Limited Skill of Projected Land Precipitation by IPCC Models During 2002-2020
JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES(2023)
Abstract
Climate models are widely used to project future climate changes and analyze underlying mechanisms. However, it remains unknown whether the earlier precipitation projections match the subsequent observations in recent decades, which is the scientific basis for the confidence of precipitation projections and associated impacts. Here, we find models in the Third (TAR), Fourth (AR4), and Fifth (AR5) Assessment Reports of the Intergovernmental Panel on Climate Change (IPCC) skillfully project the subsequent climatological changes in global mean land precipitation for 2002-2020, 2008-2020, and 2014-2020 (relative to 1980-1999 climatology) from several to 10 years ahead, respectively. Skillful regional projections are mainly found in the northern mid to high latitudes. IPCC models are less skillful in projecting subsequent changes in land precipitation at regional scales than at global scales, which is likely to be at least partly explained by the lower signal-to-noise ratio. Plain Language Summary As an important tool, climate models are widely used to project future climate changes and analyze underlying mechanisms. The precondition of this is that the projections of climate models are credible. The most convincing way of validating the credibility of climate projections is to quantify the extent to which past projections agree with subsequent observations. Here, we provide a comprehensive analysis on the skill of past climate models in projecting the subsequent precipitation changes over global land. Results show that models have robust skills in projecting the subsequent climatological changes in global mean land precipitation from several to 10 years ahead. Relative to global scale land, the models are less skillful in projecting the subsequent changes in precipitation at regional scale, although they exhibit some skills in northern mid- to high-latitudes.
MoreTranslated text
Key words
projected land precipitation,ipcc models
AI Read Science
Must-Reading Tree
Example
![](https://originalfileserver.aminer.cn/sys/aminer/pubs/mrt_preview.jpeg)
Generate MRT to find the research sequence of this paper
Chat Paper
Summary is being generated by the instructions you defined