Robust anthropogenic signal identified in the seasonal cycle of tropospheric temperature
<jats:title>Abstract</jats:title> <jats:p>Previous work identified an anthropogenic fingerprint pattern in <jats:italic>T</jats:italic><jats:sub>AC</jats:sub>(<jats:italic>x</jats:italic>, <jats:italic>t</jats:italic>), the amplitude...
| Main Authors: | , , , , , , , , , , , , , , , |
|---|---|
| Other Authors: | |
| Format: | Article |
| Language: | English |
| Published: |
American Meteorological Society
2023
|
| Online Access: | https://hdl.handle.net/1721.1/148249 |
| _version_ | 1826210340006789120 |
|---|---|
| author | Santer, Benjamin D Po-Chedley, Stephen Feldl, Nicole Fyfe, John C Fu, Qiang Solomon, Susan England, Mark Rodgers, Keith B Stuecker, Malte F Mears, Carl Zou, Cheng-Zhi Bonfils, Céline JW Pallotta, Giuliana Zelinka, Mark D Rosenbloom, Nan Edwards, Jim |
| author2 | Massachusetts Institute of Technology. Department of Earth, Atmospheric, and Planetary Sciences |
| author_facet | Massachusetts Institute of Technology. Department of Earth, Atmospheric, and Planetary Sciences Santer, Benjamin D Po-Chedley, Stephen Feldl, Nicole Fyfe, John C Fu, Qiang Solomon, Susan England, Mark Rodgers, Keith B Stuecker, Malte F Mears, Carl Zou, Cheng-Zhi Bonfils, Céline JW Pallotta, Giuliana Zelinka, Mark D Rosenbloom, Nan Edwards, Jim |
| author_sort | Santer, Benjamin D |
| collection | MIT |
| description | <jats:title>Abstract</jats:title>
<jats:p>Previous work identified an anthropogenic fingerprint pattern in <jats:italic>T</jats:italic><jats:sub>AC</jats:sub>(<jats:italic>x</jats:italic>, <jats:italic>t</jats:italic>), the amplitude of the seasonal cycle of mid- to upper-tropospheric temperature (TMT), but did not explicitly consider whether fingerprint identification in satellite <jats:italic>T</jats:italic><jats:sub>AC</jats:sub>(<jats:italic>x</jats:italic>, <jats:italic>t</jats:italic>) data could have been influenced by real-world multidecadal internal variability (MIV). We address this question here using large ensembles (LEs) performed with five climate models. LEs provide many different sequences of internal variability noise superimposed on an underlying forced signal. Despite differences in historical external forcings, climate sensitivity, and MIV properties of the five models, their <jats:italic>T</jats:italic><jats:sub>AC</jats:sub>(<jats:italic>x</jats:italic>, <jats:italic>t</jats:italic>) fingerprints are similar and statistically identifiable in 239 of the 240 LE realizations of historical climate change. Comparing simulated and observed variability spectra reveals that consistent fingerprint identification is unlikely to be biased by model underestimates of observed MIV. Even in the presence of large (factor of 3–4) intermodel and inter-realization differences in the amplitude of MIV, the anthropogenic fingerprints of seasonal cycle changes are robustly identifiable in models and satellite data. This is primarily due to the fact that the distinctive, global-scale fingerprint patterns are spatially dissimilar to the smaller-scale patterns of internal <jats:italic>T</jats:italic><jats:sub>AC</jats:sub>(<jats:italic>x</jats:italic>, <jats:italic>t</jats:italic>) variability associated with the Atlantic multidecadal oscillation and El Niño–Southern Oscillation. The robustness of the seasonal cycle detection and attribution results shown here, taken together with the evidence from idealized aquaplanet simulations, suggest that basic physical processes are dictating a common pattern of forced <jats:italic>T</jats:italic><jats:sub>AC</jats:sub>(<jats:italic>x</jats:italic>, <jats:italic>t</jats:italic>) changes in observations and in the five LEs. The key processes involved include GHG-induced expansion of the tropics, lapse-rate changes, land surface drying, and sea ice decrease.</jats:p> |
| first_indexed | 2024-09-23T14:48:15Z |
| format | Article |
| id | mit-1721.1/148249 |
| institution | Massachusetts Institute of Technology |
| language | English |
| last_indexed | 2024-09-23T14:48:15Z |
| publishDate | 2023 |
| publisher | American Meteorological Society |
| record_format | dspace |
| spelling | mit-1721.1/1482492023-03-16T04:05:43Z Robust anthropogenic signal identified in the seasonal cycle of tropospheric temperature Santer, Benjamin D Po-Chedley, Stephen Feldl, Nicole Fyfe, John C Fu, Qiang Solomon, Susan England, Mark Rodgers, Keith B Stuecker, Malte F Mears, Carl Zou, Cheng-Zhi Bonfils, Céline JW Pallotta, Giuliana Zelinka, Mark D Rosenbloom, Nan Edwards, Jim Massachusetts Institute of Technology. Department of Earth, Atmospheric, and Planetary Sciences <jats:title>Abstract</jats:title> <jats:p>Previous work identified an anthropogenic fingerprint pattern in <jats:italic>T</jats:italic><jats:sub>AC</jats:sub>(<jats:italic>x</jats:italic>, <jats:italic>t</jats:italic>), the amplitude of the seasonal cycle of mid- to upper-tropospheric temperature (TMT), but did not explicitly consider whether fingerprint identification in satellite <jats:italic>T</jats:italic><jats:sub>AC</jats:sub>(<jats:italic>x</jats:italic>, <jats:italic>t</jats:italic>) data could have been influenced by real-world multidecadal internal variability (MIV). We address this question here using large ensembles (LEs) performed with five climate models. LEs provide many different sequences of internal variability noise superimposed on an underlying forced signal. Despite differences in historical external forcings, climate sensitivity, and MIV properties of the five models, their <jats:italic>T</jats:italic><jats:sub>AC</jats:sub>(<jats:italic>x</jats:italic>, <jats:italic>t</jats:italic>) fingerprints are similar and statistically identifiable in 239 of the 240 LE realizations of historical climate change. Comparing simulated and observed variability spectra reveals that consistent fingerprint identification is unlikely to be biased by model underestimates of observed MIV. Even in the presence of large (factor of 3–4) intermodel and inter-realization differences in the amplitude of MIV, the anthropogenic fingerprints of seasonal cycle changes are robustly identifiable in models and satellite data. This is primarily due to the fact that the distinctive, global-scale fingerprint patterns are spatially dissimilar to the smaller-scale patterns of internal <jats:italic>T</jats:italic><jats:sub>AC</jats:sub>(<jats:italic>x</jats:italic>, <jats:italic>t</jats:italic>) variability associated with the Atlantic multidecadal oscillation and El Niño–Southern Oscillation. The robustness of the seasonal cycle detection and attribution results shown here, taken together with the evidence from idealized aquaplanet simulations, suggest that basic physical processes are dictating a common pattern of forced <jats:italic>T</jats:italic><jats:sub>AC</jats:sub>(<jats:italic>x</jats:italic>, <jats:italic>t</jats:italic>) changes in observations and in the five LEs. The key processes involved include GHG-induced expansion of the tropics, lapse-rate changes, land surface drying, and sea ice decrease.</jats:p> 2023-02-28T18:16:17Z 2023-02-28T18:16:17Z 2022 2023-02-28T18:02:35Z Article http://purl.org/eprint/type/JournalArticle https://hdl.handle.net/1721.1/148249 Santer, Benjamin D, Po-Chedley, Stephen, Feldl, Nicole, Fyfe, John C, Fu, Qiang et al. 2022. "Robust anthropogenic signal identified in the seasonal cycle of tropospheric temperature." Journal of Climate, 35 (18). en 10.1175/JCLI-D-21-0766.1 Journal of Climate Article is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use. application/pdf American Meteorological Society American Meteorological Society (AMS) |
| spellingShingle | Santer, Benjamin D Po-Chedley, Stephen Feldl, Nicole Fyfe, John C Fu, Qiang Solomon, Susan England, Mark Rodgers, Keith B Stuecker, Malte F Mears, Carl Zou, Cheng-Zhi Bonfils, Céline JW Pallotta, Giuliana Zelinka, Mark D Rosenbloom, Nan Edwards, Jim Robust anthropogenic signal identified in the seasonal cycle of tropospheric temperature |
| title | Robust anthropogenic signal identified in the seasonal cycle of tropospheric temperature |
| title_full | Robust anthropogenic signal identified in the seasonal cycle of tropospheric temperature |
| title_fullStr | Robust anthropogenic signal identified in the seasonal cycle of tropospheric temperature |
| title_full_unstemmed | Robust anthropogenic signal identified in the seasonal cycle of tropospheric temperature |
| title_short | Robust anthropogenic signal identified in the seasonal cycle of tropospheric temperature |
| title_sort | robust anthropogenic signal identified in the seasonal cycle of tropospheric temperature |
| url | https://hdl.handle.net/1721.1/148249 |
| work_keys_str_mv | AT santerbenjamind robustanthropogenicsignalidentifiedintheseasonalcycleoftropospherictemperature AT pochedleystephen robustanthropogenicsignalidentifiedintheseasonalcycleoftropospherictemperature AT feldlnicole robustanthropogenicsignalidentifiedintheseasonalcycleoftropospherictemperature AT fyfejohnc robustanthropogenicsignalidentifiedintheseasonalcycleoftropospherictemperature AT fuqiang robustanthropogenicsignalidentifiedintheseasonalcycleoftropospherictemperature AT solomonsusan robustanthropogenicsignalidentifiedintheseasonalcycleoftropospherictemperature AT englandmark robustanthropogenicsignalidentifiedintheseasonalcycleoftropospherictemperature AT rodgerskeithb robustanthropogenicsignalidentifiedintheseasonalcycleoftropospherictemperature AT stueckermaltef robustanthropogenicsignalidentifiedintheseasonalcycleoftropospherictemperature AT mearscarl robustanthropogenicsignalidentifiedintheseasonalcycleoftropospherictemperature AT zouchengzhi robustanthropogenicsignalidentifiedintheseasonalcycleoftropospherictemperature AT bonfilscelinejw robustanthropogenicsignalidentifiedintheseasonalcycleoftropospherictemperature AT pallottagiuliana robustanthropogenicsignalidentifiedintheseasonalcycleoftropospherictemperature AT zelinkamarkd robustanthropogenicsignalidentifiedintheseasonalcycleoftropospherictemperature AT rosenbloomnan robustanthropogenicsignalidentifiedintheseasonalcycleoftropospherictemperature AT edwardsjim robustanthropogenicsignalidentifiedintheseasonalcycleoftropospherictemperature |