Articles | Volume 8, issue 2
Adv. Stat. Clim. Meteorol. Oceanogr., 8, 249–271, 2022
https://doi.org/10.5194/ascmo-8-249-2022
Adv. Stat. Clim. Meteorol. Oceanogr., 8, 249–271, 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 et al.

Related authors

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
Short summary

Related subject area

Statistics
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
Short summary
A conditional approach for joint estimation of wind speed and direction under future climates
Qiuyi Wu, Julie Bessac, Whitney Huang, Jiali Wang, and Rao Kotamarthi
Adv. Stat. Clim. Meteorol. Oceanogr., 8, 205–224, https://doi.org/10.5194/ascmo-8-205-2022,https://doi.org/10.5194/ascmo-8-205-2022, 2022
Short summary
Comparing climate time series – Part 2: A multivariate test
Timothy DelSole and Michael K. Tippett
Adv. Stat. Clim. Meteorol. Oceanogr., 7, 73–85, https://doi.org/10.5194/ascmo-7-73-2021,https://doi.org/10.5194/ascmo-7-73-2021, 2021
Short summary
Forecast score distributions with imperfect observations
Julie Bessac and Philippe Naveau
Adv. Stat. Clim. Meteorol. Oceanogr., 7, 53–71, https://doi.org/10.5194/ascmo-7-53-2021,https://doi.org/10.5194/ascmo-7-53-2021, 2021
Short summary
Novel measures for summarizing high-resolution forecast performance
Eric Gilleland
Adv. Stat. Clim. Meteorol. Oceanogr., 7, 13–34, https://doi.org/10.5194/ascmo-7-13-2021,https://doi.org/10.5194/ascmo-7-13-2021, 2021
Short summary

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.