Journalartikel

Jahr der Veröffentlichung: 2010

Seiten: 5325-5331

Zeitschrift: Journal of Climate

Bandnummer: 23

Heftnummer: 19

ISSN: 0894-8755

eISSN: 1520-0442

Open Access Status: Bronze

DOI Link: https://doi.org/10.1175/2010JCLI3499.1

Verlag: American Meteorological Society

Abstract: 
Instrumental daily series of temperature are often affected by inhomogeneities. Several methods are available for their correction at monthly and annual scales, whereas few exist for daily data. Here, an improved version of the higher-order moments (HOM) method, the higher-order moments for autocorrelated data (HOMAD), is proposed. HOMAD addresses the main weaknesses of HOM, namely, data autocorrelation and the subjective choice of regression parameters. Simulated series are used for the comparison of both methodologies. The results highlight and reveal that HOMAD outperforms HOM for small samples. Additionally, three daily temperature time series from stations in the eastern Mediterranean are used to show the impact of homogenization procedures on trend estimation and the assessment of extremes. HOMAD provides an improved correction of daily temperature time series and further supports the use of corrected daily temperature time series prior to climate change assessment.

Harvard-Zitierstil: Toreti, A., Kuglitsch, F., Xoplaki, E., Luterbacher, J. and Wanner, H. (2010) A Novel Method for the Homogenization of Daily Temperature Series and Its Relevance for Climate Change Analysis, Journal of Climate, 23(19), pp. 5325-5331. https://doi.org/10.1175/2010JCLI3499.1

APA-Zitierstil: Toreti, A., Kuglitsch, F., Xoplaki, E., Luterbacher, J., & Wanner, H. (2010). A Novel Method for the Homogenization of Daily Temperature Series and Its Relevance for Climate Change Analysis. Journal of Climate. 23(19), 5325-5331. https://doi.org/10.1175/2010JCLI3499.1