Leo Šeparović
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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: Fixing the Double Penalty in Data-Driven Weather Forecasting Through a Modified Spherical Harmonic Loss Function
Fixing the Double Penalty in Data-Driven Weather Forecasting Through a Modified Spherical Harmonic Loss Function Open
Recent advancements in data-driven weather forecasting models have delivered deterministic models that outperform the leading operational forecast systems based on traditional, physics-based models. However, these data-driven models are ty…
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: Use of a Genetic Algorithm to Optimize a Numerical Weather Prediction System
Use of a Genetic Algorithm to Optimize a Numerical Weather Prediction System Open
An important step in an ensemble Kalman filter (EnKF) algorithm is the integration of an ensemble of short-range forecasts with a numerical weather prediction (NWP) model. A multiphysics approach is used in the Canadian global EnKF system.…
View article: A Convection Parameterization for Low-CAPE Environments
A Convection Parameterization for Low-CAPE Environments Open
Numerical models that are unable to resolve moist convection in the atmosphere employ physical parameterizations to represent the effects of the associated processes on the resolved-scale state. Most of these schemes are designed to repres…
View article: On the Progressive Attenuation of Finescale Orography Contributions to the Vertical Coordinate Surfaces within a Terrain-Following Coordinate System
On the Progressive Attenuation of Finescale Orography Contributions to the Vertical Coordinate Surfaces within a Terrain-Following Coordinate System Open
A modified hybrid terrain-following vertical coordinate has recently been implemented within the Global Environmental Multiscale atmospheric model that introduces separately controlled height-dependent progressive decaying of the small- an…
View article: Modernization of Atmospheric Physics Parameterization in Canadian NWP
Modernization of Atmospheric Physics Parameterization in Canadian NWP Open
Atmospheric physics is represented in numerical models by parameterizations that use resolved‐scale information to estimate the effects of physical processes on the atmospheric state. Over time, our understanding of these processes improve…
View article: A Lagrangian Perspective on Parameterizing Deep Convection
A Lagrangian Perspective on Parameterizing Deep Convection Open
The parameterization of deep moist convection as a subgrid-scale process in numerical models of the atmosphere is required at resolutions that extend well into the convective “gray zone,” the range of grid spacings over which such convecti…
View article: Internal variability of fine‐scale components of meteorological fields in extended‐range limited‐area model simulations with atmospheric and surface nudging
Internal variability of fine‐scale components of meteorological fields in extended‐range limited‐area model simulations with atmospheric and surface nudging Open
Internal variability (IV) in dynamical downscaling with limited‐area models (LAMs) represents a source of error inherent to the downscaled fields, which originates from the sensitive dependence of the models to arbitrarily small modificati…