White, Rachel H.; Kornhuber, Kai; Martius, Olivia; Wirth, Volkmar (2021). From Atmospheric Waves to Heatwaves: A Waveguide Perspective for Understanding and Predicting Concurrent, Persistent and Extreme Extratropical Weather. Bulletin of the American Meteorological Society, 103(3), E923-E935. American Meteorological Society 10.1175/BAMS-D-21-0170.1
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From_Atmospheric_Waves_to_Heatwaves_A_Waveguide_Perspective_for_Understanding_and_Predicting_Concurrent__Persistent_and_Extreme.pdf - Accepted Version Restricted to registered users only Available under License Publisher holds Copyright. Download (1MB) |
A notable number of high impact weather extremes have occurred in recent years, often associated with persistent, strongly meandering atmospheric circulation patterns known as Rossby waves. Because of the high societal and ecosystem impacts, it is of great interest to be able to accurately project how such extreme events will change with climate change, and to predict these events on seasonal to subseasonal (S2S) timescales. There are multiple physical links connecting upper atmosphere circulation patterns to surface weather extremes, and it is asking a lot of our dynamical models to accurately simulate all of these. Subsequently, our confidence in future projections and S2S forecasts of extreme events connected to Rossby waves remains relatively low. We also lack full fundamental theories for the growth and propagation of Rossby waves on the spatial and temporal scales relevant to extreme events, particularly under strongly non-linear conditions. By focussing on one of the first links in the chain from upper atmospheric conditions to surface extremes -- the Rossby waveguide -- it may be possible to circumvent some model biases in later links. To further our understanding of the nature of waveguides, links to persistent surface weather events and their representation in models, we recommend: exploring these links in model hierarchies of increasing complexity, developing fundamental theory, exploiting novel large ensemble data sets, harnessing deep learning, and increased community collaboration. This would help increase understanding and confidence in both S2S predictions of extremes and of projections of the impact of climate change on extreme weather events.
Item Type: |
Journal Article (Original Article) |
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Division/Institute: |
08 Faculty of Science > Institute of Geography > Physical Geography > Unit Impact 10 Strategic Research Centers > Oeschger Centre for Climate Change Research (OCCR) 08 Faculty of Science > Institute of Geography 08 Faculty of Science > Institute of Geography > Physical Geography 10 Strategic Research Centers > Oeschger Centre for Climate Change Research (OCCR) > MobiLab |
UniBE Contributor: |
Romppainen-Martius, Olivia |
Subjects: |
900 History > 910 Geography & travel |
ISSN: |
0003-0007 |
Publisher: |
American Meteorological Society |
Funders: |
[42] Schweizerischer Nationalfonds |
Language: |
English |
Submitter: |
Yannick Barton |
Date Deposited: |
24 Feb 2022 16:09 |
Last Modified: |
05 Dec 2022 16:07 |
Publisher DOI: |
10.1175/BAMS-D-21-0170.1 |
BORIS DOI: |
10.48350/165204 |
URI: |
https://boris.unibe.ch/id/eprint/165204 |