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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.

Author Concept Summary/Quotes Sources

Climatology on Homogenization - Dictionary of Arguments

Edwards I 401
Homogenization/climatology/Edwards: (…) observing systems and standards changed often and rapidly over time, creating temporal discontinuities and inconsistencies. These “inhomogeneities,” as meteorologists call them, rendered large quantities of weather data unusable for climatological purposes. Yet in recent decades, with fast, high-quality 4-D data assimilation, forecasting and climatology have begun to converge. Reanalysis of global weather data is producing - for the first time - consistent, gridded data on the planetary circulation, over periods of 50 years or more, at resolutions much higher than those achieved with traditional climatological data sets. Reanalysis may never replace traditional climate data, since serious concerns remain about how assimilation models “bias” data when integrated over very long periods. >Reanalysis/climatology
Edwards I 402
Nonetheless, the weather and climate data infrastructures are now inextricably linked by the “models of data” each of these infrastructures requires in order to project the atmosphere’s future and to know its past.
>Models/metereology, >Weather data/metereology.
Edwards I 406
Reanalysis: permits true four-dimensional assimilation, in which future observations as well as past observations can influence the state of the analysis at any point in time.(1)
Edwards I 415
Inhomogeneities: Most inhomogeneities in climate data have little political valence, but there are important exceptions. As we saw in chapter 8, during the Cold War the Soviet Union withheld some data, while the People’s Republic of China withheld virtually all data. These data were not included in any Western climate data set until the mid 1980s.(2)
Some recent work suggests that systematic errors may be more widespread than was previously believed. For example, nineteenth-century meteorologists throughout the Alps placed precipitation gauges on rooftops and thermometers
Edwards I 416
thermometers in windows; later, they moved precipitation gauges to ground level and mounted thermometers inside screening devices placed in open areas (thus reducing the artifactual effects of buildings and pavement). Although stations modified their instrument placement at different times, precipitation measurements were systematically higher and temperature measurements lower after instrument placements were changed.(3)
Satellite data: A different and much more problematic issue arises with respect to satellite data. (…) most raw sensor readings from satellites require some kind of processing to convert them into meteorological information. This can be a complex modeling process, as in the inversion of microwave radiances, but it also can be a much simpler data-reduction process. >Reanalysis/climatology, >Model bias/climatology.

1. K. E. Trenberth, “Atmospheric Circulation Climate Changes,” Climatic Change 31, no. 2 (1995), 306.
2. 15. P. D. Jones et al., A Gridpoint Surface Air Temperature Data Set for the Northern Hemisphere (US Department of Energy, Carbon Dioxide Research Division, 1985), 1.
3. R. Boehm et al., “Regional Temperature Variability in the European Alps: 1760–8 From Homogenized Instrumental Time Series,” International Journal of Climatology 21, no. 14 (2001): 1779–; Auer et al., “Metadata and Their Role in Homogenising.”

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.
Edwards I
Paul N. Edwards
A Vast Machine: Computer Models, Climate Data, and the Politics of Global Warming Cambridge 2013

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