Weekly to multi-month persistence in sets of daily weather patterns over Europe and the North Atlantic Ocean

© 2018 Royal Meteorological Society Persistence in time series of daily weather pattern (WP) classifications can provide useful information such as on the memory of broad-scale atmospheric circulation. Despite this, research of WP persistence has lagged behind that exploring their frequencies of occ...

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Main Authors: Richardson D, Kilsby CG, Fowler HJ, Bardossy A
Format: Article in Journal/Newspaper
Language:unknown
Published: John Wiley and Sons Ltd 2018
Subjects:
Online Access:https://eprint.ncl.ac.uk/fulltext.aspx?url=253844/BA0435FE-E2BB-44C6-A8AD-21A83748A176.pdf&pub_id=253844
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spelling ftunivnewcastle:oai:eprint.ncl.ac.uk:253844 2023-05-15T17:32:00+02:00 Weekly to multi-month persistence in sets of daily weather patterns over Europe and the North Atlantic Ocean Richardson D Kilsby CG Fowler HJ Bardossy A 2018 application/pdf https://eprint.ncl.ac.uk/fulltext.aspx?url=253844/BA0435FE-E2BB-44C6-A8AD-21A83748A176.pdf&pub_id=253844 unknown John Wiley and Sons Ltd International Journal of Climatology, 2018 Article 2018 ftunivnewcastle 2020-06-11T23:45:07Z © 2018 Royal Meteorological Society Persistence in time series of daily weather pattern (WP) classifications can provide useful information such as on the memory of broad-scale atmospheric circulation. Despite this, research of WP persistence has lagged behind that exploring their frequencies of occurrence. We develop two methods for identifying persistence in a 167-year time series of WPs defined over the North Atlantic–European domain. The first is an empirical counting technique used to find periods of persistence among sets of WPs, with the definition of persistence more relaxed than just consecutive occurrences. We then condition this method on the driest WPs to see if persistence can be used to identify historical drought. The second method uses a Markov model to assess if WP transition probabilities change when conditioned on information up to 20 days prior, without the need for estimating the large number of parameters usually required for high-order Markov chains. Results are compared with a benchmark ensemble of synthetic time series generated using first-order transition probabilities. We show that there were multi-month periods when small sets of WPs dominated, and some of these periods coincided with notable meteorological events, including droughts and storms, such as the mid-1990s drought in northern England and the Burn's Day Storm over southern Scotland in 1990. Some WPs also behave as “attractors,” showing increased probability of reoccurrence despite other WPs occurring in-between. However, we find no link between the persistence statistics of each WP and their flow characteristics, except for those featuring an easterly flow over the United Kingdom, which are among the most persistent. The benchmark simulation ensemble is unable to reproduce many of the key persistence statistics of the observations, confirming that the persistence is a physical phenomenon. Finally, we discuss the potential processes underpinning WP persistence, such as the effects of large-scale circulation patterns and land-surface feedbacks. Article in Journal/Newspaper North Atlantic Newcastle University Library ePrints Service
institution Open Polar
collection Newcastle University Library ePrints Service
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description © 2018 Royal Meteorological Society Persistence in time series of daily weather pattern (WP) classifications can provide useful information such as on the memory of broad-scale atmospheric circulation. Despite this, research of WP persistence has lagged behind that exploring their frequencies of occurrence. We develop two methods for identifying persistence in a 167-year time series of WPs defined over the North Atlantic–European domain. The first is an empirical counting technique used to find periods of persistence among sets of WPs, with the definition of persistence more relaxed than just consecutive occurrences. We then condition this method on the driest WPs to see if persistence can be used to identify historical drought. The second method uses a Markov model to assess if WP transition probabilities change when conditioned on information up to 20 days prior, without the need for estimating the large number of parameters usually required for high-order Markov chains. Results are compared with a benchmark ensemble of synthetic time series generated using first-order transition probabilities. We show that there were multi-month periods when small sets of WPs dominated, and some of these periods coincided with notable meteorological events, including droughts and storms, such as the mid-1990s drought in northern England and the Burn's Day Storm over southern Scotland in 1990. Some WPs also behave as “attractors,” showing increased probability of reoccurrence despite other WPs occurring in-between. However, we find no link between the persistence statistics of each WP and their flow characteristics, except for those featuring an easterly flow over the United Kingdom, which are among the most persistent. The benchmark simulation ensemble is unable to reproduce many of the key persistence statistics of the observations, confirming that the persistence is a physical phenomenon. Finally, we discuss the potential processes underpinning WP persistence, such as the effects of large-scale circulation patterns and land-surface feedbacks.
format Article in Journal/Newspaper
author Richardson D
Kilsby CG
Fowler HJ
Bardossy A
spellingShingle Richardson D
Kilsby CG
Fowler HJ
Bardossy A
Weekly to multi-month persistence in sets of daily weather patterns over Europe and the North Atlantic Ocean
author_facet Richardson D
Kilsby CG
Fowler HJ
Bardossy A
author_sort Richardson D
title Weekly to multi-month persistence in sets of daily weather patterns over Europe and the North Atlantic Ocean
title_short Weekly to multi-month persistence in sets of daily weather patterns over Europe and the North Atlantic Ocean
title_full Weekly to multi-month persistence in sets of daily weather patterns over Europe and the North Atlantic Ocean
title_fullStr Weekly to multi-month persistence in sets of daily weather patterns over Europe and the North Atlantic Ocean
title_full_unstemmed Weekly to multi-month persistence in sets of daily weather patterns over Europe and the North Atlantic Ocean
title_sort weekly to multi-month persistence in sets of daily weather patterns over europe and the north atlantic ocean
publisher John Wiley and Sons Ltd
publishDate 2018
url https://eprint.ncl.ac.uk/fulltext.aspx?url=253844/BA0435FE-E2BB-44C6-A8AD-21A83748A176.pdf&pub_id=253844
genre North Atlantic
genre_facet North Atlantic
op_source International Journal of Climatology, 2018
_version_ 1766129917073817600