Introduction to uncertainties
Image credit: UnsplashNavigating the world of uncertainties can be quite tricky, as often terms such as errors and uncertainties are used interchangeably, even though they do not describe the same thing.
In this brief introduction to uncertainties and their propagation, we will highlight the most important concepts and signpost you to useful resources.
By providing learning materials covering relevant topics at varying levels of depth, we want to ensure that you can fully understand and therefore implement the capabilities of this toolkit.
❔ Why do we care about uncertainties?
Uncertainties are a vital aspect of the measurement science, as they provide credibility and trust in measured data.
To ensure that everyone is on the same page, a great place to start is this Measurement Good Practice Guide put together by the National Physical Labpratory (NPL).
It covers all the relevant terminology, best practises, and examples for understanding the uncertainty of measurements.
As mentioned at the beginning of this article, we can confirm that uncertainties and errors are, in fact, not the same thing:
Uncertainty is a quantification of the doubt about the measurement result.
Error is the difference between the measured value and the “true value” of the thing being measured.
📜 Metrology & the Guide to Uncertainties in Measurements
Metrology, the science of measurement, is the discipline that maintains the SI and the associated system of measurement, ensuring measurements are stable over time and measurement standards equivalent worldwide. These properties are supported by the principles of metrological traceability: uncertainty analysis and comparison.
The Guide to the expression of Uncertainty in Measurement or GUM for short, is the ultimate resource to refer to, when you are evaluating measurement uncertainties.
All the official documentation of GUM as well as a guide to the International Vocabulary of Metrology (VIM) are available here.
🏆 Best practice framework for EO
To ensure credible and reliable interpretation of environmental observations from satellites and in-situ measurements, Committee on Earth Observation Satellites (CEOS) has established and endorced the Quality Assurance framework for Earth Observation (QA4EO).
This framework requires that associated uncertainty information is provided for all measurements. Additionally, it highlights the importance of understanding the error-covariances in the data.
Approaches defined within QA4EO enable the EO community to develop quantitative characterisation of uncertainty in EO data.
QA4EO developed a 5-steps approach to do an uncertainty budget. These 5 steps are described on this CoMet page and in the QA4EO process document.
However, practically implementing these methods is not trivial and can be time consuming.
As a way to facilitate this, the CoMet Toolkit was developed as a means to store and propagate uncertainty and error-correlation information.
✔️Other useful resources for Uncertainty in Earth Observations (EO)
A great resource that describes all the various aspects of uncertainty propagation for satellite EO data is FIDUCEO.
This project provides a comprehensive guide to understanding and implementing:
