Results on a common grid
Objective
Deliver results on a common map grid on which every measurement keeps its meaning, its uncertainty and the record of what shaped it.
Observed in real data Current focus See the results How stages are defined
Checking that a delivered result's uncertainty is carried through correctly, not only present.
Resampling and aggregation are where uncertainty is most often lost. An error shared by many pixels does not average away, and a regular grid can suggest spatial detail the observations never contained.
A tidy map can suggest more certainty than the measurements behind it. Anyone combining map cells into areas, time series or indicators needs the shared uncertainty to travel with them.
We trace measurements and their shared uncertainties through every step to the delivered map, following established methods for propagating uncertainty through measurement models, and check that it is carried correctly wherever values are combined.
The uncertainty of every delivered map cell accounts for errors shared across pixels, and no cell implies detail the observations do not contain.
Each result is dated and published on its own page with its data, conditions and limits. Results that went against the objective are listed here with the rest.
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Band-specific confidence carried onto a common grid
RefCal has carried band-specific confidence and spatial state into real common-grid outputs end to end. That earns an observed-in-real-data stage. It does not yet show that the propagated covariance is scientifically faithful or that the resulting uncertainty has passed independent validation.
Full result, data and credits ->
Established work this area builds on. Results from the programme are published separately, with their data and limits.
- Evaluation of measurement data: Supplement 2 to the GUM, extension to any number of output quantities (JCGM 102:2011) Joint Committee for Guides in Metrology, BIPM How uncertainty, including shared uncertainty, carries through to combined results.
- Determining uncertainties FIDUCEO project, University of Reading Why shared calibration errors behave differently from independent noise.
Questions about this work?
If you work on this problem, or hold reference data that bears on it, contact us.