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A Practical Introduction to Utilising Uncertainty Information in the Analysis of Essential Climate Variables

Surveys in Geophysics Springer Science and Business Media LLC (2025)

Authors:

Adam C Povey, Claire E Bulgin, Alexander Gruber

Abstract:

Abstract An estimate of uncertainty is essential to understanding what information is conveyed by data and how it relates to the wider context of what one intended to measure. It can be difficult to know how to use uncertainty during the analysis of environmental data and the best way to present that information within a dataset. In many common uses, such as calculating statistical significance, it is easy to make mistakes due to incomplete or inappropriate use of the available uncertainty information. Uncertainty is itself uncertain, such that many practical or empirical solutions are available when a comprehensive uncertainty budget is impractical to produce. This manuscript collects actionable guidance on how uncertainty can be used, presented, and calculated when working with essential climate variables (ECVs). This includes qualitative discussions of the utility of uncertainties, explanations of common misconceptions, advice on presentation style, and plain descriptions of the essential equations. Selected worked examples are included on the propagation of uncertainties, particularly for data aggregation and merging. Uncertainty need not be off-putting as even incomplete uncertainty budgets add value to any observation. This paper aims to provide a starting point, or refresher, for researchers in the environmental sciences to make more complete use of uncertainty in their work.
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Raikoke volcanic sulfate/SO2 anticyclonic contained circulations: in situ proof, morphology, and radiative signature

Journal of Geophysical Research: Atmospheres Wiley 130:17 (2025) e2024JD041653

Authors:

Md Fromm, Gp Kablick, Ia Taylor, Rg Grainger, C Seftor, Ej Welton, J Fochesatto

Abstract:

300–400 km in diameter. Previous reports showed that one of these entities was traceable for 3 months. Anticyclonic circulation was also previously reported. We present multiple lines of evidence to characterize these cloud subelements by their spatial confinement, morphology, and sulfate-dominated aerosol aspect, which was evident from plume onset. In addition, we show that they were ably identifiable in geostationary satellite “cirrus channel” reflectance imagery and had an enduring signal of window infrared absorption, detectable for at least 1 month. The term we apply to this phenomenon is “sulfate/SO2 anticyclonic contained circulation,” abbreviated SSACC. Anticyclonic circulation is first detectable on 24 June, 2 days posteruption. Two SSACCs persist beyond June. One is traceable until mid-August over Canada. The other SSACC was discernible until 5 October after having completed three global circumnavigations. The internal SSACC circulation aspect is gleaned from geostationary-based visible image animations and confirmed in situ via a novel application of high-resolution radiosonde wind direction and balloon position data. We also examine diabatic lofting of both SSACCs in relation to their individual geographic and constituent morphologies. Thermal infrared observations show that SSACC aerosols produce brightness temperature depressions of ~2.6 K, opening a new line of investigation into the source of heating that contributes to diabatic rise.

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The Challenges and Limitations of Validating Satellite-Derived Datasets Using Independent Measurements: Lessons Learned from Essential Climate Variables

Surveys in Geophysics Springer Science and Business Media LLC (2025)

Authors:

Mary Langsdale, Tijl Verhoelst, Adam Povey, Nick Schutgens, Thomas Dowling, Jean-Christopher Lambert, Steven Compernolle, Stefan Kern

Abstract:

Abstract Validation of satellite-derived essential climate variable (ECV) datasets requires comparison against independent measurements. These independent measurements, which include ground-based, airborne, and other non-satellite-based measurements, are typically the product of a different measurement system and may include some contribution from models. These reference data therefore have their own characteristics, uncertainties, and limitations which must be accounted for in the validation process. In addition, they typically differ from the data to be validated in spatio-temporal resolution, sensitivity, and sampling. As such, comparisons to independent data do not necessarily yield clear feedback on the quality of satellite data and insufficient awareness of these issues can lead to erroneous interpretation. This is the cost of leaving the laboratory and studying the real world. In this review paper, we examine the challenges and limitations of evaluating satellite-derived datasets with independent measurements, using examples across different ECVs within the terrestrial, ocean, and atmospheric domains. Drawing from other studies, we discuss issues with the reference datasets themselves, issues specific to use of these data for validation, and issues resulting from the comparison methodology. We conclude with recommendations to the community based on this review. In this, we highlight the importance of continued efforts towards (1) advancing uncertainty modelling of reference datasets and quality control knowledge and procedures, (2) establishing and communicating limitations in reference data, (3) reference data (and metadata) timeliness and preservation, and (4) best practices for the validation methodologies that address the spatio-temporal differences of the measurements.
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Making Sense of Uncertainties: Ask the Right Question

Surveys in Geophysics Springer Science and Business Media LLC (2025)

Authors:

Alexander Gruber, Claire E Bulgin, Wouter Dorigo, Owen Embury, Maud Formanek, Christopher Merchant, Jonathan Mittaz, Joaquín Muñoz-Sabater, Florian Pöppl, Adam Povey, Wolfgang Wagner

Abstract:

Abstract Earth observation data should inform decision making, but good decisions can only be made if the uncertainties in the data are taken into account. Making sense of uncertainty information can be difficult, because uncertainties represent the statistical spread in the observations (e.g., expressed as $$x \pm y$$ x ± y ), which does not relate directly to one specific use case of the data. Here, we propose a Bayesian framework to transform Earth observation product uncertainties into actionable information, i.e., estimates of how confident one can be in the occurrence of specific events of interest given the data and their uncertainty. We demonstrate this framework using two case examples: (i) monitoring drought severity based on soil moisture and (ii) estimating coral bleaching risk based on sea surface temperature. In both cases, we show that ignoring uncertainties can easily lead to misinterpretation of the data, making any decisions based on these data unlikely to be the best course of action. The proposed framework is general and can, in principle, be applied to a wide range of applications. Doing so requires a careful dialogue between data users, to formulate meaningful use cases and decision criteria, and data producers, to provide a rigorous description of their data and its uncertainties. The next step would then be to confront the uncertainty-informed estimates of event probabilities (created by the framework proposed here) with the costs and benefits of possible courses of action in order to make the best possible decisions that maximize socioeconomic merit.
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A Unified Framework for Trend Uncertainty Assessment in Climate Data Record: Application to the Analysis of the Global Mean Sea Level Measured by Satellite Altimetry

Copernicus Publications (2025)

Authors:

Kevin Gobron, Roland Hohensinn, Claire E Bulgin, Xavier Loizeau, Emma R Woolliams, Christopher J Merchant, Jon Mittaz, Adam C Povey, Mary Langsdale, Wouter Dorigo, Maurice G Cox, Michael Ablain, Anna Klos, Alexander Gruber, Janusz Bogusz
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