Can an ensemble transform Kalman filter predict the reduction in forecast‐error variance produced by targeted observations?

By Sharanya J. Majumdar, Craig H. Bishop, B. Etherton, Istvan Szunyogh, Zoltán Tóth. 2001

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The Ensemble Kalman Filter: theoretical formulation and practical implementation (2003, methodology): “The methodology was named Ensemble Trans-form Kalman Filter and it was further examined by Majumdar et al. (2001).”
Using Improved Background-Error Covariances from an Ensemble Kalman Filter for Adaptive Observations (2002, methodology): “However, we aim for a slightly different goal than in Bishop et al. (2001) and their subsequent work (e.g., Majumdar et al. 2001).”
Initial perturbations based on the ensemble transform (ET) technique in the NCEP global operational forecast system (2008, background): “The ranges of forecast error variances that are associated the ranges of ensemble variances are the explained error variances statistically (see Majumdar et al., 2001, 2002; Wang and Bishop, 2003 and W06 for more details).”
Ensemble Transform Kalman Filter-based ensemble perturbations in an operational global prediction system at NCEP (2006, methodology): “To analyse how well the ensemble variance can explain the forecast error variance, we follow the method used in Majumdar et al. (2001; 2002) and Wang and Bishop (2003).”