Abstract

Volume‐area power law scaling, one of a set of analytical scaling techniques based on principals of dimensional analysis, has become an increasingly important and widely used method for estimating the future response of the world's glaciers and ice caps to environmental change. Over 60 papers since 1988 have been published in the glaciological and environmental change literature containing applications of volume‐area scaling, mostly for the purpose of estimating total global glacier and ice cap volume and modeling future contributions to sea level rise from glaciers and ice caps. The application of the theory is not entirely straightforward, however, and many of the recently published results contain analyses that are in conflict with the theory as originally described by Bahr et al. (1997). In this review we describe the general theory of scaling for glaciers in full three‐dimensional detail without simplifications, including an improved derivation of both the volume‐area scaling exponent γ and a new derivation of the multiplicative scaling parameter c. We discuss some common misconceptions of the theory, presenting examples of both appropriate and inappropriate applications. We also discuss potential future developments in power law scaling beyond its present uses, the relationship between power law scaling and other modeling approaches, and some of the advantages and limitations of scaling techniques.

Highlights

  • Power law representations of natural phenomena, and the application of dimensional analysis and rescaling operations, have been conspicuously successful in the analysis of complex systems in physics, biology, and various natural sciences for more than a century

  • Volume-area power law scaling, one of a set of analytical scaling techniques based on principals of dimensional analysis, has become an increasingly important and widely used method for estimating the future response of the world’s glaciers and ice caps to environmental change

  • While the results embodied in the 15 dimensionless groups defined above were obtained with essentially no knowledge of glacier mechanics, neither can much understanding of the underlying mechanics be deduced from those 15 groups

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Summary

Introduction

Power law representations of natural phenomena, and the application of dimensional analysis and rescaling operations, have been conspicuously successful in the analysis of complex systems in physics, biology, and various natural sciences for more than a century. Related concepts and practices identified by Newton and by Maxwell, Fourier, and others were applied to problems in mechanics, electrodynamics, fluid mechanics, and heat transfer. These eventually became codified in principles known variously as geometric, kinematic, and dynamic similitude, dimensional analysis, and in many cases have led to well-known power law structures. The ubiquity of power law-type structure in natural processes has been explained in terms of statistical theory [e.g., Pietronero et al, 2001] and is understood to be shaped by specific aspects of a given application but determined by very broad principals

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