Skip to main content

A Causality-guided Statistical Approach for Modeling Extreme Mei-yu Rainfall Based on Known Large-scale Modes—A Pilot Study

Abstract

Extreme Mei-yu rainfall (MYR) can cause catastrophic impacts to the economic development and societal welfare in China. While significant improvements have been made in climate models, they often struggle to simulate local-to-regional extreme rainfall (e.g., MYR). Yet, large-scale climate modes (LSCMs) are relatively well represented in climate models. Since there exists a close relationship between MYR and various LSCMs, it might be possible to develop causality-guided statistical models for MYR prediction based on LSCMs. These statistical models could then be applied to climate model simulations to improve the representation of MYR in climate models.

In this pilot study, it is demonstrated that skillful causality-guided statistical models for MYR can be constructed based on known LSCMs. The relevancy of the selected predictors for statistical models are found to be consistent with the literature. The importance of temporal resolution in constructing statistical models for MYR is also shown and is in good agreement with the literature. The results demonstrate the reliability of the causality-guided approach in studying complex circulation systems such as the East Asian summer monsoon (EASM). Some limitations and possible improvements of the current approach are discussed. The application of the causality-guided approach opens up a new possibility to uncover the complex interactions in the EASM in future studies.

References

Download references

Acknowledgements

The authors thank two anonymous reviewers and an associate editor-in-chief for their valuable comments. This work was supported by the UK-China Research and Innovation Partnership Fund through the Met Office Climate Science for Service Partnership (CSSP) China as part of the Newton Fund. The authors thank Dr. Jia WU at National Climate Center, China Meteorological Administration for providing CN05.1. The calculations described in this paper were performed using the Blue-BEAR HPC service at the University of Birmingham.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Kelvin S. Ng.

Additional information

Article Highlights

• Skillful spatiotemporal statistical models of extreme Mei-yu rainfall can be produced using the causality approach.

• Based on spatial consistency, the large-scale climate modes that are relevant to the regional extreme Mei-yu rainfall can be identified.

Electronic Supplementary Material to

376_2022_1348_MOESM1_ESM.pdf

A Causality-guided Statistical Approach for Modeling Extreme Mei-yu Rainfall Based on Known Large-scale Modes—A Pilot Study

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Ng, K.S., Leckebusch, G.C. & Hodges, K.I. A Causality-guided Statistical Approach for Modeling Extreme Mei-yu Rainfall Based on Known Large-scale Modes—A Pilot Study. Adv. Atmos. Sci. (2022). https://doi.org/10.1007/s00376-022-1348-3

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1007/s00376-022-1348-3

Key words

  • extreme rainfall
  • Mei-yu front
  • causality-guided approach
  • large-scale climate modes