Computer simulation has been a valuable tool in the physical, biological and social sciences for the last several decades. It has come to be regarded as yet another mode of scientific investigation accompanying theoretical analysis and experimentation. Yet validation and verification of simulation results have continued to be serious concerns. In some cases validation is relatively straightforward: run the simulation and compare the results against independent measured data. In other circumstances things are not so simple. A simulation of the interior of a star might be evaluated for consistency via measurements of secondary stellar characteristics, but it may be essentially impossible to confirm the details. Questions of validation and verification become even stickier when simulations are used to inform public policy. Of particular concern in the current book is the role of simulation in developing public policy for global climate change.
This is the second edition of a book originally published in 2006; some errors have been corrected and the sections on the Intergovernmental Panel on Climate Change have been expanded and revised. Unfortunately the book still has the appearance and style of a lightly edited doctoral dissertation.
The book is divided into two parts. The first part addresses simulation practice and its relationship to public policy in a broad context. The second focuses on global climate change. Of particular concern throughout is the assessment of uncertainty of simulation results. For the author, analysis of uncertainty is not a purely technical problem. Other uncertainties arise in the ways in which the problem is posed, models are structured, and expert judgments are made. The book is called a “philosophical study” because it explores the epistemological dimensions of scientific practice as well as the social and political aspects.
The first part of the book is broad and general, full of general guidelines and principles, and short on detail. Much of what is here is not illuminating and frankly makes for rather dull reading. In the second part, especially Chapters 5 and 6, the author applies his methodology to global climate simulation. Although the level of detail is higher here, it is still disappointingly low as is the overall technical content. It is understandable that the author’s interests are broader than the purely technical. (He expresses a good deal of concern, for example, about ad hoc modifications to models that may introduce biases.) Yet the technical details matter a great deal, and they tend to fade into a background of less than useful generalities.
Bill Satzer (firstname.lastname@example.org) is a senior intellectual property scientist at 3M Company, having previously been a lab manager at 3M for composites and electromagnetic materials. His training is in dynamical systems and particularly celestial mechanics; his current interests are broadly in applied mathematics and the teaching of mathematics.