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 W.; Pallotta, Giuliana; Zelinka, Mark D.; Rosenbloom, Nan; Edwards, Jim

doi:10.1175/jcli-d-21-0766.1

Title: Robust Anthropogenic Signal Identified in the Seasonal Cycle of Tropospheric Temperature

Journal Article · Mon Aug 29 00:00:00 EDT 2022 · Journal of Climate

DOI:https://doi.org/10.1175/jcli-d-21-0766.1· OSTI ID:1885115

Santer, Benjamin D. ^[1]; Po-Chedley, Stephen ^[2]; Feldl, Nicole ^[3]; Fyfe, John C. ^[4]; Fu, Qiang ^[5]; Solomon, Susan ^[6]; England, Mark ^[3]; Rodgers, Keith B. ^[7]; Stuecker, Malte F. ^[8]; Mears, Carl ^[9]; Zou, Cheng-Zhi ^[10]; Bonfils, Céline W. ^[2]; Pallotta, Giuliana ^[2]; Zelinka, Mark D. ^[2]; Rosenbloom, Nan ^[11]; Edwards, Jim ^[11]

Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Univ. of California, Los Angeles, CA (United States)
Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)
Univ. of California, Santa Cruz, CA (United States)
Canadian Centre for Climate Modelling and Analysis (CCCma), Victoria, BC (Canada)
Univ. of Washington, Seattle, WA (United States)
Massachusetts Inst. of Technology (MIT), Cambridge, MA (United States)
IBS Center for Climate Physics, Busan (Korea, Republic of); Pusan National Univ., Busan (Korea, Republic of)
Univ. of Hawaii at Manoa, Honolulu, HI (United States)
Remote Sensing Systems, Santa Rosa, CA (United States)
National Oceanic and Atmospheric Administration (NOAA), Camp Springs, MD (United States). National Environmental Satellite Data and Information Service (NESDIS)
National Center for Atmospheric Research (NCAR), Boulder, CO (United States)

Previous work identified an anthropogenic fingerprint pattern in T_AC(x, t), the amplitude of the seasonal cycle of mid- to upper-tropospheric temperature (TMT), but did not explicitly consider whether fingerprint identification in satellite T_AC(x, t) data could have been influenced by real-world multidecadal internal variability (MIV). Here 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 T_AC(x, t) 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 T_AC(x, t) 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 T_AC(x, t) 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.

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Research Organization:: Lawrence Livermore National Laboratory (LLNL), Livermore, CA (United States)

Sponsoring Organization:: USDOE National Nuclear Security Administration (NNSA); USDOE Laboratory Directed Research and Development (LDRD) Program; National Science Foundation (NSF); National Oceanic and Atmospheric Administration (NOAA); Institute for Basic Sciences (IBS), South Korea; USDOE Office of Science (SC), Biological and Environmental Research (BER). Earth and Environmental Systems Science Division

Grant/Contract Number:: AC52-07NA27344; AGS-1753034; NA20OAR4310445; IBS-R028-D1; AGS-1821437; AGS-1848863; IA 1844590

OSTI ID:: 1885115

Report Number(s):: LLNL-JRNL-833144; 1051239

Journal Information:: Journal of Climate, Vol. 35, Issue 18; ISSN 0894-8755

Publisher:: American Meteorological SocietyCopyright Statement

Country of Publication:: United States

Language:: English

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