Abstract: AbstractWith the serial treatment of observations in the ensemble Kalman filter (EnKF), the assimilation order of observations is usually assumed to have no significant impact on analysis accuracy. However, Nerger derived ...

Abstract: AbstractThe ensemble predictability of the January 2015 and 2016 East Coast winter storms is assessed, with model precipitation forecasts verified against observational datasets. Skill scores and reliability diagrams ...

Abstract: Previous methods for creating consensus forecasts weight individual ensemble members based upon their relative performance over the previous N days, implicitly making a short-term persistence assumption about the underlying ...

Abstract: In ensemble Kalman filter (EnKF) data assimilation, localization modifies the error covariance matrices to suppress the influence of distant observations, removing spurious long-distance correlations. In addition to allowing ...

Abstract: he potential of Bayesian model averaging (BMA) and heteroscedastic censored logistic regression (HCLR) to postprocess precipitation ensembles is investigated. For this, outputs from the National Oceanic and Atmospheric ...