Climate Change Research ›› 2021, Vol. 17 ›› Issue (6): 644-651.doi: 10.12006/j.issn.1673-1719.2021.205

• Special Section on the Sixth Assessment Report of IPCC: WGI • Previous Articles     Next Articles

Interpretation of IPCC AR6 on human influence on the climate system

HU Ting1, SUN Ying1,2()   

  1. 1 Laboratory for Climate Studies, National Climate Center, China Meteorological Administration, Beijing 100081, China
    2 Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Nanjing University of Information Science & Technology, Nanjing 210044, China
  • Received:2021-09-10 Revised:2021-09-18 Online:2021-11-30 Published:2021-10-25
  • Contact: SUN Ying E-mail:sunying@cma.gov.cn

Abstract:

The Working Group I contribution to the IPCC Sixth Assessment Report (AR6) has been released on 9 August 2021. Chapter 3 of the report, entitled “human influence on the climate system”, has quantitatively assessed the human influence on climate system and the climate model representation of observed mean climate, changes and variability. The combined evidence from across the climate system clearly indicated that it is unequivocal that human influence has warmed the atmosphere, ocean and land, and that for most large-scale indicators of climate change, the simulated recent mean climate from the latest generation Coupled Model Intercomparison Project Phase 6 (CMIP6) climate models underpinning this assessment has improved compared to the CMIP5 models assessed in the AR5. With updated observation datasets and paleoclimate evidence, new modelling evidence, improved analysis methods, and deeper process understanding, the report has obtained more reliable and strong evidence of human influence on the climate system. However, uncertainties remain in quantification of the human influence on large-scale indicators of climate change in the atmosphere, ocean, cryosphere and at the land surface. And there is still a significant gap, after decades of works in this field. The limitation includes brevity of the observational records, poor model performance and limited process understanding.

Key words: Detection and attribution, Climate system, Human influence, Model evaluation

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