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Fundamentals of Atmospheric Radiation
Meeting the need for teaching material suitable for students of atmospheric science and courses on atmospheric radiation, this textbook covers the fundamentals of emission, absorption, and scattering of electromagnetic radiation from ultraviolet to infrared and beyond. Much of the contents applies to planetary atmosphere, with graded discussions providing a thorough treatment of subjects, including single scattering by particles at different levels of complexity. The discussion of the simple multiple scattering theory introduces concepts in more advanced theories, such that the more complicated two-stream theory allows readers to progress beyond the pile-of-plates theory. The authors are physicists teaching at the largest meteorology department in the US at Penn State. The problems given in the text come from students, colleagues, and correspondents, and the figures designed especially for this book facilitate comprehension. Ideal for advanced undergraduate and graduate students of atmospheric science. * Free solutions manual available for lecturers at www.wiley-vch.de/supplements/
Radiation and Water in the Climate System
The study of the earth's climate requires reliable global data sets to validate numerical simulation models and to identify regional and global fluctuations and trends. This book presents ways to obtain such data from space-borne and ground-based measurements, both passive and active, over the entire electromagnetic spectrum. It describes the basics of such methods together with the most recent advancements and spans the field from clouds and the planetary radiation budget to surface processes and ocean properties. Each subject is backed by extensive reference lists to enable readers to probe more deeply.
Neural Nets: Applications in Geography
Neural nets offer a fascinating new strategy for spatial analysis, and their application holds enormous potential for the geographic sciences. However, the number of studies that have utilized these techniques is limited. This lack of interest can be attributed, in part, to lack of exposure, to the use of extensive and often confusing jargon, and to the misapprehension that, without an underlying statistical model, the explanatory power of the neural net is very low. Neural Nets: Applications for Geography attacks all three issues; the text demonstrates a wide variety of neural net applications in geography in a simple manner, with minimal jargon. The volume presents an introduction to neura...
3D Radiative Transfer in Cloudy Atmospheres
Developments in three-dimensional cloud radiation over the past few decades are assessed and distilled into this contributed volume. Chapters are authored by subject-matter experts who address a broad audience of graduate students, researchers, and anyone interested in cloud-radiation processes in the solar and infrared spectral regions. After two introductory chapters and a section on the fundamental physics and computational techniques, the volume extensively treats two main application areas: the impact of clouds on the Earth's radiation budget, which is an essential aspect of climate modeling; and remote observation of clouds, especially with the advanced sensors on current and future satellite missions.
How We Learn; How We Remember:toward An Understanding Of Brain And Neural Systems - Selected Papers Of Leon N Cooper
Leon Cooper's somewhat peripatetic career has resulted in work in quantum field theory, superconductivity, the quantum theory of measurement as well as the mechanisms that underly learning and memory. He has written numerous essays on a variety of subjects as well as a highly regarded introduction to the ideas and methods of physics for non-physicists. Among the many accolades, he has received (some deserved) one he likes specially is the comment of an anonymous reviewer who characterized him as “a nonsense physicist”.This compilation of papers presents the evolution of his thinking on mechanisms of learning, memory storage and higher brain function. The first half proceeds from early mo...
