The winter North Atlantic Oscillation downstream teleconnection: insights from large-ensemble climate model simulations

Environmental Research Letters IOP Publishing 20:8 (2025) 084005

Authors:

Sing Lau, Kunhui Ye, Tim Woollings

Abstract:

The winter North Atlantic Oscillation (NAO) is the dominant pattern of atmospheric circulation variability over the North Atlantic region. It influences climate and weather such as surface air temperatures downstream over Eurasia through establishing a large-scale teleconnection, but past studies on the NAO’s downstream teleconnection have been largely limited to observational data, and further evidence of downstream impacts and associated mechanisms from comprehensive climate modeling is desirable. This study quantifies and analyzes this teleconnection on an interannual timescale by using both ERA5 reanalysis, and five large ensembles from four climate simulation models. A particular focus is placed on dynamical pathways, as well as variability among ensemble members that modulates the teleconnection strength. Results suggest that NAO signals are propagated downstream by Rossby waves, efficiently transmitted through waveguides along both the polar and subtropical jet streams to Eastern Eurasia; while heat can be advected weakly from upstream, advection plays a rather local effect inducing temperature anomalies from the Pacific Ocean onshore. Multiple linear regression shows that internal climate variability significantly modulates the teleconnection: a more locally dominant NAO pattern, and narrower waveguides could strengthen the teleconnection. These two factors combine to explain up to 70% of variance in the teleconnection strength, with each contributing almost equally. Reanalysis data marginally agree with the regression model (1.9 standardized residuals higher in strength), suggesting potential model biases in jets and the NAO variability. Monitoring these modulating factors would be crucial to understanding downstream climate predictability and improving climate prediction models linked to the NAO.

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.

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

The Mass Extinction Coefficient for Dust: challenges in the link between mass and optical properties for models, reanalyses, in-situ and satellite observations

(2025)

Authors:

Claire Ryder, Natalie Ratcliffe, Alcide Zhao, Nicolas Bellouin, Laura Wilcox, Helen Dacre, Clément Bézier, Vassilis Amiridis, Eleni Marinou, Emmanouil Proestakis, Bernadett Weinzierl, Stephanie Woodward, Ben Johnson, Anthony Jones

Abstract:

The latest range of CMIP6 model dust simulations shows a greater diversity than previous generations of models in terms of dust emission, deposition, burden and dust optical depth (DOD) (Zhao et al., 2022). Validation of dust models is crucial for understanding the impact of dust on climate and climate change, as well as for quantifying socio-economic and health impacts of dust.While models (and reanalyses) mostly provide output in terms of mass, satellite observations used for model validation are optical measurements. Thus we require good knowledge of the dust mass extinction coefficient (MEC) to successfully validate our dust models. However, the MEC is intricately linked to the dust size distribution, fraction of coarse particles and composition, all of which may vary regionally, in the vertical and in time.This presentation will provide a perspective on some recent efforts exploring the challenges in model validation relating to dust size, composition, optical depth and dust mass loading in climate models (Zhao et al., 2024; Ratcliffe et al., 2024), reanalyses (Ryder et al., 2024), space-borne lidar, space-borne optical depth and in-situ measurements, demonstrating the critical importance and uncertainty of the dust MEC.ReferencesRatcliffe, N.G., Ryder, C.L., Bellouin, N., Woodward, S., Jones, A., Johnson, B., Wieland, L.-M., Dollner, M., Gasteiger, J., Weinzierl, B. Long range transport of coarse mineral dust: an evaluation of the Met Office Unified Model against aircraft observations, Atmos. Chem. Phys., 24, 12161–12181, https://doi.org/10.5194/acp-24-12161-2024, 2024.Ryder, C.L., Bézier, C., Dacre, H., Clarkson, R., Amiridis, V., Marinou, E., Proestakis, E., Kipling, Z., Benedetti, A., Parrington, M., Rémy, S., Vaughan, M., Aircraft Engine Dust Ingestion at Global Airports, https://doi.org/10.5194/nhess-24-2263-2024, 24, 7, Natural Hazards and Earth System Science, 2024.Zhao, A., Ryder, C.L., Wilcox, L., How well do the CMIP6 models simulate dust aerosols?, Atmos. Chem. Phys., 22, 2095–2119, https://doi.org/10.5194/acp-22-2095-2022, 2022.Zhao, A., Wilcox, L., Ryder, C.L., The key role of atmospheric absorption in the Asian Summer Monsoon response to dust emissions in CMIP6 models, Atmos. Chem. Phys., https://doi.org/10.5194/acp-24-13385-2024, 2024.

Making sense of uncertainties: Ask the right question

Copernicus Publications (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