Model evaluation of short-lived climate forcers for the Arctic Monitoring and Assessment Programme: a multi-species, multi-model study
While carbon dioxide is the main cause for global warming, modeling short-lived climate forcers (SLCFs) such as methane, ozone, and particles in the Arctic allows us to simulate near-term climate and health impacts for a sensitive, pristine region that is warming at 3 times the global rate. Atmosphe...
Published in: | Atmospheric Chemistry and Physics |
---|---|
Main Authors: | , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , |
Format: | Text |
Language: | unknown |
Published: |
2022
|
Subjects: | |
Online Access: | https://doi.org/10.5194/acp-22-5775-2022 https://infoscience.epfl.ch/record/294046/files/acp-22-5775-2022.pdf http://infoscience.epfl.ch/record/294046 |
id |
ftinfoscience:oai:infoscience.epfl.ch:294046 |
---|---|
record_format |
openpolar |
spelling |
ftinfoscience:oai:infoscience.epfl.ch:294046 2023-05-15T13:21:35+02:00 Model evaluation of short-lived climate forcers for the Arctic Monitoring and Assessment Programme: a multi-species, multi-model study Whaley, Cynthia H. Mahmood, Rashed von Salzen, Knut Winter, Barbara Eckhardt, Sabine Arnold, Stephen Beagley, Stephen Becagli, Silvia Chien, Rong-You Christensen, Jesper Damani, Sujay Manish Dong, Xinyi Eleftheriadis, Konstantinos Evangeliou, Nikolaos Faluvegi, Gregory Flanner, Mark Fu, Joshua S. Gauss, Michael Giardi, Fabio Gong, Wanmin Hjorth, Jens Liengaard Huang, Lin Im, Ulas Kanaya, Yugo Krishnan, Srinath Klimont, Zbigniew Kühn, Thomas Langner, Joakim Law, Kathy S. Marelle, Louis Massling, Andreas Olivié, Dirk Onishi, Tatsuo Oshima, Naga Peng, Yiran Plummer, David A. Popovicheva, Olga Pozzoli, Luca Raut, Jean-Christophe Sand, Maria Saunders, Laura N. Schmale, Julia Sharma, Sangeeta Skeie, Ragnhild Bieltvedt Skov, Henrik Taketani, Fumikazu Thomas, Manu A. Traversi, Rita Tsigaridis, Kostas Tsyro, Svetlana 2022-05-16T09:35:17Z https://doi.org/10.5194/acp-22-5775-2022 https://infoscience.epfl.ch/record/294046/files/acp-22-5775-2022.pdf http://infoscience.epfl.ch/record/294046 unknown doi:10.5194/acp-22-5775-2022 https://infoscience.epfl.ch/record/294046/files/acp-22-5775-2022.pdf http://infoscience.epfl.ch/record/294046 http://infoscience.epfl.ch/record/294046 Text 2022 ftinfoscience https://doi.org/10.5194/acp-22-5775-2022 2023-02-13T23:10:04Z While carbon dioxide is the main cause for global warming, modeling short-lived climate forcers (SLCFs) such as methane, ozone, and particles in the Arctic allows us to simulate near-term climate and health impacts for a sensitive, pristine region that is warming at 3 times the global rate. Atmospheric modeling is critical for understanding the long-range transport of pollutants to the Arctic, as well as the abundance and distribution of SLCFs throughout the Arctic atmosphere. Modeling is also used as a tool to determine SLCF impacts on climate and health in the present and in future emissions scenarios. In this study, we evaluate 18 state-of-the-art atmospheric and Earth system models by assessing their representation of Arctic and Northern Hemisphere atmospheric SLCF distributions, considering a wide range of different chemical species (methane, tropospheric ozone and its precursors, black carbon, sulfate, organic aerosol, and particulate matter) and multiple observational datasets. Model simulations over 4 years (2008–2009 and 2014–2015) conducted for the 2022 Arctic Monitoring and Assessment Programme (AMAP) SLCF assessment report are thoroughly evaluated against satellite, ground, ship, and aircraft-based observations. The annual means, seasonal cycles, and 3-D distributions of SLCFs were evaluated using several metrics, such as absolute and percent model biases and correlation coefficients. The results show a large range in model performance, with no one particular model or model type performing well for all regions and all SLCF species. The multi-model mean (mmm) was able to represent the general features of SLCFs in the Arctic and had the best overall performance. For the SLCFs with the greatest radiative impact (CH4, O3, BC, and SO ), the mmm was within ±25 % of the measurements across the Northern Hemisphere. Therefore, we recommend a multi-model ensemble be used for simulating climate and health impacts of SLCFs. Of the SLCFs in our study, model biases were smallest for CH4 and greatest for OA. For ... Text AMAP Arctic black carbon Global warming EPFL Infoscience (Ecole Polytechnique Fédérale Lausanne) Arctic Atmospheric Chemistry and Physics 22 9 5775 5828 |
institution |
Open Polar |
collection |
EPFL Infoscience (Ecole Polytechnique Fédérale Lausanne) |
op_collection_id |
ftinfoscience |
language |
unknown |
description |
While carbon dioxide is the main cause for global warming, modeling short-lived climate forcers (SLCFs) such as methane, ozone, and particles in the Arctic allows us to simulate near-term climate and health impacts for a sensitive, pristine region that is warming at 3 times the global rate. Atmospheric modeling is critical for understanding the long-range transport of pollutants to the Arctic, as well as the abundance and distribution of SLCFs throughout the Arctic atmosphere. Modeling is also used as a tool to determine SLCF impacts on climate and health in the present and in future emissions scenarios. In this study, we evaluate 18 state-of-the-art atmospheric and Earth system models by assessing their representation of Arctic and Northern Hemisphere atmospheric SLCF distributions, considering a wide range of different chemical species (methane, tropospheric ozone and its precursors, black carbon, sulfate, organic aerosol, and particulate matter) and multiple observational datasets. Model simulations over 4 years (2008–2009 and 2014–2015) conducted for the 2022 Arctic Monitoring and Assessment Programme (AMAP) SLCF assessment report are thoroughly evaluated against satellite, ground, ship, and aircraft-based observations. The annual means, seasonal cycles, and 3-D distributions of SLCFs were evaluated using several metrics, such as absolute and percent model biases and correlation coefficients. The results show a large range in model performance, with no one particular model or model type performing well for all regions and all SLCF species. The multi-model mean (mmm) was able to represent the general features of SLCFs in the Arctic and had the best overall performance. For the SLCFs with the greatest radiative impact (CH4, O3, BC, and SO ), the mmm was within ±25 % of the measurements across the Northern Hemisphere. Therefore, we recommend a multi-model ensemble be used for simulating climate and health impacts of SLCFs. Of the SLCFs in our study, model biases were smallest for CH4 and greatest for OA. For ... |
format |
Text |
author |
Whaley, Cynthia H. Mahmood, Rashed von Salzen, Knut Winter, Barbara Eckhardt, Sabine Arnold, Stephen Beagley, Stephen Becagli, Silvia Chien, Rong-You Christensen, Jesper Damani, Sujay Manish Dong, Xinyi Eleftheriadis, Konstantinos Evangeliou, Nikolaos Faluvegi, Gregory Flanner, Mark Fu, Joshua S. Gauss, Michael Giardi, Fabio Gong, Wanmin Hjorth, Jens Liengaard Huang, Lin Im, Ulas Kanaya, Yugo Krishnan, Srinath Klimont, Zbigniew Kühn, Thomas Langner, Joakim Law, Kathy S. Marelle, Louis Massling, Andreas Olivié, Dirk Onishi, Tatsuo Oshima, Naga Peng, Yiran Plummer, David A. Popovicheva, Olga Pozzoli, Luca Raut, Jean-Christophe Sand, Maria Saunders, Laura N. Schmale, Julia Sharma, Sangeeta Skeie, Ragnhild Bieltvedt Skov, Henrik Taketani, Fumikazu Thomas, Manu A. Traversi, Rita Tsigaridis, Kostas Tsyro, Svetlana |
spellingShingle |
Whaley, Cynthia H. Mahmood, Rashed von Salzen, Knut Winter, Barbara Eckhardt, Sabine Arnold, Stephen Beagley, Stephen Becagli, Silvia Chien, Rong-You Christensen, Jesper Damani, Sujay Manish Dong, Xinyi Eleftheriadis, Konstantinos Evangeliou, Nikolaos Faluvegi, Gregory Flanner, Mark Fu, Joshua S. Gauss, Michael Giardi, Fabio Gong, Wanmin Hjorth, Jens Liengaard Huang, Lin Im, Ulas Kanaya, Yugo Krishnan, Srinath Klimont, Zbigniew Kühn, Thomas Langner, Joakim Law, Kathy S. Marelle, Louis Massling, Andreas Olivié, Dirk Onishi, Tatsuo Oshima, Naga Peng, Yiran Plummer, David A. Popovicheva, Olga Pozzoli, Luca Raut, Jean-Christophe Sand, Maria Saunders, Laura N. Schmale, Julia Sharma, Sangeeta Skeie, Ragnhild Bieltvedt Skov, Henrik Taketani, Fumikazu Thomas, Manu A. Traversi, Rita Tsigaridis, Kostas Tsyro, Svetlana Model evaluation of short-lived climate forcers for the Arctic Monitoring and Assessment Programme: a multi-species, multi-model study |
author_facet |
Whaley, Cynthia H. Mahmood, Rashed von Salzen, Knut Winter, Barbara Eckhardt, Sabine Arnold, Stephen Beagley, Stephen Becagli, Silvia Chien, Rong-You Christensen, Jesper Damani, Sujay Manish Dong, Xinyi Eleftheriadis, Konstantinos Evangeliou, Nikolaos Faluvegi, Gregory Flanner, Mark Fu, Joshua S. Gauss, Michael Giardi, Fabio Gong, Wanmin Hjorth, Jens Liengaard Huang, Lin Im, Ulas Kanaya, Yugo Krishnan, Srinath Klimont, Zbigniew Kühn, Thomas Langner, Joakim Law, Kathy S. Marelle, Louis Massling, Andreas Olivié, Dirk Onishi, Tatsuo Oshima, Naga Peng, Yiran Plummer, David A. Popovicheva, Olga Pozzoli, Luca Raut, Jean-Christophe Sand, Maria Saunders, Laura N. Schmale, Julia Sharma, Sangeeta Skeie, Ragnhild Bieltvedt Skov, Henrik Taketani, Fumikazu Thomas, Manu A. Traversi, Rita Tsigaridis, Kostas Tsyro, Svetlana |
author_sort |
Whaley, Cynthia H. |
title |
Model evaluation of short-lived climate forcers for the Arctic Monitoring and Assessment Programme: a multi-species, multi-model study |
title_short |
Model evaluation of short-lived climate forcers for the Arctic Monitoring and Assessment Programme: a multi-species, multi-model study |
title_full |
Model evaluation of short-lived climate forcers for the Arctic Monitoring and Assessment Programme: a multi-species, multi-model study |
title_fullStr |
Model evaluation of short-lived climate forcers for the Arctic Monitoring and Assessment Programme: a multi-species, multi-model study |
title_full_unstemmed |
Model evaluation of short-lived climate forcers for the Arctic Monitoring and Assessment Programme: a multi-species, multi-model study |
title_sort |
model evaluation of short-lived climate forcers for the arctic monitoring and assessment programme: a multi-species, multi-model study |
publishDate |
2022 |
url |
https://doi.org/10.5194/acp-22-5775-2022 https://infoscience.epfl.ch/record/294046/files/acp-22-5775-2022.pdf http://infoscience.epfl.ch/record/294046 |
geographic |
Arctic |
geographic_facet |
Arctic |
genre |
AMAP Arctic black carbon Global warming |
genre_facet |
AMAP Arctic black carbon Global warming |
op_source |
http://infoscience.epfl.ch/record/294046 |
op_relation |
doi:10.5194/acp-22-5775-2022 https://infoscience.epfl.ch/record/294046/files/acp-22-5775-2022.pdf http://infoscience.epfl.ch/record/294046 |
op_doi |
https://doi.org/10.5194/acp-22-5775-2022 |
container_title |
Atmospheric Chemistry and Physics |
container_volume |
22 |
container_issue |
9 |
container_start_page |
5775 |
op_container_end_page |
5828 |
_version_ |
1766360404744732672 |