In Memoriam

In Memoriam ing to ice jams, and the theory of ice jam mechanics. tion of available numerical models of river ice, dis- This theory originated in the early 1960s with the in- cussions of physical models of river ice, ice jam miti- sight that an ice jam could be considered a "floating gation, and ice jam data collection. The emphasis of granular mass" that is "subject to collapse when inter- these chapters is breadth of coverage rather than depth. nal stresses become too large." From this, the strength The bibliography is fairly complete and the reader in- of an ice jam can be estimated using limiting stability terested in greater detail will be able to make a good relationships borrowed from the field of soil mechan- start in the relevant literature. ics. Knowledge of the ice jam strength allows the jam The book closes with a case study of freezeup and thickness to be found. Given the jam thickness and breakup jams on the Peace River in Canada. (Even a hydraulic roughness, the flood levels resulting from cursory reader will quickly learn the difference an ice jam can be determined. Chapter 4 provides a between freezeup and breakup jams.) Examples pre- clear and succinct description of the mathematics of sented throughout the book are largely, although not this theory in more detail. These chapters are an ex- exclusively, Canadian. However, their import is inter- cellent exposition of a theory that has been success- national. This book is a very good introduction for fully applied at many locations, and that forms the those not familiar with ice jams. Several chapters, foundation of most current studies of ice jams. This especially chapter 4, are an excellent reference for description of ice jam mechanics should be consid- hydraulic engineers and others who desire to quanti- ered a "snapshot" of theory that is undergoing con- tatively estimate the effects of ice jams.—Steven F. tinual research and revision. Admitting that "our un- Daly. derstanding of most aspects of ice jams is incomplete," Beltaos finishes the chapter with major unknowns and Steven F. Daly is a research hydraulic engineer at research needs. the U.S. Army Cold Regions Research and Engineer- The remaining chapters contain a too-brief descrip- ing Laboratory in Hanover, New Hampshire. Singular Spectrum Analysis: A New Tool in ponent of specified parametric form (which may in- Time Series Analysis. James B. Eisner an d clude secular and periodic components) plus serially Anastasio s A . Tsonis. 1996 . 16 4 pp. $49.50 . independent noise with constant variance, then an ef- Hardbound . Plenum Publishing . ISB N 0-306-45472-6 . ficient decomposition can be based on ordinary least squares. If the deterministic component is known only to be smooth, then a smoothing method (such as spline The problem of decomposing a time series into meaningful components arises in many fields includ- fitting) can be applied. It is also possible to allow for ing atmospheric science. When the properties of the serial dependence of known structure, such as a low- components of a time series are known in advance, order autoregressive process, in the noise. In many the problem becomes much simpler. For example, if a situations, however, prior knowledge of time series time series is known to consist of a deterministic com- structure is unavailable and eyes search the skies—or at least the statistical literature—for nonparametric methods. Recently, a method called singular spectrum analysis has attracted attention as a method for isolat- ing modes of variation in oceanographic and atmo- 3n ji/Lrnixmami spheric time series. The book by Eisner and Tsonis is intended as a user's guide to this method. This short and highly readable book consists of three parts. The first part reviews the relevant mathemati- ^wmul jiixxA cal background: linear algebra, including eigenvalues 1914-1997 and eigenvectors. The second part lays out the theory and methods of singular spectrum analysis. Briefly, ^fka/tA singular spectrum analysis is an application of princi- pal component analysis (or empirical orthogonal func- 1905-1997 tion analysis), in which lagged versions of the origi- nal time series play the part of the variables (or spa- Vol. 78, , No. 70, October 1997 http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Bulletin of the American Meteorological Society American Meteorological Society
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Abstract

ing to ice jams, and the theory of ice jam mechanics. tion of available numerical models of river ice, dis- This theory originated in the early 1960s with the in- cussions of physical models of river ice, ice jam miti- sight that an ice jam could be considered a "floating gation, and ice jam data collection. The emphasis of granular mass" that is "subject to collapse when inter- these chapters is breadth of coverage rather than depth. nal stresses become too large." From this, the strength The bibliography is fairly complete and the reader in- of an ice jam can be estimated using limiting stability terested in greater detail will be able to make a good relationships borrowed from the field of soil mechan- start in the relevant literature. ics. Knowledge of the ice jam strength allows the jam The book closes with a case study of freezeup and thickness to be found. Given the jam thickness and breakup jams on the Peace River in Canada. (Even a hydraulic roughness, the flood levels resulting from cursory reader will quickly learn the difference an ice jam can be determined. Chapter 4 provides a between freezeup and breakup jams.) Examples pre- clear and succinct description of the mathematics of sented throughout the book are largely, although not this theory in more detail. These chapters are an ex- exclusively, Canadian. However, their import is inter- cellent exposition of a theory that has been success- national. This book is a very good introduction for fully applied at many locations, and that forms the those not familiar with ice jams. Several chapters, foundation of most current studies of ice jams. This especially chapter 4, are an excellent reference for description of ice jam mechanics should be consid- hydraulic engineers and others who desire to quanti- ered a "snapshot" of theory that is undergoing con- tatively estimate the effects of ice jams.—Steven F. tinual research and revision. Admitting that "our un- Daly. derstanding of most aspects of ice jams is incomplete," Beltaos finishes the chapter with major unknowns and Steven F. Daly is a research hydraulic engineer at research needs. the U.S. Army Cold Regions Research and Engineer- The remaining chapters contain a too-brief descrip- ing Laboratory in Hanover, New Hampshire. Singular Spectrum Analysis: A New Tool in ponent of specified parametric form (which may in- Time Series Analysis. James B. Eisner an d clude secular and periodic components) plus serially Anastasio s A . Tsonis. 1996 . 16 4 pp. $49.50 . independent noise with constant variance, then an ef- Hardbound . Plenum Publishing . ISB N 0-306-45472-6 . ficient decomposition can be based on ordinary least squares. If the deterministic component is known only to be smooth, then a smoothing method (such as spline The problem of decomposing a time series into meaningful components arises in many fields includ- fitting) can be applied. It is also possible to allow for ing atmospheric science. When the properties of the serial dependence of known structure, such as a low- components of a time series are known in advance, order autoregressive process, in the noise. In many the problem becomes much simpler. For example, if a situations, however, prior knowledge of time series time series is known to consist of a deterministic com- structure is unavailable and eyes search the skies—or at least the statistical literature—for nonparametric methods. Recently, a method called singular spectrum analysis has attracted attention as a method for isolat- ing modes of variation in oceanographic and atmo- 3n ji/Lrnixmami spheric time series. The book by Eisner and Tsonis is intended as a user's guide to this method. This short and highly readable book consists of three parts. The first part reviews the relevant mathemati- ^wmul jiixxA cal background: linear algebra, including eigenvalues 1914-1997 and eigenvectors. The second part lays out the theory and methods of singular spectrum analysis. Briefly, ^fka/tA singular spectrum analysis is an application of princi- pal component analysis (or empirical orthogonal func- 1905-1997 tion analysis), in which lagged versions of the origi- nal time series play the part of the variables (or spa- Vol. 78, , No. 70, October 1997

Journal

Bulletin of the American Meteorological SocietyAmerican Meteorological Society

Published: Oct 1, 1997

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