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This is an introductory textbook on global spectral modeling designed for senior-level undergraduates and possibly for first-year graduate students. This text starts with an introduction to elementary finite-difference methods and moves on towards the gradual description of sophisticated dynamical and physical models in spherical coordinates. Computational aspects of the spectral transform method, the planetary boundary layer physics, the physics of precipitation processes in large-scale models, the radiative transfer including effects of diagnostic clouds and diurnal cycle, the surface energy balance over land and ocean, and the treatment of mountains are some issues that are addressed. The topic of model initialization includes the treatment of normal modes and physical processes. A concluding chapter covers the spectral energetics as a diagnostic tool for model evaluation. This revised second edition of the text also includes three additional chapters. Chapter 11 deals with the formulation of a regional spectral model for mesoscale modeling which uses a double Fourier expansion of data and model equations for its transform. Chapter 12 deals with ensemble modeling. This is a new and important area for numerical weather and climate prediction. Finally, yet another new area that has to do with adaptive observational strategies is included as Chapter 13. It foretells where data deficiencies may reside in model from an exploratory ensemble run of experiments and the spread of such forecasts.
This is an introductory textbook on global spectral modeling designed for senior-level undergraduates and possibly for first-year graduate students. This text starts with an introduction to elementary finite-difference methods and moves on towards the gradual description of sophisticated dynamical and physical models in spherical coordinates. Computational aspects of the spectral transform method, the planetary boundary layer physics, the physics of precipitation processes in large-scale models, the radiative transfer including effects of diagnostic clouds and diurnal cycle, the surface energy balance over land and ocean, and the treatment of mountains are some issues that are addressed. The topic of model initialization includes the treatment of normal modes and physical processes. A concluding chapter covers the spectral energetics as a diagnostic tool for model evaluation. This revised second edition of the text also includes three additional chapters. Chapter 11 deals with the formulation of a regional spectral model for mesoscale modeling which uses a double Fourier expansion of data and model equations for its transform. Chapter 12 deals with ensemble modeling. This is a new and important area for numerical weather and climate prediction. Finally, yet another new area that has to do with adaptive observational strategies is included as Chapter 13. It foretells where data deficiencies may reside in model from an exploratory ensemble run of experiments and the spread of such forecasts.
"This volume is based on the "School/Workshop on Linear Time, Branching Time and Partial Order in Logics and Models for Concurrency" organized by the editors and held in the period May 30-June 3, 1988 at Noordwijkerhout, The Netherlands. The School/Workshop was an activity of the project REX - Research and Education in Concurrent Systems. The volume contains tutorials and research contributions to the three approaches - linear time, - branching time, and - partial order in semantics and proof theory of concurrent programs by the main specialists in this field. It promotes an in-depth understanding of the relative merits and disadvantages of these three approaches. An introduction to the recent literature on the subject is provided by the invited research contributions.''--Publisher's website.
An Introduction to Numerical Weather Prediction Techniques is unique in the meteorological field as it presents for the first time theories and software of complex dynamical and physical processes required for numerical modeling. It was first prepared as a manual for the training of the World Meteorological Organization's programs at a similar level. This new book updates these exercises and also includes the latest data sets. This book covers important aspects of numerical weather prediction techniques required at an introductory level. These techniques, ranging from simple one-dimensional space derivative to complex numerical models, are first described in theory and for most cases supported by fully tested computational software. The text discusses the fundamental physical parameterizations needed in numerical weather models, such as cumulus convection, radiative transfers, and surface energy fluxes calculations. The book gives the user all the necessary elements to build a numerical model. An Introduction to Numerical Weather Prediction Techniques is rich in illustrations, especially tables showing outputs from each individual algorithm presented. Selected figures using actual meteorological data are also used. This book is primarily intended for senior-level undergraduates and first-year graduate students in meteorology. It is also excellent for individual scientists who wish to use the book for self-study. Scientists dealing with geophysical data analysis or predictive models will find this book filled with useful techniques and data-processing algorithms.
General circulation models (GCMs), which define the fundamental dynamics of atmospheric circulation, are nowadays used in various fields of atmospheric science such as weather forecasting, climate predictions and environmental estimations. The Second Edition of this renowned work has been updated to include recent progress of high resolution global modeling. It also contains for the first time aspects of high-resolution global non-hydrostatic models that the author has been studying since the publication of the first edition. Some highlighted results from the Non-hydrostatic ICosahedral Atmospheric Model (NICAM) are also included. The author outlines the theoretical concepts, simple models and numerical methods for modeling the general circulation of the atmosphere. Concentrating on the physical mechanisms responsible for the development of large-scale circulation of the atmosphere, the book offers comprehensive coverage of an important and rapidly developing technique used in the atmospheric science. Dynamic interpretations of the atmospheric structure and their aspects in the general circulation model are described step by step.
This book describes the methods used to construct general circulation models of the atmosphere, and how such models perform in applications relating to the real climate and environmental systems. The author describes the fundamental dynamics of the atmospheric circulation, modelling of the general circulation, and applications of GCMs. The book consists of three parts: - Part 1 summarizes the physical processes involved, including basic equations, waves and instabilities; - Part 2 covers atmospheric structures, including various types of one- and two-dimensional structures and circulations; - Part 3 describes the basic notions for construction of general circulation models of the atmosphere and their applications. Atmospheric Circulation Dynamics and General Circulation Methods includes an appendix incorporating the basic data and mathematical formulae required to enable readers to construct GCMs for themselves.
The flexible resolution/truncation baseline version of the AFGL global spectral model as adapted to the CRAY-1 is described. A series of low-resolution (6 layer, rhomboidal 15) and high-resolution (12 layer, rhomboidal 30) forecasts were run and compared to test the performance of the model. In general, higher resolution resulted in improved forecast skill in the 24-to-96-hour range. The only exception to this is the humidity forecast, which shows minimal skill. This characteristic is rather insensitive to the resolution partly because of the poor quality of analyzed humidity fields used for initial data and verification. The original gridded (2.5 X 2.5 deg) topography has been replaced by a smoothed terrain field that has been passed through a nine-point smoother, interpolated to the model's Gaussian grid, and then spectrally truncated. Finally, the effects of initialization have been studied by comparing a series of forecasts subjected to several initialization methods. For forecasts beyond 24 hours, the model is able to supress spurious gravity waves through the combined effects of the semi-implicit time scheme and the subgrid scale diffusion. The impact of normal mode initialization is seen mainly in the very short-range forecasts (less than 24 hours) and is thus important for providing smooth first-guess fields for the analysis/data assimilation cycle. Keywords: Atmospheric models; Spectral models; Weather forecasting; Numerical weather prediction; Global atmospheric circulation.
Spectral estimation is important in many fields including astronomy, meteorology, seismology, communications, economics, speech analysis, medical imaging, radar, sonar, and underwater acoustics. Most existing spectral estimation algorithms are devised for uniformly sampled complete-data sequences. However, the spectral estimation for data sequences with missing samples is also important in many applications ranging from astronomical time series analysis to synthetic aperture radar imaging with angular diversity. For spectral estimation in the missing-data case, the challenge is how to extend the existing spectral estimation techniques to deal with these missing-data samples. Recently, nonparametric adaptive filtering based techniques have been developed successfully for various missing-data problems. Collectively, these algorithms provide a comprehensive toolset for the missing-data problem based exclusively on the nonparametric adaptive filter-bank approaches, which are robust and accurate, and can provide high resolution and low sidelobes. In this book, we present these algorithms for both one-dimensional and two-dimensional spectral estimation problems.