The book provides a valuable resource for environmental scientists, while also providing an important basis for graduate and postgraduate students interested in research on hydrological cycles and environmental changes.
Truly comprehensive observational diagnostic studies of these issues are essentially impossible, since they would require the global observational overage at extremely high spatial resolution. An alternative is to study such issues in high resolution models that may span 3 or more orders of magnitude in terms of spatial scales.
There has been a great deal of progress recently on development and application of such fine resolution models. This had been spurred in part by the recent availability of exceptionally powerful computers. Noteworthy in this respect is the Earth Simulator in Yokohama, Japan, which commenced operations in 2002 and provides a peak performance of 40 Terraflops, but competitive supercomputers for scientific applications are now becoming available in the USA and Europe as well. There has developed in the last few years an increased understanding of the scientific value of results from very high resolution comprehensive numerical simulations.
This book documents the first international meeting focused specifically on high-resolution atmospheric and oceanic modeling held at the Earth Simulator Center. Rather than producing a standard conference proceedings it includes papers written by invited speakers at the meeting reporting on their most exciting recent results involving high resolution modeling.
This book shows that a conceptual design approach for spatio-temporal databases is both feasible and easy to apprehend. While providing a firm basis through extensive discussion of traditional data modeling concepts, the major focus of the book is on modeling spatial and temporal information. Parent, Spaccapietra and Zimányi provide a detailed and comprehensive description of an approach that fills the gap between application conceptual requirements and system capabilities, covering both data modeling and data manipulation features. The ideas presented summarize several years of research on the characteristics and description of space, time, and perception. In addition to the authors' own data modeling approach, MADS (Modeling of Application Data with Spatio-temporal features), the book also surveys alternative data models and approaches (from industry and academia) that target support of spatio-temporal modeling.
The reader will acquire intimate knowledge of both the traditional and innovative features that form a consistent data modeling approach. Visual notations and examples are employed extensively to illustrate the use of the various constructs. Therefore, this book is of major importance and interest to advanced professionals, researchers, and graduate or post-graduate students in the areas of spatio-temporal databases and geographical information systems.
"For anyone thinking of doing research in this field, or who is developing a system based on spatio-temporal data, this text is essential reading." (Mike Worboys, U Maine, Orono, ME, USA)
"The high-level semantic model presented and validated in this book provides essential guidance to researchers and implementers when improving the capabilities of data systems to serve the actual needs of applications and their users in the temporal and spatial domains that are so prevalent today." (Gio Wiederhold, Stanford U, CA, USA)
The author focuses on the conceptual understanding. The example time series and the exercises lead the reader to explore the meaning of concepts such as the estimation of the linear time series (AMRA) models or spectra.
This book is also a guide to using "R" for the statistical analysis of time series. "R" is a powerful environment for the statistical and graphical analysis of data."R" is available under GNU conditions.