How well do integrated assessment models represent non-$ CO_{2} $ radiative forcing?
Abstract This study aims to create insight in how Integrated Assessment Models (IAMs) perform in describing the climate forcing by non-$ CO_{2} $ gases and aerosols. The simple climate models (SCMs) included in IAMs have been run with the same prescribed anthropogenic emission pathways and compared...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Harmsen, Mathijs J. H. M. [verfasserIn] van Vuuren, Detlef P [verfasserIn] van den Berg, Maarten [verfasserIn] Hof, Andries F [verfasserIn] Hope, Chris [verfasserIn] Krey, Volker [verfasserIn] Lamarque, Jean-Francois [verfasserIn] Marcucci, Adriana [verfasserIn] Shindell, Drew T [verfasserIn] Schaeffer, Michiel [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2015 |
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| Schlagwörter: |
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| Übergeordnetes Werk: |
Enthalten in: Climatic change - Dordrecht [u.a.] : Springer Science + Business Media B.V, 1977, 133(2015), 4 vom: 07. Sept., Seite 565-582 |
|---|---|
| Übergeordnetes Werk: |
volume:133 ; year:2015 ; number:4 ; day:07 ; month:09 ; pages:565-582 |
| Links: |
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| DOI / URN: |
10.1007/s10584-015-1485-0 |
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| Katalog-ID: |
SPR011474289 |
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| 520 | |a Abstract This study aims to create insight in how Integrated Assessment Models (IAMs) perform in describing the climate forcing by non-$ CO_{2} $ gases and aerosols. The simple climate models (SCMs) included in IAMs have been run with the same prescribed anthropogenic emission pathways and compared to analyses with complex earth system models (ESMs) in terms of concentration and radiative forcing levels. In our comparison, particular attention was given to the short-lived forcers' climate effects. In general, SCMs show forcing levels within the expert model ranges. However, the more simple SCMs seem to underestimate forcing differences between baseline and mitigation scenarios because of omission of ozone, black carbon and/or indirect methane forcing effects. Above all, results also show that among IAMs there is a significant spread (0.74 W/$ m^{2} $ in 2100) in non-$ CO_{2} $ forcing projections for a 2.6 W/$ m^{2} $ mitigation scenario, mainly due to uncertainties in the indirect effects of aerosols. This has large implications for determining optimal mitigation strategies among IAMs with regard to required $ CO_{2} $ forcing targets and policy costs. | ||
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| 700 | 1 | |a van den Berg, Maarten |e verfasserin |4 aut | |
| 700 | 1 | |a Hof, Andries F |e verfasserin |4 aut | |
| 700 | 1 | |a Hope, Chris |e verfasserin |4 aut | |
| 700 | 1 | |a Krey, Volker |e verfasserin |4 aut | |
| 700 | 1 | |a Lamarque, Jean-Francois |e verfasserin |4 aut | |
| 700 | 1 | |a Marcucci, Adriana |e verfasserin |4 aut | |
| 700 | 1 | |a Shindell, Drew T |e verfasserin |4 aut | |
| 700 | 1 | |a Schaeffer, Michiel |e verfasserin |4 aut | |
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10.1007/s10584-015-1485-0 doi (DE-627)SPR011474289 (SPR)s10584-015-1485-0-e DE-627 ger DE-627 rakwb eng 550 ASE 38.82 bkl 43.47 bkl Harmsen, Mathijs J. H. M. verfasserin aut How well do integrated assessment models represent non-$ CO_{2} $ radiative forcing? 2015 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract This study aims to create insight in how Integrated Assessment Models (IAMs) perform in describing the climate forcing by non-$ CO_{2} $ gases and aerosols. The simple climate models (SCMs) included in IAMs have been run with the same prescribed anthropogenic emission pathways and compared to analyses with complex earth system models (ESMs) in terms of concentration and radiative forcing levels. In our comparison, particular attention was given to the short-lived forcers' climate effects. In general, SCMs show forcing levels within the expert model ranges. However, the more simple SCMs seem to underestimate forcing differences between baseline and mitigation scenarios because of omission of ozone, black carbon and/or indirect methane forcing effects. Above all, results also show that among IAMs there is a significant spread (0.74 W/$ m^{2} $ in 2100) in non-$ CO_{2} $ forcing projections for a 2.6 W/$ m^{2} $ mitigation scenario, mainly due to uncertainties in the indirect effects of aerosols. This has large implications for determining optimal mitigation strategies among IAMs with regard to required $ CO_{2} $ forcing targets and policy costs. Black Carbon (dpeaa)DE-He213 Force Level (dpeaa)DE-He213 Radiative Force (dpeaa)DE-He213 Tropospheric Ozone (dpeaa)DE-He213 Force Effect (dpeaa)DE-He213 van Vuuren, Detlef P verfasserin aut van den Berg, Maarten verfasserin aut Hof, Andries F verfasserin aut Hope, Chris verfasserin aut Krey, Volker verfasserin aut Lamarque, Jean-Francois verfasserin aut Marcucci, Adriana verfasserin aut Shindell, Drew T verfasserin aut Schaeffer, Michiel verfasserin aut Enthalten in Climatic change Dordrecht [u.a.] : Springer Science + Business Media B.V, 1977 133(2015), 4 vom: 07. Sept., Seite 565-582 (DE-627)270429514 (DE-600)1477652-2 1573-1480 nnns volume:133 year:2015 number:4 day:07 month:09 pages:565-582 https://dx.doi.org/10.1007/s10584-015-1485-0 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OPC-GGO SSG-OPC-ASE GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_381 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 38.82 ASE 43.47 ASE AR 133 2015 4 07 09 565-582 |
| spelling |
10.1007/s10584-015-1485-0 doi (DE-627)SPR011474289 (SPR)s10584-015-1485-0-e DE-627 ger DE-627 rakwb eng 550 ASE 38.82 bkl 43.47 bkl Harmsen, Mathijs J. H. M. verfasserin aut How well do integrated assessment models represent non-$ CO_{2} $ radiative forcing? 2015 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract This study aims to create insight in how Integrated Assessment Models (IAMs) perform in describing the climate forcing by non-$ CO_{2} $ gases and aerosols. The simple climate models (SCMs) included in IAMs have been run with the same prescribed anthropogenic emission pathways and compared to analyses with complex earth system models (ESMs) in terms of concentration and radiative forcing levels. In our comparison, particular attention was given to the short-lived forcers' climate effects. In general, SCMs show forcing levels within the expert model ranges. However, the more simple SCMs seem to underestimate forcing differences between baseline and mitigation scenarios because of omission of ozone, black carbon and/or indirect methane forcing effects. Above all, results also show that among IAMs there is a significant spread (0.74 W/$ m^{2} $ in 2100) in non-$ CO_{2} $ forcing projections for a 2.6 W/$ m^{2} $ mitigation scenario, mainly due to uncertainties in the indirect effects of aerosols. This has large implications for determining optimal mitigation strategies among IAMs with regard to required $ CO_{2} $ forcing targets and policy costs. Black Carbon (dpeaa)DE-He213 Force Level (dpeaa)DE-He213 Radiative Force (dpeaa)DE-He213 Tropospheric Ozone (dpeaa)DE-He213 Force Effect (dpeaa)DE-He213 van Vuuren, Detlef P verfasserin aut van den Berg, Maarten verfasserin aut Hof, Andries F verfasserin aut Hope, Chris verfasserin aut Krey, Volker verfasserin aut Lamarque, Jean-Francois verfasserin aut Marcucci, Adriana verfasserin aut Shindell, Drew T verfasserin aut Schaeffer, Michiel verfasserin aut Enthalten in Climatic change Dordrecht [u.a.] : Springer Science + Business Media B.V, 1977 133(2015), 4 vom: 07. Sept., Seite 565-582 (DE-627)270429514 (DE-600)1477652-2 1573-1480 nnns volume:133 year:2015 number:4 day:07 month:09 pages:565-582 https://dx.doi.org/10.1007/s10584-015-1485-0 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OPC-GGO SSG-OPC-ASE GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_381 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 38.82 ASE 43.47 ASE AR 133 2015 4 07 09 565-582 |
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10.1007/s10584-015-1485-0 doi (DE-627)SPR011474289 (SPR)s10584-015-1485-0-e DE-627 ger DE-627 rakwb eng 550 ASE 38.82 bkl 43.47 bkl Harmsen, Mathijs J. H. M. verfasserin aut How well do integrated assessment models represent non-$ CO_{2} $ radiative forcing? 2015 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract This study aims to create insight in how Integrated Assessment Models (IAMs) perform in describing the climate forcing by non-$ CO_{2} $ gases and aerosols. The simple climate models (SCMs) included in IAMs have been run with the same prescribed anthropogenic emission pathways and compared to analyses with complex earth system models (ESMs) in terms of concentration and radiative forcing levels. In our comparison, particular attention was given to the short-lived forcers' climate effects. In general, SCMs show forcing levels within the expert model ranges. However, the more simple SCMs seem to underestimate forcing differences between baseline and mitigation scenarios because of omission of ozone, black carbon and/or indirect methane forcing effects. Above all, results also show that among IAMs there is a significant spread (0.74 W/$ m^{2} $ in 2100) in non-$ CO_{2} $ forcing projections for a 2.6 W/$ m^{2} $ mitigation scenario, mainly due to uncertainties in the indirect effects of aerosols. This has large implications for determining optimal mitigation strategies among IAMs with regard to required $ CO_{2} $ forcing targets and policy costs. Black Carbon (dpeaa)DE-He213 Force Level (dpeaa)DE-He213 Radiative Force (dpeaa)DE-He213 Tropospheric Ozone (dpeaa)DE-He213 Force Effect (dpeaa)DE-He213 van Vuuren, Detlef P verfasserin aut van den Berg, Maarten verfasserin aut Hof, Andries F verfasserin aut Hope, Chris verfasserin aut Krey, Volker verfasserin aut Lamarque, Jean-Francois verfasserin aut Marcucci, Adriana verfasserin aut Shindell, Drew T verfasserin aut Schaeffer, Michiel verfasserin aut Enthalten in Climatic change Dordrecht [u.a.] : Springer Science + Business Media B.V, 1977 133(2015), 4 vom: 07. Sept., Seite 565-582 (DE-627)270429514 (DE-600)1477652-2 1573-1480 nnns volume:133 year:2015 number:4 day:07 month:09 pages:565-582 https://dx.doi.org/10.1007/s10584-015-1485-0 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OPC-GGO SSG-OPC-ASE GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_381 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 38.82 ASE 43.47 ASE AR 133 2015 4 07 09 565-582 |
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10.1007/s10584-015-1485-0 doi (DE-627)SPR011474289 (SPR)s10584-015-1485-0-e DE-627 ger DE-627 rakwb eng 550 ASE 38.82 bkl 43.47 bkl Harmsen, Mathijs J. H. M. verfasserin aut How well do integrated assessment models represent non-$ CO_{2} $ radiative forcing? 2015 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract This study aims to create insight in how Integrated Assessment Models (IAMs) perform in describing the climate forcing by non-$ CO_{2} $ gases and aerosols. The simple climate models (SCMs) included in IAMs have been run with the same prescribed anthropogenic emission pathways and compared to analyses with complex earth system models (ESMs) in terms of concentration and radiative forcing levels. In our comparison, particular attention was given to the short-lived forcers' climate effects. In general, SCMs show forcing levels within the expert model ranges. However, the more simple SCMs seem to underestimate forcing differences between baseline and mitigation scenarios because of omission of ozone, black carbon and/or indirect methane forcing effects. Above all, results also show that among IAMs there is a significant spread (0.74 W/$ m^{2} $ in 2100) in non-$ CO_{2} $ forcing projections for a 2.6 W/$ m^{2} $ mitigation scenario, mainly due to uncertainties in the indirect effects of aerosols. This has large implications for determining optimal mitigation strategies among IAMs with regard to required $ CO_{2} $ forcing targets and policy costs. Black Carbon (dpeaa)DE-He213 Force Level (dpeaa)DE-He213 Radiative Force (dpeaa)DE-He213 Tropospheric Ozone (dpeaa)DE-He213 Force Effect (dpeaa)DE-He213 van Vuuren, Detlef P verfasserin aut van den Berg, Maarten verfasserin aut Hof, Andries F verfasserin aut Hope, Chris verfasserin aut Krey, Volker verfasserin aut Lamarque, Jean-Francois verfasserin aut Marcucci, Adriana verfasserin aut Shindell, Drew T verfasserin aut Schaeffer, Michiel verfasserin aut Enthalten in Climatic change Dordrecht [u.a.] : Springer Science + Business Media B.V, 1977 133(2015), 4 vom: 07. Sept., Seite 565-582 (DE-627)270429514 (DE-600)1477652-2 1573-1480 nnns volume:133 year:2015 number:4 day:07 month:09 pages:565-582 https://dx.doi.org/10.1007/s10584-015-1485-0 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OPC-GGO SSG-OPC-ASE GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_381 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 38.82 ASE 43.47 ASE AR 133 2015 4 07 09 565-582 |
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Harmsen, Mathijs J. H. M. @@aut@@ van Vuuren, Detlef P @@aut@@ van den Berg, Maarten @@aut@@ Hof, Andries F @@aut@@ Hope, Chris @@aut@@ Krey, Volker @@aut@@ Lamarque, Jean-Francois @@aut@@ Marcucci, Adriana @@aut@@ Shindell, Drew T @@aut@@ Schaeffer, Michiel @@aut@@ |
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The simple climate models (SCMs) included in IAMs have been run with the same prescribed anthropogenic emission pathways and compared to analyses with complex earth system models (ESMs) in terms of concentration and radiative forcing levels. In our comparison, particular attention was given to the short-lived forcers' climate effects. In general, SCMs show forcing levels within the expert model ranges. However, the more simple SCMs seem to underestimate forcing differences between baseline and mitigation scenarios because of omission of ozone, black carbon and/or indirect methane forcing effects. Above all, results also show that among IAMs there is a significant spread (0.74 W/$ m^{2} $ in 2100) in non-$ CO_{2} $ forcing projections for a 2.6 W/$ m^{2} $ mitigation scenario, mainly due to uncertainties in the indirect effects of aerosols. 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Harmsen, Mathijs J. H. M. |
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Harmsen, Mathijs J. H. M. ddc 550 bkl 38.82 bkl 43.47 misc Black Carbon misc Force Level misc Radiative Force misc Tropospheric Ozone misc Force Effect How well do integrated assessment models represent non-$ CO_{2} $ radiative forcing? |
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Harmsen, Mathijs J. H. M. van Vuuren, Detlef P van den Berg, Maarten Hof, Andries F Hope, Chris Krey, Volker Lamarque, Jean-Francois Marcucci, Adriana Shindell, Drew T Schaeffer, Michiel |
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how well do integrated assessment models represent non-$ co_{2} $ radiative forcing? |
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How well do integrated assessment models represent non-$ CO_{2} $ radiative forcing? |
| abstract |
Abstract This study aims to create insight in how Integrated Assessment Models (IAMs) perform in describing the climate forcing by non-$ CO_{2} $ gases and aerosols. The simple climate models (SCMs) included in IAMs have been run with the same prescribed anthropogenic emission pathways and compared to analyses with complex earth system models (ESMs) in terms of concentration and radiative forcing levels. In our comparison, particular attention was given to the short-lived forcers' climate effects. In general, SCMs show forcing levels within the expert model ranges. However, the more simple SCMs seem to underestimate forcing differences between baseline and mitigation scenarios because of omission of ozone, black carbon and/or indirect methane forcing effects. Above all, results also show that among IAMs there is a significant spread (0.74 W/$ m^{2} $ in 2100) in non-$ CO_{2} $ forcing projections for a 2.6 W/$ m^{2} $ mitigation scenario, mainly due to uncertainties in the indirect effects of aerosols. This has large implications for determining optimal mitigation strategies among IAMs with regard to required $ CO_{2} $ forcing targets and policy costs. |
| abstractGer |
Abstract This study aims to create insight in how Integrated Assessment Models (IAMs) perform in describing the climate forcing by non-$ CO_{2} $ gases and aerosols. The simple climate models (SCMs) included in IAMs have been run with the same prescribed anthropogenic emission pathways and compared to analyses with complex earth system models (ESMs) in terms of concentration and radiative forcing levels. In our comparison, particular attention was given to the short-lived forcers' climate effects. In general, SCMs show forcing levels within the expert model ranges. However, the more simple SCMs seem to underestimate forcing differences between baseline and mitigation scenarios because of omission of ozone, black carbon and/or indirect methane forcing effects. Above all, results also show that among IAMs there is a significant spread (0.74 W/$ m^{2} $ in 2100) in non-$ CO_{2} $ forcing projections for a 2.6 W/$ m^{2} $ mitigation scenario, mainly due to uncertainties in the indirect effects of aerosols. This has large implications for determining optimal mitigation strategies among IAMs with regard to required $ CO_{2} $ forcing targets and policy costs. |
| abstract_unstemmed |
Abstract This study aims to create insight in how Integrated Assessment Models (IAMs) perform in describing the climate forcing by non-$ CO_{2} $ gases and aerosols. The simple climate models (SCMs) included in IAMs have been run with the same prescribed anthropogenic emission pathways and compared to analyses with complex earth system models (ESMs) in terms of concentration and radiative forcing levels. In our comparison, particular attention was given to the short-lived forcers' climate effects. In general, SCMs show forcing levels within the expert model ranges. However, the more simple SCMs seem to underestimate forcing differences between baseline and mitigation scenarios because of omission of ozone, black carbon and/or indirect methane forcing effects. Above all, results also show that among IAMs there is a significant spread (0.74 W/$ m^{2} $ in 2100) in non-$ CO_{2} $ forcing projections for a 2.6 W/$ m^{2} $ mitigation scenario, mainly due to uncertainties in the indirect effects of aerosols. This has large implications for determining optimal mitigation strategies among IAMs with regard to required $ CO_{2} $ forcing targets and policy costs. |
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| container_issue |
4 |
| title_short |
How well do integrated assessment models represent non-$ CO_{2} $ radiative forcing? |
| url |
https://dx.doi.org/10.1007/s10584-015-1485-0 |
| remote_bool |
true |
| author2 |
van Vuuren, Detlef P van den Berg, Maarten Hof, Andries F Hope, Chris Krey, Volker Lamarque, Jean-Francois Marcucci, Adriana Shindell, Drew T Schaeffer, Michiel |
| author2Str |
van Vuuren, Detlef P van den Berg, Maarten Hof, Andries F Hope, Chris Krey, Volker Lamarque, Jean-Francois Marcucci, Adriana Shindell, Drew T Schaeffer, Michiel |
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270429514 |
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c |
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true |
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| doi_str |
10.1007/s10584-015-1485-0 |
| up_date |
2024-07-03T22:52:01.819Z |
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1803600130811625472 |
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| score |
7.399868 |