Moving Towards Fully Ensemble-Derived Background-Error Covariances for NWP at ECCC
The transition from hybrid covariances to fully ensemble-derived background-error covariances for Numerical Weather Prediction (NWP) at Environment and Climate Change Canada (ECCC) is explored in this paper. It discusses the evolution of covariance formulations, the use of scale-dependent localizati
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Understanding Multinomial Distribution in Statistical Analysis
Multinomial Distribution is a powerful tool used in statistical analysis to model outcomes of events with multiple categories. This distribution is applied to scenarios where each trial has several possible outcomes, and the sum of probabilities of all outcomes is equal to 1. By defining random vari
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Exploring Nuclear Data Needs and Covariances with Alejandro Sonzogni
In this collection by Tim Johnson, Libby McCutchan, and Alejandro Sonzogni from the National Nuclear Data Center, various aspects of nuclear data needs and beta-delayed neutron covariances are discussed. Topics include different radiation types, gamma decay heat, beta transitions, antineutrinos, and
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