JOURNAL ARTICLE

Bayesian assessment of CMIP6 surface net radiation predictions for Köppen–Geiger climate zones.

  • Published In: International Journal of Climatology, 2023, v. 43, n. 12. P. 5387 1 of 3

  • Database: Academic Search Ultimate 2 of 3

  • Authored By: Liu, Zhu 3 of 3

Abstract

Köppen–Geiger climate zones were originally constructed to designate the manifold climates to reflect the mean spatial climate characteristics, which includes the Tropical Zone, Dry Zone, Temperate Zone, Continental Zone and Polar Zone. In this study, 20 CMIP6 models are applied to evaluate historical net radiation (Rn) climatology during 1950–2014 for the five Köppen–Geiger climate zones, respectively. Additionally, Bayesian model averaging (BMA) approach is applied to obtain the multimodel weighted average predictions, which are further used to assess the seasonal variation of net radiation and decadal trends for far historical period (1951–1970), middle historical period (1971–1990) and near historical period (1991–2010), respectively. Moreover, the Bayesian‐Gaussian mixture PDFs are generated for global land surface as well as five climate zones to quantify the uncertainty associated with the BMA predictions. Results indicate that the global land surface Rn is overestimated in general with significant diversity in different climate zones. In addition, Rn prediction from BMA model is more accurate and reliable than individual models. The highest Rn occurs in JJA for Polar Zone and Continental Zone. However, as for zones in lower latitudes, the peaks of Rn reach slightly earlier. The Rn has decreasing trends for Tropical Zone, Continental Zone and Temperate Zones during far historical period; however, it becomes to increasing trends after 1970s, which is strongly related with anthropogenic global warming. In addition, compared to other zones, there exists smallest prediction uncertainty associated with BMA prediction for Dry Zone. [ABSTRACT FROM AUTHOR]

Additional Information

  • Source:International Journal of Climatology. 2023/10, Vol. 43, Issue 12, p5387
  • Document Type:Article
  • Subject Area:Earth and Atmospheric Sciences
  • Publication Date:2023
  • ISSN:0899-8418
  • DOI:10.1002/joc.8152
  • Accession Number:172894550
  • Copyright Statement:Copyright of International Journal of Climatology is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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