Earth Observation Data Group

Abstract:

It is well known that scientific data have uncertainties and that it is crucial to take these uncertainties into account in any decision making process. Nevertheless, despite data producer’s best efforts to provide complete and rigorous uncertainty estimates alongside their data, users commonly struggle to make sense of uncertainty information. This is because uncertainties are usually expressed as the statistical spread in the observations (for example, as random error standard deviation), which does not relate to the intended use of the data.Put simply, data and their uncertainty are usually expressed as something like “x plus/minus y”, which does not answer the really important question: How much can I trust “x”, or any use of or decision based upon “x”? Consequently, uncertainties are often either ignored altogether and the data taken at face value, or interpreted by experts (or non-experts) heuristically to arrive at rather subjective, qualitative judgements of the confidence they can have in the data.In line with existing practices (e.g., the communication of uncertianties in the IPCC reports), we conjecture that the key to enabling users to make sense of uncertainties is to represent them as the confidence one can have in whatever event one is interested in, given the available data and their uncertainty.To that end, we propose a novel, generic framework that transforms common uncertaintiy representations (i.e., estimates of stochastic data properties, such as “the state of this variable is “x plus/minus y”) into more meaningful, actionable information that actually relate to their intended use, (i.e., statements such as “the data and their uncertainties suggest that we can be “z” % confident that…”). This is done by first formulating a meaningful question that links the available data to some events of interest, and then deriving quantiative estimates for the confidence in the occurrence of these events using Bayes theorem.We demonstrate this framework using two case examples: (i) using satellte soil moisture retrievals and their uncertainty to derive how confident one can be in the presence and severity of a drought; and (ii) how ocean temperature analyses and their uncertainty can be used to determine how confident one can be that prevailing conditions are likely to cause coral bleaching. 

Abstract:

The eruption of Hunga volcano on 15 January 2022 was an exceptional event in the satellite era. Record-breaking heights of the volcanic plume were reported, a large amount of water was injected into the stratosphere and a broad spectrum of atmospheric waves were detected. Here, we use satellite measurements to show that a transient ring of small ice particles (~2 μm) formed around the plume. We hypothesize that the ice ring was generated by the passage of an atmospheric wave triggered by a pressure pulse at the surface corresponding to a violent explosion that occurred during the 15 January 2022 eruption sequence. The passage of the atmospheric wave produced a transient rarefaction in the upper troposphere-lower stratosphere, which in turn led to oscillations in ambient temperature. Due to the supersaturated state of the atmosphere with respect to ice, ice particles formed in the wake of the radially propagating atmospheric wave, allowing an exceptional opportunity to study ice particle growth via vapour deposition. This atmospheric phenomenon serves as an important natural experiment that reveals the time scale on which ice particles nucleate and grow given an abrupt perturbation in ambient temperature.

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.

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.