Economics Dictionary of ArgumentsHome
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| Homogenization: Data homogenization is the process of standardizing and unifying data from different sources to ensure consistency and compatibility and modeling across different sources or time periods. See also Data, Method, Measurements, Comparability, Climate periods, Climate history._____________Annotation: The above characterizations of concepts are neither definitions nor exhausting presentations of problems related to them. Instead, they are intended to give a short introduction to the contributions below. – Lexicon of Arguments. | |||
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Hans von Storch on Homogenization - Dictionary of Arguments
Norgaard I 116 Homogenization/Parameterization/von Storch: The climate system has different ‘compartments’ (…). (…) due to the unavoidable discrete description of the system, turbulence cannot be described in mathematical accuracy, and the equations need to be ‘closed’—the effect of friction, in particular at the boundaries between land, atmosphere, and ocean, need to be ‘parameterized’ (e.g. Washington and Parkinson 2005)(1). Norgaard I 117 The basic idea is that there is a set of ‘state variables’ {Ψ} (among them the temperature field at a certain time t at certain discrete positions on the globe), which describe the system, and which dynamics is given by a differential equation d{Ψ}/dt = F({Ψ}). [An] aspect of parameterizations is their strong dependence on the spatial resolution. When the model is changed to run on a higher resolution, the parameterizations need to be reformulated or respecified. There is no rule how to do that, when the spatial resolution is increased—which means that the difference equations do not converge towards a pre‐specified set of differential equations, or, in other words: there is nothing like a set of differential equations describing the climate system per se, as is the case in most physical disciplines. >Parameterization. Norgaard I 120 [Another aspect is that] the ‘instrumental’ data usually suffer from ‘inhomogeneities’ (e.g. Jones 1995(2); Karl et al. 1993(3)). Before using such data in climate analysis, the series have to be ‘homogenized’ (e.g. Peterson et al. 1998)(4). 1. Washington, W. M., and Parkinson, C. L. 2005. An Introduction to Three‐Dimensional Climate Modelling. 2nd edn., Sausalito, CA: University Science Books. 2. Jones, P. D. 1995. The instrumental data record: Its accuracy and use in attempts to identify the ‘CO2 Signal’. Pp. 53–76 in H. von Storch and A. Navarra (eds.), Analysis of Climate Variability: Applications of Statistical Techniques. Berlin: Springer Verlag. 3. Karl, T. R., Quayle, R. G., and Groisman, P. Y. 1993. Detecting climate variations and change: New challenges for observing and data management systems. J. Climate 6: 1481–94. 4. Peterson, T. C., Easterling, D. R., Karl, T. R., Groisman, P., Nicholls, N., Plummer, N., Torok, S., Auer, I., Boehm, R., Gullett, D., Vincent, L., Heino, R., Tuomenvirta, H., Mestre, O., Szentimrey, T., Saliner, J., Førland, E., Hanssen‐Bauer, I., Alexandersson, H., Jones, P., and Parker, D. 1998. Homogeneity adjustments of in situ atmospheric climate data: A review. Intern. J. Climatol. 18: 1493–517. Hans von Storch, Armin Bunde, and Nico Stehr, „Methodical Challenges of the Physics of Climate”, in: John S. Dryzek, Richard B. Norgaard, David Schlosberg (eds.) (2011): The Oxford Handbook of Climate Change and Society. Oxford: Oxford University Press._____________Explanation of symbols: Roman numerals indicate the source, arabic numerals indicate the page number. The corresponding books are indicated on the right hand side. ((s)…): Comment by the sender of the contribution. Translations: Dictionary of Arguments The note [Concept/Author], [Author1]Vs[Author2] or [Author]Vs[term] resp. "problem:"/"solution:", "old:"/"new:" and "thesis:" is an addition from the Dictionary of Arguments. If a German edition is specified, the page numbers refer to this edition. |
Storch, Hans von Norgaard I Richard Norgaard John S. Dryzek The Oxford Handbook of Climate Change and Society Oxford 2011 |
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