What is a CDR?
A Climate Data Record (CDR) consists of a long, stabilised record of uncertainty-quantified retrieved values of a geophysical variable relevant to Earth’s climate, together with all ancillary data used in retrieval and uncertainty estimation. The CDR is linked to (an) underlying fundamental climate data record(s).
What is the challenge
The definition above stresses the need to quantify uncertainty in a CDR, and link to underlying data to ensure traceability of origin. From a metrological perspective, uncertainty estimates in a CDR should be rigorous and traceable. Uncertainty from the FCDR should be propagated through the L2 measurement function, and the uncertainty introduced in transforming from L1 to L2 should be estimated. To be valuable, the CDR must be of sufficient duration, quality and stability to be useful for understanding climate variability and change: providing traceable uncertainty information helps establish that this is the case.
How can FIDUCEO help?
In FIDUCEO a systematic method for presenting error covariance information for the FCDR was developed so that it can be used in a CDR. Similarly, a systematic method for presenting CDR-level uncertainty information was developed. The CDR uncertainty analysis can be broken down into the following steps:
STEP 1: Establishing the processing chain. This shows the direct processing from the FCDR to the CDR and the origin of auxiliary information brought into the CDR processing. This chain will include both the main retrieval and any steps to prepare the data for that retrieval, for example through cloud masking or pixel selection. It may involve both forward steps and look-up-table based inverse retrievals. This processing chain is presented diagrammatically and any sources of uncertainty introduced by these steps are considered.
STEP 2: Defining uncertainties effects. For the main retrieval process, we establish the measurement function that is used to calculate the retrieved CDR from the input quantities. We note that it may be possible to write this equation explicitly as an algebraic expression, or it may only be possible to represent it conceptually as the processing is performed through iterative or look-up-table-based software processes. As with the FCDR, the main uncertainty analysis is performed through considering all input quantities to this measurement function and the sources of uncertainty that influence each input quantity. As with the FCDR this can be presented diagrammatically using and uncertainty tree diagram.
STEP 3: Determining uncertainties. Uncertainty is established for each CDR pixel and/or regridded “superpixel”. This uncertainty propagates the error correlation structure of the FCDR to the extent that it affects the CDR; i.e. if the CDR value combines data from different spectral channels, then the channel-to-channel error correlation is included in the analysis. If a regridding to a “superpixel” is performed during the CDR propagation, then the pixel-to-pixel error covariance in considered in that uncertainty analysis. However, the only information currently provided on how to propagate uncertainty from the CDR to later processing steps is qualitative with, perhaps, indicative scales.
STEP 4: Completing the effects table. For each source of uncertainty, an effects table is produced. The CDR effects table is similar to the FCDR effects table, but allows for different error correlation structures.
STEP 5: Generating a CDR. The CDR production involves more complex processes than the FCDR production, and often less is known quantitatively about these processes. For this reason, uncertainty analysis for the CDR has to rely more frequently on “expert judgement” and assumptions. Therefore within the CDR effects tables some qualitative categorisation is included, suggesting the extent to which the uncertainties provided are evaluated or estimated.
For similar reasons, the CDR documents also provide tables of sources of uncertainty that are known to exist, but which have not been studied in detail. Here too, a qualitative estimate is provided on how significant such effects are expected to be.
- D2-4a: Principles and concepts (http://fiduceo.pbworks.com/w/file/133584030/D2-4a%20Principles%20of%20CDR%20uncertainty%20analysis.docx)
- D2-4 Template: A template for writing a D2-4 (http://fiduceo.pbworks.com/w/file/124079772/Template%20for%20FIDUCEO%20CDR%20Reports.docx)
- D2-4 Guidance: Notes to support the template (http://fiduceo.pbworks.com/w/file/128810154/Guidance%20for%20FIDUCEO%20CDR%20Reports.docx)
- D2-4 examples – for all our CDRs