Uncertainties in Numerical Weather Prediction 1st edition by Haraldur Olafsso, Jian Wen Bao 0128154918 978-0128154915

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ISBN-10 ‏ : ‎ 0128154918

ISBN-13 ‏ : ‎ 978-0128154915

Author :  Haraldur Olafsso, Jian-Wen Bao

Uncertainties in Numerical Weather Prediction is a comprehensive work on the most current understandings of uncertainties and predictability in numerical simulations of the atmosphere. It provides general knowledge on all aspects of uncertainties in the weather prediction models in a single, easy to use reference. The book illustrates particular uncertainties in observations and data assimilation, as well as the errors associated with numerical integration methods. Stochastic methods in parameterization of subgrid processes are also assessed, as are uncertainties associated with surface-atmosphere exchange, orographic flows and processes in the atmospheric boundary layer.

Uncertainties in Numerical Weather Prediction 1st Table of contents:

Chapter 1: Dynamical cores for NWP: An uncertain landscape*
Abstract
Acknowledgments
1: Introduction
2: Governing equations
3: Some physical properties
4: Discretizing in time
5: Discretizing in space
6: (Semi-)Lagrangian approach
7: Multidimensional aspects
8: An outlook
Chapter 2: Numerical uncertainties in discretization of the shallow-water equations for weather predication models
Abstract
Acknowledgments
1: Introduction
2: Discretization of the governing equation I
3: Discretization of the governing equation II
4: Filtering, damping, and limiting techniques
5: Global models on unstructured grids
6: Summary
Chapter 3: Probabilistic view of numerical weather prediction and ensemble prediction
Abstract
Acknowledgments
1: The numerical weather prediction problem
2: Sources of forecast errors and the chaotic nature of the atmospheric flow
3: Ensemble-based probabilistic prediction
4: Examples of ensemble-based probabilistic products
5: A look into the future
6: Key learning points
Chapter 4: Predictability
Abstract
1: Predictability, error growth and uncertainty
2: Error growth, and scale-dependent predictability
3: Metrics to measure forecast error and forecast skill
4: An error growth model
5: Predictability estimates
6: Sources of predictability
7: Conclusions
8: List of acronyms
Chapter 5: Modeling moist dynamics on subgrid
Abstract
Acknowledgments
1: Introduction
2: Large-scale vs convective precipitation
3: Convection, waves, and the large-scale circulation
4: Gravity waves and the stratosphere
5: Mesoscale convective systems and the diurnal cycle
6: Boundary-layer clouds and the radiation budget
7: Conclusions
Chapter 6: Ensemble data assimilation for estimating analysis uncertainty
Abstract
1: State estimation and state uncertainty
2: Ensembles of states for uncertainty estimation
3: Particle filters in high dimensions
Chapter 7: Subgrid turbulence mixing
Abstract
Acknowledgments
1: Introduction
2: Nonlocal flux
3: Mixing length
4: Subgrid horizontal mixing parameterizations
5: Discussions
Chapter 8: Uncertainties in the surface layer physics parameterizations
Abstract
1: Introduction
2: Atmosphere-ocean interaction
3: Atmosphere-land interaction
4: Summary
Chapter 9: Radiation
Abstract
Acknowledgment
1: Introduction
2: External uncertainties
3: Internal uncertainties
4: Subgrid assumptions
Chapter 10: Uncertainties in the parameterization of cloud microphysics: An illustration of the problem
Abstract
1: Introduction
2: A brief history of the development of cloud microphysics schemes within the community WRF model
3: Theoretical basis for cloud microphysics parameterization: A perspective of cloud particle population balance
4: Uncertainties in the parameterization complexity required for applications
5: Uncertainties in the parameterized warm rain processes
6: Uncertainties in the simulated liquid hydrometeor particle size distributions
7: Uncertainties in the parameterized cold rain processes
8: Uncertainties in the simulated frozen hydrometeor particle properties and size distributions
9: Uncertainties in the interaction of aerosols and clouds
10: Summary
Chapter 11: Mesoscale orographic flows
Abstract
1: Introduction
2: Patterns of mountain flows
3: Forecasting the orographic flows
4: Future improvements
Chapter 12: Numerical methods to identify model uncertainty
Abstract
1: Numerical tracers
2: Tendency diagnostics
Chapter 13: Dynamic identification and tracking of errors in numerical simulations of the atmosphere
Abstract
1: Introduction
2: Variables and functions, useful for error tracing in atmospheric flow
3: Precipitation and vertical velocity
4: The method of error tracking
5: Wrong prediction of the surface pressure field
6: Wrong prediction of heavy precipitation
7: Wrong prediction of a rapidly deepening cyclone
8: Wrong prediction of the surface pressure field and mesoscale orographic impacts

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