Challenges in the Detection and Attribution of Northern Hemisphere Surface Temperature Trends Since 1850

CONNOLLY, RONAN; SOON, WILLIE; CONNOLLY, MICHAEL; BALIUNAS, SALLIE; CIONCO, RODOLFO G.; ELIAS, ANA G.

RESEARCH IN ASTRONOMY AND ASTROPHYSICS

NATL ASTRONOMICAL OBSERVATORIES

Lugar: Beijing; Año: 2023 vol. 23

1674-4527

Research in Astronomy and AstrophysicsRESEARCH PAPER • THE FOLLOWING ARTICLE ISFREE ARTICLEChallenges in the Detection and Attribution of Northern Hemisphere Surface Temperature Trends Since 1850Ronan Connolly1,2, Willie Soon1,3, Michael Connolly1,2, Sallie Baliunas4, Johan Berglund5, C. J. Butler6, Rodolfo Gustavo Cionco7,8, Ana G. Elias9,10, Valery M. Fedorov11, Hermann Harde12Show full author listPublished 27 September 2023 • © 2023. National Astronomical Observatories, CAS and IOP Publishing Ltd.Research in Astronomy and Astrophysics, Volume 23, Number 10Citation Ronan Connolly et al 2023 Res. Astron. Astrophys. 23 105015DOI 10.1088/1674-4527/acf18eDownloadArticle PDFFiguresTablesReferencesDownload PDFArticle metrics8436 Total downloads66 total citations on Dimensions.Article has an altmetric score of 118MathJaxTurn off MathJaxPermissionsGet permission to re-use this articleShare this articleShare this content via emailShare on Facebook (opens new window)Share on Twitter (opens new window)Share on Mendeley (opens new window)Hide article and author informationAuthor e-mailsronan@ceres-science.comAuthor affiliations1 Center for Environmental Research and Earth Science (CERES), Salem, MA 01970, USA; ronan@ceres-science.com2 Independent scientists, Dublin, Ireland3 Institute of Earth Physics and Space Science (EPSS), Sopron, Hungary4 Retired, formerly Harvard-Smithsonian Center for Astrophysics, Cambridge, MA 02138, USA5 Independent researcher, Malmö, Sweden6 Retired, formerly Armagh Observatory, College Hill, Armagh BT61 9DG, Northern Ireland, UK7 Comisión de Investigaciones Científicas de la Provincia de Buenos Aires, Argentina8 Grupo de Estudios Ambientales, Universidad Tecnológica Nacional, Colón 332, San Nicolás (2900), Buenos Aires, Argentina9 Laboratorio de Ionosfera, Atmosfera Neutra y Magnetosfera (LIANM), Facultad de Ciencias Exactas y Tecnología, Universidad Nacional de Tucumán, Av. Independencia 1800, 4000 Tucumán, Argentina10 Instituto de Física del Noroeste Argentino (Consejo Nacional de Investigaciones Científicas y Técnicas—Universidad Nacional de Tucumán), 4000 Tucumán, Argentina11 Faculty of Geography, Lomonosov Moscow State University, Leninskie Gory St. 1, Moscow 119991, Russia12 Helmut-Schmidt-University, Hamburg, Germany13 Center of Excellence in Information Systems, Tennessee State University, Nashville, TN 37209 USA14 Independent scientist, Berkeley Springs, WV, USA15 Emeritus Professor in Physical Geography, Department of Geosciences, University of Oslo, Norway16 Professor Emeritus, College of Earth, Ocean, and the Environment, University of Delaware, Newark DE 19716-2541, USA17 Department of Earth Sciences, Environment and Georesources, University of Naples Federico II, Complesso Universitario di Monte S. Angelo, via Cinthia, 21, I-80126 Naples, Italy18 Retired, formerly Department of Physics and Technology, UiT The Arctic University of Norway, 9037 Tromsø, Norway19 Instituto de Geofisica, Universidad Nacional Autónoma de México, Ciudad Universitaria, Coyoacán, 04510, México D.F., México20 State Key Laboratory of Loess and Quaternary Geology, Institute of Earth Environment, Chinese Academy of Sciences, Xi´an 710061, China21 Department of Mathematics and Physics, Shaoxing University, Shaoxing 312000, ChinaORCID iDsRonan Connolly https://orcid.org/0000-0001-5843-3544DatesReceived 26 July 2023Revised 9 August 2023Accepted 15 August 2023Published 27 September 2023Check for updates using CrossmarkJournal RSSSign up for new issue notificationsAbstractSince 2007, the Intergovernmental Panel on Climate Change (IPCC) has heavily relied on the comparison between global climate model hindcasts and global surface temperature (ST) estimates for concluding that post-1950s global warming is mostly human-caused. In Connolly et al., we cautioned that this approach to the detection and attribution of climate change was highly dependent on the choice of Total Solar Irradiance (TSI) and ST data sets. We compiled 16 TSI and five ST data sets and found by altering the choice of TSI or ST, one could (prematurely) conclude anything from the warming being "mostly human-caused" to "mostly natural." Richardson and Benestad suggested our analysis was "erroneous" and "flawed" because we did not use a multilinear regression. They argued that applying a multilinear regression to one of the five ST series re-affirmed the IPCC´s attribution statement. They also objected that many of the published TSI data sets were out-of-date. However, here we show that when applying multilinear regression analysis to an expanded and updated data set of 27 TSI series, the original conclusions of Connolly et al. are confirmed for all five ST data sets. Therefore, it is still unclear whether the observed warming is mostly human-caused, mostly natural or some combination of both.