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Uncertainty information in climate data records from Earth observation

Merchant, Christopher J.; Paul, Frank; Popp, Thomas; Ablain, Michael; Bontemps, Sophie; Defourny, Pierre; Hollmann, Rainer; Lavergne, Thomas; Laeng, Alexandra 1; Leeuw, Gerrit de; Mittaz, Jonathan; Poulsen, Caroline; Povey, Adam C.; Reuter, Max; Sathyendranath, Shubha; Sandven, Stein; Sofieva, Viktoria F.; Wagner, Wolfgang
1 Karlsruher Institut für Technologie (KIT)

Abstract:

The question of how to derive and present uncertainty information in climate data records (CDRs) has received sustained attention within the European Space Agency Climate Change Initiative (CCI), a programme to generate CDRs addressing a range of essential climate variables (ECVs) from satellite data. Here, we review the nature, mathematics, practicalities, and communication of uncertainty information in CDRs from Earth observations. This review paper argues that CDRs derived from satellite-based Earth observation (EO) should include rigorous uncertainty information to support the application of the data in contexts such as policy, climate modelling, and numerical weather prediction reanalysis. Uncertainty, error, and quality are distinct concepts, and the case is made that CDR products should follow international metrological norms for presenting quantified uncertainty. As a baseline for good practice, total standard uncertainty should be quantified per datum in a CDR, meaning that uncertainty estimates should clearly discriminate more and less certain data. In this case, flags for data quality should not duplicate uncertainty information, but instead describe complementary information (such as the confidence in the uncertainty estimate provided or indicators of conditions violating the retrieval assumptions). ... mehr


Volltext §
DOI: 10.5445/IR/1000072944
Originalveröffentlichung
DOI: 10.5194/essd-9-511-2017
Scopus
Zitationen: 109
Web of Science
Zitationen: 108
Dimensions
Zitationen: 112
Cover der Publikation
Zugehörige Institution(en) am KIT Institut für Meteorologie und Klimaforschung – Atmosphärische Spurenstoffe und Fernerkundung (IMK-ASF)
KIT-Zentrum Klima und Umwelt (ZKU)
Publikationstyp Zeitschriftenaufsatz
Publikationsjahr 2017
Sprache Englisch
Identifikator ISSN: 1866-3508, 1866-3516
urn:nbn:de:swb:90-729440
KITopen-ID: 1000072944
HGF-Programm 12.04.05 (POF III, LK 01) Trends,Variaility,Large-Scale Processes
Erschienen in Earth system science data
Verlag Copernicus Publications
Band 9
Heft 2
Seiten 511-527
Nachgewiesen in Dimensions
Web of Science
Scopus
Globale Ziele für nachhaltige Entwicklung Ziel 13 – Maßnahmen zum Klimaschutz
KIT – Die Forschungsuniversität in der Helmholtz-Gemeinschaft
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