Impact of observational error on the validation of ensemble prediction systems

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How researchers see this paper

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The Multiensemble Approach: The NAEFS Example (2009, unknown): “Here the predicted ensembles and observed verifications data are all synthetic (e.g., Candille and Talagrand 2008).”
Cloud-Resolving Ensemble Simulations of Mediterranean Heavy Precipitating Events: Uncertainty on Initial Conditions and Lateral Boundary Conditions (2011, background): “Some studies have shown that considering the uncertainties on observations can change the computed scores (Candille and Talagrand 2008; Bowler 2006).”
On the representation error in data assimilation (2018, unknown): “Also, accurate speciﬁcation of these statistics is important for veriﬁcation of forecast results (Hamill, 2001; Bowler, 2008; Candille and Talagrand, 2008).”
Generalization of the Ignorance Score: Continuous Ranked Version and Its Decomposition (2012, background): “Candille and Talagrand (2005) also presented the decomposition in (8); however, they stated that a practical calculation requires ‘‘many approximations and assumptions,’’ assuming a prior transformation of each predicted ensemble into a continuous distribution function is necessary.”