Wu et al. (2025) Changes of Eurasian Cold Winters and Their Associated Key Variables Based on CMIP6 Global Climate Models

⚠️ Warning: This summary was generated from the abstract only, as the full text was not available.

Identification

• Journal: Journal of Geophysical Research Atmospheres
• Year: 2025
• Date: 2025-12-18
• Authors: Jie Wu, Ying Xu, Ying Shi, Guangxu Liu, Juncheng Lei
• DOI: 10.1029/2025jd044570

Research Groups

Multiple international research institutions contributing to the Coupled Model Intercomparison Project (CMIP) phases 5 and 6.

Short Summary

This study evaluates the historical simulation skill of CMIP5 and CMIP6 global climate models for Eurasian cold winters and associated atmospheric variables, finding CMIP6 outperforms CMIP5. It also projects a decrease in cold winter probability and a "warm Arctic and cold Eurasia" pattern under future climate change scenarios.

Objective

• To evaluate the historical simulation skill of 31 CMIP6 and 33 CMIP5 global climate models for surface air temperature, sea level pressure, 500-hPa geopotential height, 150-hPa meridional and zonal wind, and polar vortex indices during Eurasian cold winters.
• To quantify the advancements of CMIP6 over CMIP5 in simulating these variables.
• To project future changes in these variables and the occurrence probability of cold winters under three Shared Socioeconomic Pathways (SSP 1-2.6, SSP 2-4.5, and SSP 5-8.5).

Study Configuration

• Spatial Scale: Eurasia, Arctic region, and global (as simulated by global climate models).
• Temporal Scale: Historical period (for model evaluation) and future projections (under SSPs) for the 21st century.

Methodology and Data

• Models used: 31 global climate models from CMIP6, 33 global climate models from CMIP5.
• Data sources: Outputs from CMIP5 and CMIP6 global climate models; observational data for model validation (specific sources not detailed in the abstract).

Main Results

• Multimodel ensemble means from both CMIP5 and CMIP6 effectively capture the main features of observed Eurasian cold winters and their associated factors.
• The CMIP6 ensemble mean demonstrates superior performance compared to its CMIP5 counterpart.
• Both CMIP5 and CMIP6 ensemble means perform better than individual CMIP6 models.
• Among CMIP6 models, 500-hPa geopotential height shows the highest simulation skill, while sea level pressure exhibits the lowest.
• CMIP6 models show overall improvements compared to same-institute CMIP5 models, with notable advancements in sea level pressure simulation.
• Under all three SSPs, the occurrence probability of cold winters is projected to decrease, accompanied by a decline in the area and intensity indices of the polar vortex.
• Future surface temperature anomalies are projected to exhibit a "warm Arctic and cold Eurasia" pattern.
• Anticyclonic anomalies at 500 hPa and 150 hPa are projected to be centered at high latitudes in the future.

Contributions

• Provides a comprehensive intercomparison and quantification of the advancements of CMIP6 over CMIP5 in simulating Eurasian cold winters and associated atmospheric circulation.
• Offers future projections of cold winter probability and related atmospheric variables under various SSPs, highlighting a consistent decrease in cold winter occurrence and a "warm Arctic and cold Eurasia" pattern.
• Identifies specific strengths and weaknesses of CMIP6 models in simulating different atmospheric variables relevant to cold winters.

Funding

Not specified in the abstract.

Citation

@article{Wu2025Changes,
  author = {Wu, Jie and Xu, Ying and Shi, Ying and Liu, Guangxu and Lei, Juncheng},
  title = {Changes of Eurasian Cold Winters and Their Associated Key Variables Based on CMIP6 Global Climate Models},
  journal = {Journal of Geophysical Research Atmospheres},
  year = {2025},
  doi = {10.1029/2025jd044570},
  url = {https://doi.org/10.1029/2025jd044570}
}