A composite-based analysis of the dynamical linkage of atmospheric rivers, warm conveyor belts, and extratropical cyclones

Abstract. Extratropical cyclones (ETCs), warm conveyor belts (WCBs), and atmospheric rivers (ARs) are dynamically connected features key to understand midlatitude weather and hydroclimate. However, the precise spatial and temporal coupling between the moisture transport in ARs and the ascent in ETC’s associated WCBs remains poorly understood. Therefore, this study employs a composite-based analysis, combining probabilistic footprints of WCB identification and Eulerian AR detection for the North Atlantic extended winter (October–March) using ERA5 reanalysis. We evaluate composite fields relative to AR centroids, differentiating between events where the WCB ascent phase is present within the AR plume from those where it is absent. Our results demonstrate that ARs linked to WCBs are characterized by stronger integrated vapor transport, a wider AR plume, and, most critically, a shift of precipitation maxima northeast of the AR axis, aligning with the region of strongest frontal ascent near the associated ETC. In contrast, AR-only events exhibit weaker IVT values and a diffuse precipitation to the northeast towards the cyclone. Finally, temporal composites centered on the ETC's maximum deepening point (MDP) reveal a phased evolution: while peak WCB-inflow precedes the MDP, peak WCB-ascent and AR-related precipitation coincide with the MDP, and peak WCB-outflow follows, illustrating a tightly coupled feedback loop.

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Publication Details

Journal
Weather and Climate Dynamics
Published
2026-10-14
DOI
https://doi.org/10.5194/wcd-7-2043-2026
Primary Topic
Meteorological Phenomena and Simulations
Type
article
Field-Weighted Citation Impact
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article

A composite-based analysis of the dynamical linkage of atmospheric rivers, warm conveyor belts, and extratropical cyclones

Ricardo Machado Trigo, Joaquim Ginete Pinto, Tiago M. Ferreira, Julian Quinting et al.
Weather and Climate Dynamics
Meteorological Phenomena and Simulations
article

A composite-based analysis of the dynamical linkage of atmospheric rivers, warm conveyor belts, and extratropical cyclones

Ricardo Machado Trigo, Joaquim Ginete Pinto, Tiago M. Ferreira, Julian Quinting, Alexandre Miguel Ramos, Svenja Christ
article en

Abstract

Abstract. Extratropical cyclones (ETCs), warm conveyor belts (WCBs), and atmospheric rivers (ARs) are dynamically connected features key to understand midlatitude weather and hydroclimate. However, the precise spatial and temporal coupling between the moisture transport in ARs and the ascent in ETC’s associated WCBs remains poorly understood. Therefore, this study employs a composite-based analysis, combining probabilistic footprints of WCB identification and Eulerian AR detection for the North Atlantic extended winter (October–March) using ERA5 reanalysis. We evaluate composite fields relative to AR centroids, differentiating between events where the WCB ascent phase is present within the AR plume from those where it is absent. Our results demonstrate that ARs linked to WCBs are characterized by stronger integrated vapor transport, a wider AR plume, and, most critically, a shift of precipitation maxima northeast of the AR axis, aligning with the region of strongest frontal ascent near the associated ETC. In contrast, AR-only events exhibit weaker IVT values and a diffuse precipitation to the northeast towards the cyclone. Finally, temporal composites centered on the ETC's maximum deepening point (MDP) reveal a phased evolution: while peak WCB-inflow precedes the MDP, peak WCB-ascent and AR-related precipitation coincide with the MDP, and peak WCB-outflow follows, illustrating a tightly coupled feedback loop.

Weather and Climate DynamicsVol. 7(4)
Karlsruhe Institute of Technology (DE), University of Lisbon (PT), University of Cologne (DE), Instituto Dom Luiz
European Commission, AXA Research Fund, Ministério da Ciência, Tecnologia e Ensino Superior, Fundação para a Ciência e a Tecnologia
Climate action
Openalex Percentile: Top 73%
Meteorological Phenomena and Simulations
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