糖心视频

A new study has made important strides in understanding a key teleconnection pattern, namely, the circumglobal teleconnection (CGT) pattern, and emphasizes the role of the Indian summer monsoon in improving the representation of CGT in climate models.

Climate models are essential tools used by scientists to predict future climate conditions, but how well models can simulate CGT is still an unsolved problem. This new study, led by Yu Hanzhao, a Ph.D. student at the Institute of Atmospheric 糖心视频ics (IAP) of the Chinese Academy of Sciences, offers fresh insights into how models can be improved.

Results of the study were recently in the Journal of Climate.

Previous studies paid less attention to how well coupled climate models can represent the CGT pattern. "We found that models which accurately capture features of Indian summer monsoon rainfall tend to perform better in simulating CGT," said Yu.

CGT pattern is a type of atmospheric wave activity that can affect climate conditions in mid-latitude regions across the Northern Hemisphere. Better simulations of this pattern could help predict extreme weather events like the 2022 heat wave in China's Yangtze River Valley and 2018 heat wave over Europe.

The research team examined data from 40 climate models used in two major climate research projects (Coupled Models Intercomparison Project Phase 5 and 6, CMIP5 and CMIP6) and found that models with better accuracy in reproducing Indian monsoon rainfall also did a better job at simulating wave structure over west-central Asia, hence elevating overall performance on representing CGT pattern.

The authors further explored the underlying mechanism using Rossby wave source diagnosis, a method for analyzing the formation of atmospheric waves. Results showed that realistic simulation of monsoon rainfall creates upper-level outflow of air mass over the Indian subcontinent and its adjacent regions, which help to excite the CGT pattern over west-central Asia and downstream areas. This link between Indian monsoon rainfall and CGT pattern is crucial for improving climate model predictions.

The research also highlighted the influence of El Ni帽o-Southern Oscillation (ENSO), a climate phenomenon that affects weather worldwide. It is found that the ENSO can impact the simulation skill of CGT patterns by modulating Indian summer monsoon rainfall.

"This study provides a valuable reference for climate modelers to improve their simulations," said Professor Zhou Tianjun, corresponding author of the study and a senior research scientist at IAP and the University of Chinese Academy of Sciences.

"Reducing errors in simulating the CGT pattern in coupled climate models will improve our ability to predict regional climate, such as rainfall and temperature, across the Northern Hemisphere," he said.

By identifying the critical role of the Indian monsoon in global weather patterns, this research opens new avenues for more accurate climate predictions, which could help prepare for and mitigate the impact of extreme weather events in the future.