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View article: Reducing a Tropical Cyclone Weak-Intensity Bias in a Global Numerical Weather Prediction System
Reducing a Tropical Cyclone Weak-Intensity Bias in a Global Numerical Weather Prediction System Open
The operational Canadian Global Deterministic Prediction System suffers from a weak-intensity bias for simulated tropical cyclones. The presence of this bias is confirmed in progressively simplified experiments using a hierarchical system …
View article: Leveraging Data-Driven Weather Forecasting for Improving Numerical Weather Prediction Skill Through Large-Scale Spectral Nudging
Leveraging Data-Driven Weather Forecasting for Improving Numerical Weather Prediction Skill Through Large-Scale Spectral Nudging Open
Operational weather forecasting has traditionally relied on physics-based numerical weather prediction (NWP) models, but the rise of AI-based weather emulators is reshaping this paradigm. However, most data-driven models for medium-range f…
View article: Leveraging data-driven weather models for improving numerical weather prediction skill through large-scale spectral nudging
Leveraging data-driven weather models for improving numerical weather prediction skill through large-scale spectral nudging Open
This tar file contains the additional code for spectral nudging with version 5.3.0-a4 of the Global Environmental Multiscale (GEM) model. It also contains the model configuration files representing the optimal nudging configuration. In add…
View article: Reducing a Tropical Cyclone Weak-Intensity Bias in a Global Numerical Weather Prediction System
Reducing a Tropical Cyclone Weak-Intensity Bias in a Global Numerical Weather Prediction System Open
The operational Canadian Global Deterministic Prediction System suffers from a weak-intensity bias for simulated tropical cyclones. The presence of this bias is confirmed in progressively simplified experiments using a hierarchical system …
View article: Supporting Dataset for "Reducing a tropical cyclone weak-intensity bias in a global numerical weather prediction system"
Supporting Dataset for "Reducing a tropical cyclone weak-intensity bias in a global numerical weather prediction system" Open
This archive supports the submission of "Reducing a tropical cyclone weak intensity bias in a global numerical weather prediction system" to Monthly Weather Review. It contains model configurations, the software used to create ensemble per…
View article: Supporting Dataset for "Reducing a tropical cyclone weak-intensity bias in a global numerical weather prediction system"
Supporting Dataset for "Reducing a tropical cyclone weak-intensity bias in a global numerical weather prediction system" Open
This archive supports the submission of "Reducing a tropical cyclone weak intensity bias in a global numerical weather prediction system" to Monthly Weather Review. It contains model configurations, the software used to create ensemble per…
View article: Using Stochastically Perturbed Parameterizations to Represent Model Uncertainty. Part I: Implementation and Parameter Sensitivity
Using Stochastically Perturbed Parameterizations to Represent Model Uncertainty. Part I: Implementation and Parameter Sensitivity Open
Accurately representing model-based sources of uncertainty is essential for the development of reliable ensemble prediction systems for NWP applications. Uncertainties in discretizations, algorithmic approximations, and diabatic and unreso…
View article: Implementation of a semi-Lagrangian fully-implicit time integration of the unified soundproof system of equations for numerical weather prediction
Implementation of a semi-Lagrangian fully-implicit time integration of the unified soundproof system of equations for numerical weather prediction Open
An alternate dynamical core that employs the unified equations of A. Arakawa and C.S. Konor (2009) has been developed within Environment and Climate change Canada’s GEM (Global Environmental Multiscale) atmospheric model. As in the operati…