@article{FranckeBaroniBrosinskyetal.2018,
  author    = {Francke, Till and Baroni, Gabriele and Brosinsky, Arlena and Foerster, Saskia and Lopez-Tarazon, Jos{\´e} Andr{\´e}s and Sommerer, Erik and Bronstert, Axel},
  title     = {What Did Really Improve Our Mesoscale Hydrological Model?},
  series = {Water resources research},
  volume    = {54},
  journal   = {Water resources research},
  number    = {11},
  publisher = {American Geophysical Union},
  address   = {Washington},
  issn      = {0043-1397},
  doi       = {10.1029/2018WR022813},
  pages     = {8594 -- 8612},
  year      = {2018},
  abstract  = {Modelers can improve a model by addressing the causes for the model errors (data errors and structural errors). This leads to implementing model enhancements (MEs), for example, meteorological data based on more monitoring stations, improved calibration data, and/or modifications in process formulations. However, deciding on which MEs to implement remains a matter of expert knowledge. After implementing multiple MEs, any improvement in model performance is not easily attributed, especially when considering different objectives or aspects of this improvement (e.g., better dynamics vs. reduced bias). We present an approach for comparing the effect of multiple MEs based on real observations and considering multiple objectives (MMEMO). A stepwise selection approach and structured plots help to address the multidimensionality of the problem. Tailored analyses allow a differentiated view on the effect of MEs and their interactions. MMEMO is applied to a case study employing the mesoscale hydro-sedimentological model WASA-SED for the Mediterranean-mountainous Isabena catchment, northeast Spain. The investigated seven MEs show diverse effects: some MEs (e.g., rainfall data) cause improvements for most objectives, while other MEs (e.g., land use data) only affect a few objectives or even decrease model performance. Interaction of MEs was observed for roughly half of the MEs, confirming the need to address them in the analysis. Calibration and increasing the temporal resolution showed by far stronger impact than any of the other MEs. The proposed framework can be adopted in other studies to analyze the effect of MEs and, thus, facilitate the identification and implementation of the most promising MEs for comparable cases.},
  language  = {en}
}
@article{FranckeFoersterBrosinskyetal.2018,
  author    = {Francke, Till and F{\"o}rster, Saskia and Brosinsky, Arlena and Sommerer, Erik and Lopez-Tarazonl, Jose Andres and G{\"u}ntner, Andreas and Batalla, Ramon J. and Bronstert, Axel},
  title     = {Water and sediment fluxes in Mediterranean mountainous regions},
  series = {Earth System Science Data},
  volume    = {10},
  journal   = {Earth System Science Data},
  number    = {2},
  publisher = {Copernicus},
  address   = {G{\"o}ttingen},
  issn      = {1866-3508},
  doi       = {10.5194/essd-10-1063-2018},
  pages     = {1063 -- 1075},
  year      = {2018},
  abstract  = {A comprehensive hydro-sedimentological dataset for the Isabena catchment, northeastern (NE) Spain, for the period 2010-2018 is presented to analyse water and sediment fluxes in a Mediterranean mesoscale catchment. The dataset includes rainfall data from 12 rain gauges distributed within the study area complemented by meteorological data of 12 official meteo-stations. It comprises discharge data derived from water stage measurements as well as suspended sediment concentrations (SSCs) at six gauging stations of the River Isabena and its sub-catchments. Soil spectroscopic data from 351 suspended sediment samples and 152 soil samples were collected to characterize sediment source regions and sediment properties via fingerprinting analyses. The Isabena catchment (445 km(2)) is located in the southern central Pyrenees ranging from 450 m to 2720 m a.s.l.; together with a pronounced topography, this leads to distinct temperature and precipitation gradients. The River Isabena shows marked discharge variations and high sediment yields causing severe siltation problems in the downstream Barasona Reservoir. The main sediment source is badland areas located on Eocene marls that are well connected to the river network. The dataset features a comprehensive set of variables in a high spatial and temporal resolution suitable for the advanced process understanding of water and sediment fluxes, their origin and connectivity and sediment budgeting and for the evaluation and further development of hydro-sedimentological models in Mediterranean mesoscale mountainous catchments.},
  language  = {en}
}
@article{DelgadoVossBuergeretal.2018,
  author    = {Delgado, Jos{\´e} Miguel Martins and Voss, Sebastian and B{\"u}rger, Gerd and Vormoor, Klaus Josef and Murawski, Aline and Rodrigues Pereira, Jos{\´e} Marcelo and Martins, Eduardo and Vasconcelos J{\´u}nior, Francisco and Francke, Till},
  title     = {Seasonal drought prediction for semiarid northeastern Brazil},
  series = {Hydrology and Earth System Sciences},
  volume    = {22},
  journal   = {Hydrology and Earth System Sciences},
  number    = {9},
  publisher = {Copernicus Publ.},
  address   = {G{\"o}ttingen},
  issn      = {1027-5606},
  doi       = {10.5194/hess-22-5041-2018},
  pages     = {5041 -- 5056},
  year      = {2018},
  abstract  = {A set of seasonal drought forecast models was assessed and verified for the Jaguaribe River in semiarid northeastern Brazil. Meteorological seasonal forecasts were provided by the operational forecasting system used at FUNCEME (Cear{\´a}'s research foundation for meteorology)and by the European Centre for Medium-Range Weather Forecasts (ECMWF). Three downscaling approaches (empirical quantile mapping, extended downscaling and weather pattern classification) were tested and combined with the models in hindcast mode for the period 1981 to 2014. The forecast issue time was January and the forecast period was January to June. Hydrological drought indices were obtained by fitting a multivariate linear regression to observations. In short, it was possible to obtain forecasts for (a) monthly precipitation,(b) meteorological drought indices, and (c) hydrological drought indices. The skill of the forecasting systems was evaluated with regard to root mean square error (RMSE), the Brier skill score (BSS) and the relative operating characteristic skill score (ROCSS). The tested forecasting products showed similar performance in the analyzed metrics. Forecasts of monthly precipitation had little or no skill considering RMSE and mostly no skill with BSS. A similar picture was seen when forecasting meteorological drought indices: low skill regarding RMSE and BSS and significant skill when discriminating hit rate and false alarm rate given by the ROCSS (forecasting drought events of, e.g., SPEI1 showed a ROCSS of around 0.5). Regarding the temporal variation of the forecast skill of the meteorological indices, it was greatest for April, when compared to the remaining months of the rainy season, while the skill of reservoir volume forecasts decreased with lead time. This work showed that a multi-model ensemble can forecast drought events of timescales relevant to water managers in northeastern Brazil with skill. But no or little skill could be found in the forecasts of monthly precipitation or drought indices of lower scales, like SPI1. Both this work and those here revisited showed that major steps forward are needed in forecasting the rainy season in northeastern Brazil.},
  language  = {en}
}
@article{RottlerKormannFranckeetal.2018,
  author    = {Rottler, Erwin and Kormann, Christoph Martin and Francke, Till and Bronstert, Axel},
  title     = {Elevation-dependent warming in the Swiss Alps 1981-2017},
  series = {International journal of climatology : a journal of the Royal Meteorological Society},
  volume    = {39},
  journal   = {International journal of climatology : a journal of the Royal Meteorological Society},
  number    = {5},
  publisher = {Wiley},
  address   = {Hoboken},
  issn      = {0899-8418},
  doi       = {10.1002/joc.5970},
  pages     = {2556 -- 2568},
  year      = {2018},
  abstract  = {Due to the environmental and socio-economic importance of mountainous regions, it is crucial to understand causes and consequences of climatic changes in those sensitive landscapes. Daily resolution alpine climate data from Switzerland covering an elevation range of over 3,000m between 1981 and 2017 have been analysed using highly resolved trends in order to gain a better understanding of features, forcings and feedbacks related to temperature changes in mountainous regions. Particular focus is put on processes related to changes in weather types, incoming solar radiation, cloud cover, air humidity, snow/ice and elevation dependency of temperature trends. Temperature trends in Switzerland differ depending on the time of the year, day and elevation. Warming is strongest during spring and early summer with enhanced warming of daytime maximum temperatures. Elevation-based differences in temperature trends occur during autumn and winter with stronger warming at lower elevations. We attribute this elevation-dependent temperature signal mainly to elevation-based differences in trends of incoming solar radiation and elevation-sensitive responses to changes in frequencies of weather types. In general, effects of varying frequencies of weather types overlap with trends caused by transmission changes in short- and long-wave radiation. Temperature signals arising from snow/ice albedo feedback mechanisms are probably small and might be hidden by other effects.},
  language  = {en}
}