Climate Dynamics

, Volume 42, Issue 11–12, pp 2841–2866 | Cite as

An evaluation of the statistical homogeneity of the Twentieth Century Reanalysis

Article

Abstract

The Twentieth Century Reanalysis (20CR) holds the distinction of having the longest record length (140-year; 1871–2010) of any existing global atmospheric reanalysis. If the record can be shown to be homogenous, then it would be the first reanalysis suitable for long-term trend assessments, including those of the regional hydrologic cycle. On the other hand, if discontinuities exist, then their detection and attribution—either to artificial observational shocks or climate change—is critical to their proper treatment. Previous research suggested that the quintupling of 20CR’s assimilated observation counts over the central United States was the primary cause of inhomogeneities for that region. The same work also revealed that, depending on the season, the complete record could be considered homogenous. In this study, we apply the Bai-Perron structural change point test to extend these analyses globally. A rigorous evaluation of 20CR’s (in)homogeneity is performed, composed of detailed quantitative analyses on regional, seasonal, inter-variable, and intra-ensemble bases. The 20CR record is shown to be homogenous (natural) for 69 (89) years at 50 % of land grids, based on analysis of the July 2 m air temperature. On average 54 % (41 %) of the grids between 60°S and 60°N are free from artificial inhomogenetites in their February (July) time series. Of the more than 853,376 abrupt shifts detected in 26 variable fields over two monthly time series, approximately 72 % are non-climate in origin; 25 % exceed 1.8 standard deviations of the preceding time series. The knock-on effect of inhomogeneities in 20CR’s boundary forcing and surface pressure data inputs to its surface analysis fields is implicated. In the future, reassessing these inhomogeneities will be imperative to achieving a more definitive attribution of 20CR’s abrupt shifts.

Keywords

Twentieth Century Reanalysis Change point detection Climate trend analysis Observational shocks Sparse data assimilation 

Supplementary material

382_2013_1996_MOESM1_ESM.pdf (7.4 mb)
Supplementary material 1 (PDF 7585 kb)

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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  1. 1.Department of Hydrology and Water Resources Engineering, Institute of Industrial ScienceThe University of TokyoTokyoJapan
  2. 2.Department of Environmental Resources EngineeringThe State University of New York College of Environmental Science and ForestrySyracuseUSA
  3. 3.IIHR, Hydroscience & EngineeringThe University of IowaIowa CityUSA

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