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Global historical climatology network (GHCN) quality control of monthly temperature data
Author(s) -
Peterson Thomas C.,
Vose Russell,
Schmoyer Richard,
Razuvaëv Vyachevslav
Publication year - 1998
Publication title -
international journal of climatology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.58
H-Index - 166
eISSN - 1097-0088
pISSN - 0899-8418
DOI - 10.1002/(sici)1097-0088(199809)18:11<1169::aid-joc309>3.0.co;2-u
Subject(s) - computer science , suite , outlier , quality assurance , quality (philosophy) , data set , data quality , climatology , set (abstract data type) , data mining , geography , artificial intelligence , geology , engineering , philosophy , epistemology , metric (unit) , operations management , external quality assessment , archaeology , programming language
All geophysical data bases need some form of quality assurance. Otherwise, erroneous data points may produce faulty analyses. However, simplistic quality control procedures have been known to contribute to erroneous conclusions by removing valid data points that were more extreme than the data set compilers expected. In producing version 2 of the global historical climatology network's (GHCN's) temperature data sets, a variety of quality control tests were evaluated and a specialized suite of procedures was developed. Quality control traditionally relies primarily on checks for outliers from both a time series and spatial perspective, the latter accomplished by comparisons with neighbouring stations. This traditional approach was used, and it was determined that there are many data problems that require additional tests to detect. In this paper a suite of quality control tests are justified and documented and applied to this global temperature data base, emphasizing the logic and limitations of each test. © 1998 Royal Meteorological Society