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This book offers a set of case studies exemplifying the broad range of statistical science used in evnironmental studies and application. The case studies can be used for graduate courses in environmental statistics, as a resource for courses in statistics using genuine examples to illustrate statistical methodology and theory, and for courses in environmental science. Not only are these studies valuable for teaching about an essential cross-disciplinary activity, but also they can be used to spur new research along directions exposed in these examples. The studies reported here resulted from a program of research carried on by the National Institute of Statistical Sciences (NISS) during the years 1992-1996. NISS was created in 1991 as an initiative of the national statistics organizations, with the mission to renew and focus efforts of statistical science on important cross-disciplinary problems. One of NISS' first projects was a cooperative research effort with the U.S. EPA on problems of great interest to environmental science and regulation, surely one of today's most important cross-disciplinary activities.Douglas Nychka is Professor of Statistics at North Carolina State University and currently the Directory of the Geophysical Statistics Project at the National Center for Atmospheric Research. He has made contributions to the modeling of ozone pollution and the design of monitoring networks and has been author on more than 40 scientific papers. Walter W. Piegorsch is Professor of Statistics at the University of South Carolina and studies problems in design and analysis of environmental toxicity studies, low-dose risk extrapolation, and combining environmental information.
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The need to understand and predict the processes that influence the Earth's atmosphere is one of the grand scientific challenges for the next century. Due to the complexity of observational data and the variability of geophysical phenomena at many spatial and temporal scales, statistical science has an important role to play in this effort. This volume is a series of case studies and review chapters that cover many of the recent developments in statistical methodology that are useful for interpreting atmospheric data. Although the applications in this volume target atmospheric sciences, the statistical methodology is general and addresses many common problems that arise in the analysis of spatial and spatio-temporal data. For this reason, it would also serve as a statistical source for graduate students and other researchers across a broad range of geophysical and environmental sciences. L. Mark Berliner is Professor of Statistics at Ohio State University. He has served as Project Leader for the Geophysical Statistics Project (GSP) at the National Center for Atmospheric Research (NCAR), 1995-97. Douglas Nychka is the current GSP Leader and a Senior Scientist at NCAR.Timothy Hoar is an Associate Scientist at NCAR.