Seasonal streamflow forecasts for Europe – II. Explanation of the skill
Wouter Greuell, Wietse H. P. Franssen, and Ronald W. A. Hutjes
Water Systems and Global Change (WSG) group, Wageningen University and Research, Wageningen, NL 6708 PB Wageningen, Netherlands
Received: 17 Nov 2016 – Accepted for review: 29 Nov 2016 – Discussion started: 30 Nov 2016
Abstract. Seasonal predictions can be exploited among others to optimize hydropower energy generation, navigability of rivers and irrigation management to decrease crop yield losses. This paper is the second of two papers dealing with a model-based system built to produce seasonal hydrological forecasts (WUSHP: Wageningen University Seamless Hydrological Prediction system), applied here to Europe. Whereas the first paper presents the development and the skill evaluation of the system, this paper provides explanations for the skill. In WUSHP hydrology is simulated by running the Variable Infiltration Capacity (VIC) hydrological model with meteorological forcing from bias-corrected output of ECMWF's Seasonal Forecasting System 4 (S4). WUSHP is probabilistic. For the assessment of skill, hindcast simulations (1981–2010) were carried out. To explain skill, we first looked at the forcing and found considerable skill in the precipitation forecasts of the first lead month but hardly any significant skill for later lead months. Seasonal forecasts for temperature have more skill. Skill in summer temperature is related to climate change and more or less independent of lead time. Skill in February and March is unrelated to climate change. Sources of skill in runoff were isolated with Ensemble Streamflow Prediction (ESP) experiments. These revealed that beyond the second lead month simulations with forcing that is identical for all years (ESPall) produce more skill in runoff than the simulations forced with S4 output (Full Hindcasts). This occurs because interannual variability of the S4 forcing has insufficient skill while it adds noise. Other ESP-experiments show that in Europe initial conditions of soil moisture form the dominant source of skill in runoff. From April to July, at the end of the melt season, initial conditions of snow contribute significantly to the skill, also when forecasts start much earlier. Some remarkable skill features are due to indirect effects, i.e. skill due to forcing or initial conditions of snow and soil moisture at an earlier stage is stored in the hydrological state (snow and/or soil moisture) of a later stage, which then contributes to persistence of skill. Finally, predictability of evapotranspiration was analysed in some detail, leading among others to the conclusion that it is due to all potential sources of skill but mostly to forcing.
Greuell, W., Franssen, W. H. P., and Hutjes, R. W. A.: Seasonal streamflow forecasts for Europe – II. Explanation of the skill, Hydrol. Earth Syst. Sci. Discuss., doi:10.5194/hess-2016-604, in review, 2016.