Physics and Chemistry of Clouds

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Clouds affect our daily weather and play key roles in the global climate. Through their ability to precipitate, clouds provide virtually all of the fresh water on Earth and are a crucial link in the hydrologic cycle. With ever-increasing importance being placed on quantifiable predictions - from forecasting the local weather to anticipating climate change � � we must understand how clouds operate in the real atmosphere, where interactions with natural and anthropogenic pollutants are common. This textbook provides students - whether seasoned or new to the atmospheric sciences - with a quantitative yet approachable path to learning the inner workings of clouds. Developed over many years of the authors' teaching at Pennsylvania State University, Physics and Chemistry of Clouds is an invaluable textbook for advanced students in atmospheric science, meteorology, environmental sciences/engineering and atmospheric chemistry. It is also a very useful reference text for researchers and professionals.

Physics and Chemistry of Clouds Review

I'm a PhD student in atmospheric science, and when I took grad-level cloud physics a couple of years ago, there simply wasn't a great grad-level cloud physics text available. We used A Short Course in Cloud Physics, Third Edition (International Series in Natural Philosophy) for the course, but after a few weeks it started collecting dust on my bookshelf where it has remained since. My class notes were the only good source of reference material on cloud physics until now, with the publication of the Lamb & Verlinde text.

I highly recommend this book for undergrads, grads, or researchers who deal with cloud microphysics or cloud dynamics on a regular basis. The authors begin with an overview of the role of clouds in the atmosphere, then focus on phases transformations and cloud macrophysics. I'm the most interested in the chapters on cloud microphysics - nucleation, vapor growth, and collision-coalescence. The last part of the book includes chapters that discuss the effects of supersaturation, warm clouds, cold clouds, cloud chemistry, and cloud electrification.

I bought this book for my reference library so I haven't read it cover to cover yet, but I'd recommend it highly to anyone interested in cloud physics.

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Digital Filters: Basics and Design

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This textbook provides an insight into the characteristics and design of digital filters. It includes tables of filter parameters for Butterworth, Chbeyshev, Cauer and Bessel filters and several computer routines for filter design programs.

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Digital Filters: Basics and Design Review

The difficulty comes really as a by product of the sheer size of the knowledge base in this subject. There are now so many papers published on each of the chapter headings that perhaps most writing projects of this sort would end up in an interminable fog. But there is an urgent need for such books, now that almost anyone can afford a DSP development kit, and you can create the most astonishing filters with characteristics that would be unimaginable some 20 years ago.But you would need help, and attempting to cover the whole field of design techniques is very difficult in a short time. Mind you, this book is by far one of the best I have ever seen. For instance, it covers the design of elliptic filters, though not really in the depth that you would need to be SURE.. pp27-33 is all there is here. But nontheless, I like the fact the the discussion isn't superficial, and that the sn function is drawn really well, and so on, but I think that more examples are really needed, and especially more help with translating requirments into actual elliptic filters.There is a section on filter architecture, and this is quite separate from the section on the various low pass approximations. Some terrible books recently have been written in such a way as to mix the two subjects, which is always an invitation to disaster.The section of Wave Digital filters is admirable. The work by Fetweiss has proved to be much more important than was suspected at the time, and there is some evidence that knowledge of wave digital filters is becoming desirable knowledge for some prospective employers, at least in the UK and Europe...The idea of covering limit cycles is a brave move, considering how complicated and unnerving this may be for beginners. This is done very well. Even better are the chapters on fixed point roundoff noise - so very important to those of us without floating point hardware to hand! This chapter is superb, and really goes a LONG way toward helping solve real problems. This was my favorite chapter of all.There is one deficiency in the book, and that is in design techniques where the phase alone is to be prescribed. This is a little alarming. All-pass filters are not even mentioned in the index - this might also cover the Hilbert transform for instance. Another class of filter not described are those filters which produce a pair of outputs with a quadrature relationship between them.Neither is the subject of filterbank design covered at all (aka perfect reconstruction, and all that). But that's rather specialised.I can't help but admire the book, and would only gently recommend to use it with other books which are perhaps more dilute in some ways, but perhaps in certain specialised areas, more replete with examples. But otherwise, do get it, since it's very unlikely that you won't be pleasantly surprised and very much informed by it. Help other customers find the most helpful reviews� Was this review helpful to you?�Yes No Report abuse | PermalinkComment�Comment

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Introduction to Computational Science: Modeling and Simulation for the Sciences

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Computational science is a quickly emerging field at the intersection of the sciences, computer science, and mathematics because much scientific investigation now involves computing as well as theory and experiment. However, limited educational materials exist in this field. Introduction to Computational Science fills this void with a flexible, readable textbook that assumes only a background in high school algebra and enables instructors to follow tailored pathways through the material. It is the first textbook designed specifically for an introductory course in the computational science and engineering curriculum.

The text embraces two major approaches to computational science problems: System dynamics models with their global views of major systems that change with time; and cellular automaton simulations with their local views of how individuals affect individuals. While the text is generic, an extensive author-generated Web-site contains tutorials and files in a variety of software packages to accompany the text.

• Generic software approach in the text
• Web site with tutorials and files in a variety of software packages
• Engaging examples, exercises, and projects that explore science
• Additional, substantial projects for students to develop individually or in teams
• Consistent application of the modeling process
• Quick review questions and answers
• Projects for students to develop individually or in teams
• Reference sections for most modules, as well as a glossary
• Online instructor's manual with a test bank and solutions

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Introduction to Computational Science: Modeling and Simulation for the Sciences Review

I enjoyed reading this book very much.

I found the book very useful in its conceptualization of simulation as a new form of synthesis for acquiring knowledge and helping human being make decisions. Simulation is a form of communication in that empirically-based models could be used to view the on-going processes that are cognitively beyond the capacity of human mind to untangle.

Furthermore, I found it admirable that the authors had instructed the readers in the art of model building using widely available simulation tools or even tools such as MS Excel that are not built specifically for the purpose of simulations.

I especially liked the tutorials with their wide selection of interesting material.

Regrettably, the subject matter of the book - simulation & (dynamic model building) - does not fit well within the traditional physics curriculum: Mechanics, Electromagnetism, and Quantum Mechanics. Numerical methods, including simulations, are not emphasized in such courses and normally one spends much of one's time studying well-known and solvable (in closed, analytical form) problems.

That does not mean that there is no room in physics for modeling and simulation: fractals, galaxy formation, dynamics of globular clusters, etc. are all areas that we are dependent on our numerical models and their fitness to observed phenomena to understand the processes of Nature. However, these are usually advanced topics not covered in undergraduate curricula.

And then the physicists tend to want to build their own tools rather that use COTS packages.

I think it is difficult to find a home in traditional university departments for a course on simulation based on this book. The fundamental reason, in my opinion, is that the personal computer as a scientific instrument is not valued or appreciated. And from that follows the lack of interest in simulations as venues for gaining scientific knowledge in Physics, in Chemistry & Biology. Conceivably a course in simulations might be of interest to engineers but then we would be leaving all those "soft"-science majors such as Ecology or Public Health behind. And those soft-science students are among some the people who could benefit the most from this book.

For example, the gene<->protein<->enzyme interactions, with their feedback loops and multiple pathways, are so complex that no human mind could expect to grasp all that goes on inside a cell. So Module 6.3 covering enzyme dynamics is absolutely on the right track from a scientific perspective; taking simulation out of the "hard" science world and into biology. Only through simulations and modeling are we going to develop a synthetic understanding of the cell in all its complexity.

I do not know if you have seen the book, "Historical Dynamics" by Peter Turchin in which he presents and discusses mathematical models of the evolution of agrarian states on the Eurasian land mass. His models are informed by empirical data collected from historical sources and do capture many aspects of historical reality. There is clearly a very important paradigm here at work but which is not as enunciated as I believe it should be; namely that simulations extend our scientific evidentiary-based knowledge into hitherto for dark realms of empirical experience.

Yet, Turchin did not use a simulation tool; he rolled his own and wrote much of his code in APL (A Programming Language) which is quite obscure. So readers must redo the models themselves. And his book is not about simulations, it is about what simulations tell us about history. I think that there are many fields of study in which the students could benefit from parts of this book; history, sociology, ecology, and natural resources comes to mind. There the exposition must be based heavily on using Commercial Off-the-Shelf (COTS) packages to tech the students how to build useful models.

So, for students in "soft" departments, the material in modules 5.2, 5.3, 5.4 could be skipped. In fact, even for students of physics and engineering, the understanding of the basis of the numerical simulations is not as important as learning how to build a system and observing how it behaves. On the other hand, the module 2, in my opinion, is important for all students to understand and to master so that they may interpret the results of their simulations correctly.

In my own case, I would love to be able to use a COTS package in which I could put galaxies - using a visual palette tool - on a 3-dimensional grid and observe their evolution in time as I changed the metric of space-time and/or the equation of state of the matter field.

Or consider the equations of stellar evolution, one would love to be able to run them again and again by changing parameters of these models knowing that the fundamental equations and their integration were worked out 70 years ago. As it is today, there are no such user-friendly generic approaches available to students or researchers, all such things must be painfully hand-crafted almost from scratch, barring some software libraries.

On a few occasions that I imagined writing such a book myself, I realized how difficult it was to do justice to the breadth and depth of the field of simulations from its hard-core physical scieces and engineering to ecology and wild-life management in a single book. While I might quibble with the inclusion of this or that topic or technique, I really cannot come up with a better design. There is an enormous amount of material here that may or may not be of interest to all audiences but there is a lot of material that is of interest to special audiences with focus on this or that scientific field.

The authors, if I understand them correctly, are positing that simulations (Computational Sciences) are a new way of knowledge discovery. In this they are right, in my opinion and are in the company of such luminaries as Dr. Steven Wolfram of Mathematic fame. But the problem is that "Introduction to Simulations" used to be taught in Industrial Engineering departments and then moved to places like the RAND Corporation and then the Pentagon. It is not viewed as a subject worthy of study in its own right (although such simulations as Halo or the World of War Craft sell millions of copies and make a few people wuite wealthy).

Which brings me to another topic related to simulations and to this book; namely computer games. Computer games are also simulations but with the caveat that they do not follow the Laws of Physics, Chemistry, and Biology and therefore are on somewhat of a tangent to "scientific" simulations such as those covered in this book. Gamers perform simulations, cosmologists do simulations, climatologists do simulations, agronomists do simulations, and many others but there is not set curriculum, no defined or unified approach and indeed no place to go to get an introduction to the art and science of simulation in a typical undergraduate college. This book is an attempt at just that.

I think non-science majors in Liberal Arts colleges could benefit also from a simulation course based on this book. Some colleges have a unified natural science department without the traditional divisions among Physics, Chemistry, Mathematics, and Biology. In such an environment, a course based on this book may offer that the non-science majors - a la Turchin's approach - the prospect of gaining confidence in building quantitative models of Reality and making inferences about the world on basis of such models.

This is a good book and a path-breaking book and I hope it finds the traction that it so righty deserves.

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Time Series Analysis by State Space Methods: Second Edition (Oxford Statistical Science Series)

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This new edition updates Durbin & Koopman's important text on the state space approach to time series analysis. The distinguishing feature of state space time series models is that observations are regarded as made up of distinct components such as trend, seasonal, regression elements and disturbance terms, each of which is modelled separately. The techniques that emerge from this approach are very flexible and are capable of handling a much wider range of problems than the
main analytical system currently in use for time series analysis, the Box-Jenkins ARIMA system. Additions to this second edition include the filtering of nonlinear and non-Gaussian series.

Part I of the book obtains the mean and variance of the state, of a variable intended to measure the effect of an interaction and of regression coefficients, in terms of the observations.

Part II extends the treatment to nonlinear and non-normal models. For these, analytical solutions are not available so methods are based on simulation.

Time Series Analysis by State Space Methods: Second Edition (Oxford Statistical Science Series) Review

"Preface to Second Edition", found via "Search inside", discusses the changes since the first edition, and these do address readers' comments on that book's Amazon page, by expanding coverage of the non-linear/non-normal case. I must say the book still feels like one about Kalman filter, but page-count comparisons* I now invoke to justify this feeling may be misleading. "Time series analysis by state space methods" was not quite what I was looking for - I'd prefer something less dry/technical, and more application-minded and hands-on (regrettably, readers' complaints regarding companion software have not been heeded; this, and the book's steep price, are my excuse not to give it five stars) - and I did not dig deep, but the overall impression is that of a comprehensive, rigorous and reasonably compact exploration of the field.

* The "non-linear/non-normal" Part II has half as many pages as the "linear/normal" Part I; linearity gains extra ground in Part II's chapter on approximate methods (including extended and unscented Kalman filer), and leaves less space for particle filtering. The latter gets a total of 23 pages; I opted to read the survey paper by Drew Creal, available online, and to revisit the concluding chapter of "Dynamic linear models with R" by Petris et al.

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Essentials of Radiographic Physics and Imaging

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From basic physics principles to the actual process of producing diagnostic-quality x-rays, Essentials of Radiographic Physics and Imaging effectively guides you through the physics and imaging information you need to excel on your ARRT exam and as a professional radiographer. The text's clear language and logical organization help you easily master physics principles as they apply to imaging, plus radiation production and characteristics, imaging equipment, film screen image acquisition and processing, digital image acquisition and display, basics of computed tomography, image analysis, and more. Theory to Practice discussions help you link these principles to real-world applications and practice.

Essentials of Radiographic Physics and Imaging Review

This book was the simplest book out of all the books which we used for physics and it was very informative.

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