Articles | Volume 8, issue 2
https://doi.org/10.5194/ascmo-8-249-2022
https://doi.org/10.5194/ascmo-8-249-2022
14 Dec 2022
 | 14 Dec 2022

Evaluation of simulated responses to climate forcings: a flexible statistical framework using confirmatory factor analysis and structural equation modelling – Part 2: Numerical experiment

Katarina Lashgari, Anders Moberg, and Gudrun Brattström

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Evaluation of simulated responses to climate forcings: a flexible statistical framework using confirmatory factor analysis and structural equation modelling – Part 1: Theory
Katarina Lashgari, Gudrun Brattström, Anders Moberg, and Rolf Sundberg
Adv. Stat. Clim. Meteorol. Oceanogr., 8, 225–248, https://doi.org/10.5194/ascmo-8-225-2022,https://doi.org/10.5194/ascmo-8-225-2022, 2022
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Cited articles

Allen, M. R. and Stott, P. A.: Estimating signal amplitudes in optimal fingerprinting, part I: theory, Clim. Dynam., 21, 477–491, https://doi.org/10.1007/s00382-003-0313-9, 2003. a
Bindoff, N. L., Stott, P. A., AchutaRao, K. M., Allen, M. R., Gillet, N., Gutzler, D., Hansingo, K., Hegerl, G., Hu, Y., Jain, S., Mokhov, I. I., Overland, J., Perlwitz, J., Sebbari, R., and Zhang, X.: Detection and Attribution of Climate Change: from Global to Regional, in: Climate Change 2013: The Physical Science Basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovermental Panel on Climate Change, edited by: Stocker, T. F., Qin, D., Plattner, G.-K., Tignor, M., Allen, S. K., Boschung, J., Nauels, A., Xia, Y., Bex V., and Medgley, P. M., Cambridge University Press, Cambridge, UK and New York, NY, USA, 867–952, 2013. a
Bollen, K. A.: Structural equations with latent variables, Wiley, ISBN 0471011711, 1989. 
Braconnot, P., Harrison, S. P., Kageyama, M., Bartlein, P. J., Masson-Delmotte, V., Abe-Ouchi, A., Otto-Bliesner, B., and Zhao, Y.: Evaluation of climate models using palaeoclimatic data, Nat. Clim. Change, 2, 417–424, https://doi.org/10.1038/nclimate1456, 2012. a
Brewer, S., Guiot, J., and Torre, F.: Mid-Holocene climate change in Europe: a data-model comparison, Clim. Past, 3, 499–512, https://doi.org/10.5194/cp-3-499-2007, 2007a. a
Short summary
The performance of a new statistical framework containing various structural equation modelling (SEM) models is evaluated in a pseudo-proxy experiment in comparison with the performance of statistical models used in many detection and attribution studies. Each statistical model was fitted to seven continental-scale regional temperature data sets. The results indicated the SEM specification is the most appropriate for describing the underlying latent structure of the simulated data analysed.
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