining meteorological and hydrological models to form a forecast chain, (2) propagating uncertainty information through this chain and make it available to end users in a suitable form, (3)

Abstract. The development phase (DP) of the EUMETSAT Satellite Application Facility for Support to Operational Hydrology and Water Management (H-SAF) led to the design and implementation of several precipitation products, after 5 yr (2005)(2006)(2007)(2008)(2009)(2010) of activity. Presently, five precipitation estimation algorithms based on data from passive microwave and infrared sensors, on board geostationary and sun-synchronous platforms, function in operational mode at the H-SAF hosting institute to provide near real-time precipitation products at different spatial and temporal resolutions.In order to evaluate the precipitation product accuracy, a validation activity has been established since the beginning of the project. A Precipitation Product Validation Group (PPVG) works in parallel with the development of the estimation algorithms with two aims: to provide the algorithm developers with indications to refine algorithms and products, and to evaluate the error structure to be associated with the operational products.In this paper, the framework of the PPVG is presented: (a) the characteristics of the ground reference data available to H-SAF (i.e. radar and rain gauge networks), (b) the agreed upon validation strategy settled among the eight European countries participating in the PPVG, and (c) the steps of the validation procedures. The quality of the reference data is discussed, and the efforts for its improvement are outlined, with special emphasis on the definition of a ground radar Published by Copernicus Publications on behalf of the European Geosciences Union. S. Puca et al.:The validation service of the hydrological SAF geostationary products quality map and on the implementation of a suitable rain gauge interpolation algorithm. The work done during the H-SAF development phase has led the PPVG to converge into a common validation procedure among the members, taking advantage of the experience acquired by each one of them in the validation of H-SAF products. The methodology is presented here, indicating the main steps of the validation procedure (ground data quality control, spatial interpolation, upscaling of radar data vs. satellite grid, statistical score evaluation, case study analysis).Finally, an overview of the results is presented, focusing on the monthly statistical indicators, referred to the satellite product performances over different seasons and areas.

Cooperation in Science and Technology (COST) funding allows European scientists to establish international links, communicate their work to colleagues, and promote international research cooperation. COST731 was established to study the propagation of uncertainty from hydrometeorological observations through meteorological and hydrological models to the final flood forecast. Our focus is on how information about uncertainty is presented to the end user and how it is used. COST731 has assembled a number of demonstrations/case studies that illustrate a variety of practical approaches and these are presented here. While there is yet no consensus on how such information is presented, many end users do find it useful.

We present the idea and the very first results of an "Experimental ensemble based on the COSMO-DE (EELMK)". The aim is to understand predictability limits of precipitation forecasts on the convective scale. Ensemble techniques with convection-resolving models are a new field of research. We investigate forecast uncertainties due to imperfect model physics and lateral boundary conditions. The initial case studies demonstrate the potential of EELMK to generate variability between ensemble members in terms of spatial homogeneity and intensity of precipitation.