Abstract
The uncertainty in a climate data records (CDRs) derived from Earth observations in part derives from the propagated uncertainty in the radiance record (the fundamental climate data record, FCDR) from which the geophysical estimates in the CDR are derived. A common barrier to providing uncertainty-quantified CDRs is the inaccessibility to CDR creators of appropriate radiance uncertainty information in the FCDR. Here, we propose radiance uncertainty information designed directly to facilitate estimation of propagated uncertainty in derived CDRs at full resolution and in gridded products. Errors in Earth observations are typically highly structured and complex, and the uncertainty information we propose is of intermediate complexity, sufficient to capture the main variability in propagated uncertainty in a CDR, while avoiding unfeasible complexity or data volume. The uncertainty and error correlation characteristics of uncertainty are quantified for three classes of error with different propagation properties: independent, structured and common radiance errors. The meaning, mathematical derivations, practical evaluation and example applications of this set of uncertainty information are presented.
Highlights
Climate data records (CDRs) are generated from Earth observations within several programmes [1,2,3,4] in support of societal and scientific needs to quantify change and variability in Earth’s climate system
The focus of this paper is to address the question, “What radiance uncertainty information should be provided to support the characterisation of uncertainty in derived CDRs?” The proposed approach is intended to support propagation of uncertainty to levels 2 and 3, which means that inter-channel and spatio-temporal error correlations must be included
The High-Resolution Infrared Sounder (HIRS) is a 20-channel radiometer with a heritage dating to 1975 [33], and it has been used in numerical weather prediction and analysis, and for climate data records [34]
Summary
Climate data records (CDRs) are generated from Earth observations within several programmes [1,2,3,4] in support of societal and scientific needs to quantify change and variability in Earth’s climate system. A large proportion of level-1/FCDR datasets contain either no or very limited radiance uncertainty information, meaning that CDR creators have no practical means to evaluate propagated radiance uncertainty In part, this situation arises because it is not obvious what selection of radiance uncertainty information is needed to adequately support CDR creation, given that providing comprehensive uncertainty information would entail infeasible data volumes and/or complexity (see below). From these steps, we infer the uncertainty information that should be provided at level 1 in an FCDR. Remote Sens. 2019, 11, 474 summational remarks regarding the assumptions and implications of the ideas presented, as well as some closing discussion
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