Pareto optimal analysis of global warming prevention by geoengineering methods
The study is based on a three-dimensional hydrodynamic global climate coupled model, including ocean model with real depths and continents configuration, sea ice evolution model and energy and moisture balance atmosphere model. Aerosol concentration from the year 2010 to 2100 is calculated as a cont...
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Online Access: | https://doi.org/10.20537/2076-7633-2015-7-5-1097-1108 https://doaj.org/article/843977b52a9f4a2381f6be109ca73482 |
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ftdoajarticles:oai:doaj.org/article:843977b52a9f4a2381f6be109ca73482 2023-05-15T18:18:19+02:00 Pareto optimal analysis of global warming prevention by geoengineering methods P. V. Parkhomenko 2015-10-01T00:00:00Z https://doi.org/10.20537/2076-7633-2015-7-5-1097-1108 https://doaj.org/article/843977b52a9f4a2381f6be109ca73482 RU rus Institute of Computer Science http://crm.ics.org.ru/uploads/crmissues/crm_2015_5/15.07.111.pdf https://doaj.org/toc/2076-7633 https://doaj.org/toc/2077-6853 2076-7633 2077-6853 doi:10.20537/2076-7633-2015-7-5-1097-1108 https://doaj.org/article/843977b52a9f4a2381f6be109ca73482 Компьютерные исследования и моделирование, Vol 7, Iss 5, Pp 1097-1108 (2015) climate modelling geoengineering climate stabilization Applied mathematics. Quantitative methods T57-57.97 Mathematics QA1-939 article 2015 ftdoajarticles https://doi.org/10.20537/2076-7633-2015-7-5-1097-1108 2022-12-31T14:55:20Z The study is based on a three-dimensional hydrodynamic global climate coupled model, including ocean model with real depths and continents configuration, sea ice evolution model and energy and moisture balance atmosphere model. Aerosol concentration from the year 2010 to 2100 is calculated as a controlling parameter to stabilize mean year surface air temperature. It is shown that by this way it is impossible to achieve the space and seasonal uniform approximation to the existing climate, although it is possible significantly reduce the greenhouse warming effect. Climate will be colder at 0.1-0.2 degrees in the low and mid-latitudes and at high latitudes it will be warmer at 0.2-1.2 degrees. The Pareto frontier is investigated and visualized for two parameters - atmospheric temperature mean square deviation for the winter and summer seasons. The Pareto optimal amount of sulfur emissions would be between 23.5 and 26.5 TgS/year. Article in Journal/Newspaper Sea ice Directory of Open Access Journals: DOAJ Articles Computer Research and Modeling 7 5 1097 1108 |
institution |
Open Polar |
collection |
Directory of Open Access Journals: DOAJ Articles |
op_collection_id |
ftdoajarticles |
language |
Russian |
topic |
climate modelling geoengineering climate stabilization Applied mathematics. Quantitative methods T57-57.97 Mathematics QA1-939 |
spellingShingle |
climate modelling geoengineering climate stabilization Applied mathematics. Quantitative methods T57-57.97 Mathematics QA1-939 P. V. Parkhomenko Pareto optimal analysis of global warming prevention by geoengineering methods |
topic_facet |
climate modelling geoengineering climate stabilization Applied mathematics. Quantitative methods T57-57.97 Mathematics QA1-939 |
description |
The study is based on a three-dimensional hydrodynamic global climate coupled model, including ocean model with real depths and continents configuration, sea ice evolution model and energy and moisture balance atmosphere model. Aerosol concentration from the year 2010 to 2100 is calculated as a controlling parameter to stabilize mean year surface air temperature. It is shown that by this way it is impossible to achieve the space and seasonal uniform approximation to the existing climate, although it is possible significantly reduce the greenhouse warming effect. Climate will be colder at 0.1-0.2 degrees in the low and mid-latitudes and at high latitudes it will be warmer at 0.2-1.2 degrees. The Pareto frontier is investigated and visualized for two parameters - atmospheric temperature mean square deviation for the winter and summer seasons. The Pareto optimal amount of sulfur emissions would be between 23.5 and 26.5 TgS/year. |
format |
Article in Journal/Newspaper |
author |
P. V. Parkhomenko |
author_facet |
P. V. Parkhomenko |
author_sort |
P. V. Parkhomenko |
title |
Pareto optimal analysis of global warming prevention by geoengineering methods |
title_short |
Pareto optimal analysis of global warming prevention by geoengineering methods |
title_full |
Pareto optimal analysis of global warming prevention by geoengineering methods |
title_fullStr |
Pareto optimal analysis of global warming prevention by geoengineering methods |
title_full_unstemmed |
Pareto optimal analysis of global warming prevention by geoengineering methods |
title_sort |
pareto optimal analysis of global warming prevention by geoengineering methods |
publisher |
Institute of Computer Science |
publishDate |
2015 |
url |
https://doi.org/10.20537/2076-7633-2015-7-5-1097-1108 https://doaj.org/article/843977b52a9f4a2381f6be109ca73482 |
genre |
Sea ice |
genre_facet |
Sea ice |
op_source |
Компьютерные исследования и моделирование, Vol 7, Iss 5, Pp 1097-1108 (2015) |
op_relation |
http://crm.ics.org.ru/uploads/crmissues/crm_2015_5/15.07.111.pdf https://doaj.org/toc/2076-7633 https://doaj.org/toc/2077-6853 2076-7633 2077-6853 doi:10.20537/2076-7633-2015-7-5-1097-1108 https://doaj.org/article/843977b52a9f4a2381f6be109ca73482 |
op_doi |
https://doi.org/10.20537/2076-7633-2015-7-5-1097-1108 |
container_title |
Computer Research and Modeling |
container_volume |
7 |
container_issue |
5 |
container_start_page |
1097 |
op_container_end_page |
1108 |
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1766194869518204928 |