Advancing Data Quality

Work Package 2

Scientific Questions

  • METRICS: How can we measure model performance in a climate change context?
  • FRAMEWORKS: How should parameter estimation and evaluation be performed for changing climate using these metrics?
  • ENSEMBLES: How do we select plausible members to create ensembles that encompass known uncertainties?



(a) Develop new set of metrics targeted to characterize reference data, climate model (CM), hydrological model (HM) and delta-change/bias-correction (DC/BC) method performance in simulating change in indicators
(b) Create a framework for calibration, evaluation and selection of ensemble members (both for HM members or CM members) and DC/BC methods relevant to climate indicators
(c) Demonstrate the new methods for users of both local and pan-European climate services for the water sector.



We researched how to increase the quality and usability of climate services.  We addressed research questions specifically for different indicators (e.g. 50-year return period flood, mean annual snow maximum) and different locations and address the whole climate impact modelling chain from choice of reference data used to describe today’s climate, via climate models, adjustment methods and impact modelling.

  • Differential Split Sampling Test for Hydrological Models: LINK
  • Expert Elicitation method: LINK



An Information Theory Approach to Identifying a Representative Subset of Hydro‐Climatic Simulations for Impact Modeling Studies (Pechlivanidis et. al. 2018) DOI:

Summertime precipitation extremes in a EURO-CORDEX 0.11° ensemble at an hourly resolution (Berg et. al. 2019) DOI:


Fig 2. Conceptual figure showing how research questions will address all aspects of the climate impact modelling chain leading to new ‘best-practice’ for impact studies.

Lead: Christiana Photiadou, SMHI