Arctic amplification metrics

One of the defining features of both recent and historical cases of global climate change is Arctic amplification (AA). This is the more rapid change in the surface air temperature (SAT) in the Arctic compared to some wider reference region, such as the Northern Hemisphere (NH) mean. Many different...

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Published in:International Journal of Climatology
Main Authors: Davy, Richard, Chen, Linling, Hanna, Edward
Other Authors: Horizon 2020 Framework Programme, Norges Forskningsråd
Format: Article in Journal/Newspaper
Language:English
Published: Wiley 2018
Subjects:
Online Access:http://dx.doi.org/10.1002/joc.5675
https://api.wiley.com/onlinelibrary/tdm/v1/articles/10.1002%2Fjoc.5675
https://rmets.onlinelibrary.wiley.com/doi/pdf/10.1002/joc.5675
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spelling crwiley:10.1002/joc.5675 2024-06-09T07:43:24+00:00 Arctic amplification metrics Davy, Richard Chen, Linling Hanna, Edward Horizon 2020 Framework Programme Norges Forskningsråd 2018 http://dx.doi.org/10.1002/joc.5675 https://api.wiley.com/onlinelibrary/tdm/v1/articles/10.1002%2Fjoc.5675 https://rmets.onlinelibrary.wiley.com/doi/pdf/10.1002/joc.5675 en eng Wiley http://onlinelibrary.wiley.com/termsAndConditions#vor International Journal of Climatology volume 38, issue 12, page 4384-4394 ISSN 0899-8418 1097-0088 journal-article 2018 crwiley https://doi.org/10.1002/joc.5675 2024-05-16T14:24:13Z One of the defining features of both recent and historical cases of global climate change is Arctic amplification (AA). This is the more rapid change in the surface air temperature (SAT) in the Arctic compared to some wider reference region, such as the Northern Hemisphere (NH) mean. Many different metrics have been developed to quantify the degree of AA based on SAT anomalies, trends and variability. The use of different metrics, as well as the choice of data set to use, can affect conclusions about the magnitude and temporal variability of AA. Here we review the established metrics of AA to see how well they agree upon the temporal signature of AA, such as the multi‐decadal variability, and assess the consistency in these metrics across different commonly used data sets which cover both the early and late 20th century warming in the Arctic. We find the NOAA 20th century reanalysis most closely matches the observations when using metrics based upon SAT trends ( A 2 ), variability ( A 3 ) and regression ( A 4 ) of the SAT anomalies, and the ERA 20th century reanalysis is closest to the observations in the SAT anomalies ( A 1 ) and variability of SAT anomalies ( A 3 ). However, there are large seasonal differences in the consistency between data sets. Moreover, the largest differences between the century‐long reanalysis products and observations are during the early warming period, likely due to the sparseness of the observations in the Arctic at that time. In the modern warming period, the high density of observations strongly constrains all the reanalysis products, whether they include satellite observations or only surface observations. Thus, all the reanalysis and observation products produce very similar magnitudes and temporal variability in the degree of AA during the recent warming period. Article in Journal/Newspaper Arctic Climate change Wiley Online Library Arctic International Journal of Climatology 38 12 4384 4394
institution Open Polar
collection Wiley Online Library
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description One of the defining features of both recent and historical cases of global climate change is Arctic amplification (AA). This is the more rapid change in the surface air temperature (SAT) in the Arctic compared to some wider reference region, such as the Northern Hemisphere (NH) mean. Many different metrics have been developed to quantify the degree of AA based on SAT anomalies, trends and variability. The use of different metrics, as well as the choice of data set to use, can affect conclusions about the magnitude and temporal variability of AA. Here we review the established metrics of AA to see how well they agree upon the temporal signature of AA, such as the multi‐decadal variability, and assess the consistency in these metrics across different commonly used data sets which cover both the early and late 20th century warming in the Arctic. We find the NOAA 20th century reanalysis most closely matches the observations when using metrics based upon SAT trends ( A 2 ), variability ( A 3 ) and regression ( A 4 ) of the SAT anomalies, and the ERA 20th century reanalysis is closest to the observations in the SAT anomalies ( A 1 ) and variability of SAT anomalies ( A 3 ). However, there are large seasonal differences in the consistency between data sets. Moreover, the largest differences between the century‐long reanalysis products and observations are during the early warming period, likely due to the sparseness of the observations in the Arctic at that time. In the modern warming period, the high density of observations strongly constrains all the reanalysis products, whether they include satellite observations or only surface observations. Thus, all the reanalysis and observation products produce very similar magnitudes and temporal variability in the degree of AA during the recent warming period.
author2 Horizon 2020 Framework Programme
Norges Forskningsråd
format Article in Journal/Newspaper
author Davy, Richard
Chen, Linling
Hanna, Edward
spellingShingle Davy, Richard
Chen, Linling
Hanna, Edward
Arctic amplification metrics
author_facet Davy, Richard
Chen, Linling
Hanna, Edward
author_sort Davy, Richard
title Arctic amplification metrics
title_short Arctic amplification metrics
title_full Arctic amplification metrics
title_fullStr Arctic amplification metrics
title_full_unstemmed Arctic amplification metrics
title_sort arctic amplification metrics
publisher Wiley
publishDate 2018
url http://dx.doi.org/10.1002/joc.5675
https://api.wiley.com/onlinelibrary/tdm/v1/articles/10.1002%2Fjoc.5675
https://rmets.onlinelibrary.wiley.com/doi/pdf/10.1002/joc.5675
geographic Arctic
geographic_facet Arctic
genre Arctic
Climate change
genre_facet Arctic
Climate change
op_source International Journal of Climatology
volume 38, issue 12, page 4384-4394
ISSN 0899-8418 1097-0088
op_rights http://onlinelibrary.wiley.com/termsAndConditions#vor
op_doi https://doi.org/10.1002/joc.5675
container_title International Journal of Climatology
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