Guidelines on validation procedures for meteorological data from automatic weather stations
Quality control is a major prerequisite for using meteorological information. High quality data sources are vital to scientists, engineers and decision makers alike. Validation of meteorological data ensures that the information needed has been properly generated and that it identifies incorrect values and detects problems that require immediate maintenance attention. In this work, several quality assurance procedures based on different criteria are proposed and applied to meteorological data from the Agroclimatic Information Network of Andalusia (Southern Spain) to assess their integrity and quality. The procedures include validations of record structure data, range/limits, time and internal consistency, persistence and spatial consistency tests. Quality assurance tests consist of procedures or rules against which data are tested, setting data flags to provide guidance to end users. The proposed system is capable of identifying several types of errors and is used as a tool that allows one to make decisions such as sensor replacement and to remove data prior to their application. © 2011 Elsevier B.V.
| Main Authors: | , , |
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| Format: | artículo biblioteca |
| Language: | English |
| Published: |
Elsevier
2011-05-13
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| Subjects: | Quality control, Validation, Agrometeorology, Weather network, |
| Online Access: | http://hdl.handle.net/10261/88061 |
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| Summary: | Quality control is a major prerequisite for using meteorological information. High quality data sources are vital to scientists, engineers and decision makers alike. Validation of meteorological data ensures that the information needed has been properly generated and that it identifies incorrect values and detects problems that require immediate maintenance attention. In this work, several quality assurance procedures based on different criteria are proposed and applied to meteorological data from the Agroclimatic Information Network of Andalusia (Southern Spain) to assess their integrity and quality. The procedures include validations of record structure data, range/limits, time and internal consistency, persistence and spatial consistency tests. Quality assurance tests consist of procedures or rules against which data are tested, setting data flags to provide guidance to end users. The proposed system is capable of identifying several types of errors and is used as a tool that allows one to make decisions such as sensor replacement and to remove data prior to their application. © 2011 Elsevier B.V. |
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