Definition

It is often important to determine if a set of data is homogeneous before any statistical technique is applied to it. Homogeneous data are drawn from a single population. In other words, all outside processes that could potentially affect the data must remain constant for the complete time period of the sample. Inhomogeneities are caused when artificial changes affect the statistical properties of the observations through time. These changes may be abrupt or gradual, depending on the nature of the disturbance. Realistically, obtaining perfectly homogeneous data is almost impossible, as unavoidable changes in the area surrounding the observing station will often affect the data.

Interpreting climate data with unknown homogeneity:

• Many observed trends are the result of inhomogeneities and not some other large-scale climatic change (e.g., global warming).
• Characterizing a short-term artificially-induced trend as natural variations in the climate system can cause substantial errors in conclusions drawn from the data.
• The interpretation of a given process depends on the time scales considered (i.e., analyses using short time scales should not be used as evidence to support phenomena observed over larger time scales).

Source

Columbia University

NESDIS Data Management Lexicon and Related Terms 

Category

4. Data Stewardship words