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Earth System Science Data The Data Publishing Journal
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
Review article
28 Feb 2017
Review status
A revision of this discussion paper was accepted for the journal Earth System Science Data (ESSD) and is expected to appear here in due course.
Uncertainty information in climate data records from Earth observation
Christopher J. Merchant1,2, Frank Paul3, Thomas Popp4, Michael Ablain5, Sophie Bontemps6, Pierre Defourny6, Rainer Hollmann7, Thomas Lavergne8, Alexandra Laeng9, Gerrit de Leeuw10, Jonathan Mittaz1,11, Caroline Poulsen12, Adam C. Povey13, Maximilian Reuter14, Shubha Sathyendranath15, Stein Sandven16, Viktoria F. Sofeiva11, and Wolfgang Wagner17 1Department of Meteorology, University of Reading, Reading, RG6 6AL, UK
2National Centre for Earth Observation, University of Reading, Reading, RG6 6AL, UK
3Department of Geography, University of Zurich, Winterthurerstr. 190, 8057 Zurich, Switzerland
4Deutsches Zentrum für Luft-und Raumfahrt e. V., Deutsches Fernerkundungsdatenzentrum, 82234 Oberpfaffenhofen, Germany
5Collecte Localisation Satellite, 11 rue Hermès, 31520 Ramonville Saint-Agne, France
6Earth and Life Institute, Université catholique de Louvain, 1348 Louvain-la-Neuve, Belgium
7Deutscher Wetterdienst, Frankfurterstr. 135, 63500 Offenbach, Germany
8Norwegian Meteorological Institute, NO-0313 Oslo, Norway
9Karlsrhue Institute for Technology, Institut fur Meteorologie und Klimaforschung, 76021 Karlsruhe Germany
10Finnish Meteorological Institute, FIN-00101 Helsinki, Finland
11National Physical Laboratory, Teddington, TW11 0LW, UK
12Science and Technology Facilities Council, Rutherford Appleton Laboratory, Didcot, OX11 0QX, UK
13National Centre for Earth Observation, University of Oxford, Oxford, OX1 3PU, UK
14Institute of Environmental Physics, University of Bremen, Bremen, Germany
15Plymouth Marine Laboratory, Prospect Pl, Plymouth PL1 3DH, UK
16Nansen Environmental and Remote Sensing Center, Thormohlensgate 47, N_5006 Bergen, Norway
17Department of Geodesy and Geoinformation, Vienna University of Technology, 1040 Wien, Austria
Abstract. Climate data records (CDRs) derived from Earth observation (EO) should include rigorous uncertainty information, to support application of the data in policy, climate modelling and numerical weather prediction reanalysis. Uncertainty, error and quality are distinct concepts, and CDR products should follow international norms for presenting quantified uncertainty. Ideally, uncertainty should be quantified per datum in a CDR, and the uncertainty estimates should be able to discriminate more and less certain data with confidence. In this case, flags for data quality should not duplicate uncertainty information, but instead describe complementary information (such as the confidence held in the uncertainty estimate provided, or indicators of conditions violating retrieval assumptions). Errors have many sources and some are correlated across a wide range of time and space scales. Error effects that contribute negligibly to the total uncertainty in a single satellite measurement can be the dominant sources of uncertainty in a CDR on large space and long time scales that are highly relevant for some climate applications. For this reason, identifying and characterizing the relevant sources of uncertainty for CDRs is particularly challenging. Characterisation of uncertainty caused by a given error effect involves assessing the magnitude of the effect, the shape of the error distribution, and the propagation of the uncertainty to the geophysical variable in the CDR accounting for its error correlation properties. Uncertainty estimates can and should be validated as part of CDR validation, where possible. These principles are quite general, but the form of uncertainty information appropriate to different essential climate variables (ECVs) is highly variable, as confirmed by a quick review of the different approaches to uncertainty taken across different ECVs in the European Space Agency’s Climate Change Initiative. User requirements for uncertainty information can conflict with each other, and again a variety of solutions and compromises are possible. The concept of an ensemble CDR as a simple means of communicating rigorous uncertainty information to users is discussed. Our review concludes by providing eight recommendations for good practice in providing and communicating uncertainty in EO-based climate data records.

Citation: Merchant, C. J., Paul, F., Popp, T., Ablain, M., Bontemps, S., Defourny, P., Hollmann, R., Lavergne, T., Laeng, A., de Leeuw, G., Mittaz, J., Poulsen, C., Povey, A. C., Reuter, M., Sathyendranath, S., Sandven, S., Sofeiva, V. F., and Wagner, W.: Uncertainty information in climate data records from Earth observation, Earth Syst. Sci. Data Discuss.,, in review, 2017.
Christopher J. Merchant et al.
Interactive discussionStatus: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
Printer-friendly Version - Printer-friendly version      Supplement - Supplement
AC1: 'Minor corrections to note', Christopher J. Merchant, 22 Mar 2017 Printer-friendly Version 
RC1: 'Review', Anonymous Referee #1, 31 Mar 2017 Printer-friendly Version 
RC2: 'Review of ESSD-2017-16, Uncertainties', Anonymous Referee #2, 07 May 2017 Printer-friendly Version 
AC2: 'Final comments from authors', Christopher J. Merchant, 19 Jun 2017 Printer-friendly Version 
Christopher J. Merchant et al.
Christopher J. Merchant et al.


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Short summary
Climate data records (CDRs) contain data describing Earth's climate, and are often created from measurements by environmental satellites. CDRs should be created with great attention to how uncertain the data are, because it is important to understand what can is certain about climate changes, and what range of doubt exists. The paper proposes good practice for rigorous uncertainty information, and illustrates new developments from several projects of the Climate Change Initiative of ESA.
Climate data records (CDRs) contain data describing Earth's climate, and are often created from...