Irreducible uncertainty in near-term climate projections
Model simulations of the next few decades are widely used in assessments of climate change impacts and as guidance for adaptation. Their non-linear nature reveals a level of irreducible uncertainty which it is important to understand and quantify, especially for projections of near-term regional cli...
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ftunivreading:oai:centaur.reading.ac.uk:48782 2024-05-12T08:08:19+00:00 Irreducible uncertainty in near-term climate projections Hawkins, Ed Smith, Robin S. Gregory, Jonathan M. Stainforth, David A. 2016-06 text https://centaur.reading.ac.uk/48782/ https://centaur.reading.ac.uk/48782/1/art%253A10.1007%252Fs00382-015-2806-8.pdf https://doi.org/10.1007/s00382-015-2806-8 en eng Springer https://centaur.reading.ac.uk/48782/1/art%253A10.1007%252Fs00382-015-2806-8.pdf Hawkins, E. <https://centaur.reading.ac.uk/view/creators/90000949.html> orcid:0000-0001-9477-3677 , Smith, R. S. <https://centaur.reading.ac.uk/view/creators/90000556.html> orcid:0000-0001-7479-7778 , Gregory, J. M. <https://centaur.reading.ac.uk/view/creators/90000874.html> and Stainforth, D. A. (2016) Irreducible uncertainty in near-term climate projections. Climate Dynamics, 46 (11). pp. 3807-3819. ISSN 1432-0894 doi: https://doi.org/10.1007/s00382-015-2806-8 <https://doi.org/10.1007/s00382-015-2806-8> cc_by_4 Article PeerReviewed 2016 ftunivreading https://doi.org/10.1007/s00382-015-2806-8 2024-04-17T14:48:30Z Model simulations of the next few decades are widely used in assessments of climate change impacts and as guidance for adaptation. Their non-linear nature reveals a level of irreducible uncertainty which it is important to understand and quantify, especially for projections of near-term regional climate. Here we use large idealised initial condition ensembles of the FAMOUS global climate model with a 1 %/year compound increase in CO2 levels to quantify the range of future temperatures in model-based projections. These simulations explore the role of both atmospheric and oceanic initial conditions and are the largest such ensembles to date. Short-term simulated trends in global temperature are diverse, and cooling periods are more likely to be followed by larger warming rates. The spatial pattern of near-term temperature change varies considerably, but the proportion of the surface showing a warming is more consistent. In addition, ensemble spread in inter-annual temperature declines as the climate warms, especially in the North Atlantic. Over Europe, atmospheric initial condition uncertainty can, for certain ocean initial conditions, lead to 20 year trends in winter and summer in which every location can exhibit either strong cooling or rapid warming. However, the details of the distribution are highly sensitive to the ocean initial condition chosen and particularly the state of the Atlantic meridional overturning circulation. On longer timescales, the warming signal becomes more clear and consistent amongst different initial condition ensembles. An ensemble using a range of different oceanic initial conditions produces a larger spread in temperature trends than ensembles using a single ocean initial condition for all lead times. This highlights the potential benefits from initialising climate predictions from ocean states informed by observations. These results suggest that climate projections need to be performed with many more ensemble members than at present, using a range of ocean initial conditions, if the ... Article in Journal/Newspaper North Atlantic CentAUR: Central Archive at the University of Reading Climate Dynamics 46 11-12 3807 3819 |
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Open Polar |
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CentAUR: Central Archive at the University of Reading |
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ftunivreading |
language |
English |
description |
Model simulations of the next few decades are widely used in assessments of climate change impacts and as guidance for adaptation. Their non-linear nature reveals a level of irreducible uncertainty which it is important to understand and quantify, especially for projections of near-term regional climate. Here we use large idealised initial condition ensembles of the FAMOUS global climate model with a 1 %/year compound increase in CO2 levels to quantify the range of future temperatures in model-based projections. These simulations explore the role of both atmospheric and oceanic initial conditions and are the largest such ensembles to date. Short-term simulated trends in global temperature are diverse, and cooling periods are more likely to be followed by larger warming rates. The spatial pattern of near-term temperature change varies considerably, but the proportion of the surface showing a warming is more consistent. In addition, ensemble spread in inter-annual temperature declines as the climate warms, especially in the North Atlantic. Over Europe, atmospheric initial condition uncertainty can, for certain ocean initial conditions, lead to 20 year trends in winter and summer in which every location can exhibit either strong cooling or rapid warming. However, the details of the distribution are highly sensitive to the ocean initial condition chosen and particularly the state of the Atlantic meridional overturning circulation. On longer timescales, the warming signal becomes more clear and consistent amongst different initial condition ensembles. An ensemble using a range of different oceanic initial conditions produces a larger spread in temperature trends than ensembles using a single ocean initial condition for all lead times. This highlights the potential benefits from initialising climate predictions from ocean states informed by observations. These results suggest that climate projections need to be performed with many more ensemble members than at present, using a range of ocean initial conditions, if the ... |
format |
Article in Journal/Newspaper |
author |
Hawkins, Ed Smith, Robin S. Gregory, Jonathan M. Stainforth, David A. |
spellingShingle |
Hawkins, Ed Smith, Robin S. Gregory, Jonathan M. Stainforth, David A. Irreducible uncertainty in near-term climate projections |
author_facet |
Hawkins, Ed Smith, Robin S. Gregory, Jonathan M. Stainforth, David A. |
author_sort |
Hawkins, Ed |
title |
Irreducible uncertainty in near-term climate projections |
title_short |
Irreducible uncertainty in near-term climate projections |
title_full |
Irreducible uncertainty in near-term climate projections |
title_fullStr |
Irreducible uncertainty in near-term climate projections |
title_full_unstemmed |
Irreducible uncertainty in near-term climate projections |
title_sort |
irreducible uncertainty in near-term climate projections |
publisher |
Springer |
publishDate |
2016 |
url |
https://centaur.reading.ac.uk/48782/ https://centaur.reading.ac.uk/48782/1/art%253A10.1007%252Fs00382-015-2806-8.pdf https://doi.org/10.1007/s00382-015-2806-8 |
genre |
North Atlantic |
genre_facet |
North Atlantic |
op_relation |
https://centaur.reading.ac.uk/48782/1/art%253A10.1007%252Fs00382-015-2806-8.pdf Hawkins, E. <https://centaur.reading.ac.uk/view/creators/90000949.html> orcid:0000-0001-9477-3677 , Smith, R. S. <https://centaur.reading.ac.uk/view/creators/90000556.html> orcid:0000-0001-7479-7778 , Gregory, J. M. <https://centaur.reading.ac.uk/view/creators/90000874.html> and Stainforth, D. A. (2016) Irreducible uncertainty in near-term climate projections. Climate Dynamics, 46 (11). pp. 3807-3819. ISSN 1432-0894 doi: https://doi.org/10.1007/s00382-015-2806-8 <https://doi.org/10.1007/s00382-015-2806-8> |
op_rights |
cc_by_4 |
op_doi |
https://doi.org/10.1007/s00382-015-2806-8 |
container_title |
Climate Dynamics |
container_volume |
46 |
container_issue |
11-12 |
container_start_page |
3807 |
op_container_end_page |
3819 |
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