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Climate data homogenization

Climate data are the records of observed climate conditions taken at specific sites and times with particular instruments under a set of standard procedures. A climate dataset therefore contains climate information at the observation sites, as well as other non-climate-related factors such as the environment of the observation station, and information about the instruments and observation procedures (Metadata).

These factors can be associated in the changes that can affect site, instruments or methods and procedures in the observations and data processing. Such changes can for example affect:

  • Sheltering and exposure,
  • Mean calculations, observation hours and daylight saving times;
  • Units of observed elements and data accuracy;
  • Urbanization and land-use changes;
  • Introduction of Automatic Weather Stations or new types of instruments
  • Quality control and data recovery procedures
  • Etc.

The aim of climate data homogenization is to adjust climate records, if necessary, to remove non-climatic factors so that the temporal variations in the adjusted data reflect only the variations due to climate processes.

WMO in collaboration with CCl developed a set of Guidelines on Climate Metadata and Homogenization on how to deal with in homogeneity problems. Main steps in data homogenization include:

  1. Metadata analysis and quality control: Changes in the measurement as well as in quality control procedures can be detected.
  2. Building of a reference time series: Mostly a weighted average is calculated by using neighboring stations.
  3. Breakpoint identification: It is searched for in-homogeneities in the difference between the weighted average and the candidate or in the candidate time-series itself.
  4. Data adjustment: It is decided which breakpoints are accepted as in-homogeneities. At the end the assessed discontinuities are adjusted and the data is corrected.
  5. For future projects and climate change studies it is important to document every step of the homogenization and data preservation.

Useful references:

Advances in homogenisation methods of climate series  (COST Action)

Data homogenization and climate change indices  

A case-study/guidance on the development of long-term daily adjusted temperature datasets 

Proceedings of the Sixth Seminar for Homogenization and Quality Control in Climatological Databases (Budapest, Hungary, 26-30 May 2008)


«Climate change detection and indices




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