Tropical monsoon rainfall can be predicted with lead times up to 10 months

Tropical monsoons play a critical role in shaping regional and global climate systems, with profound ecological and socio-economic impacts. However, their long-term prediction remains challenging due to the complex interplay of regional dynamics, global climate drivers, large-scale teleconnections, and inherent non-stationarities in the climate system. Here, we introduce a unified network-based framework for predicting monsoon precipitation across diverse tropical regions. By leveraging global 2-meter air temperature fields, this approach captures large-scale climate teleconnections, such as the El Niño-Southern Oscillation and Rossby waves, enabling accurate forecasts for four key monsoon systems: the South American, East Asian, West African, and Indian monsoons. Our framework achieves remarkable forecasting accuracy with lead times of 4-10 months, outperforming traditional systems such as Seasonal Forecast System 5 and Climate Forecast System version 2. Beyond its predictive capabilities, the framework offers flexibility for application to other regions and climate phenomena, advancing our understanding of global climate dynamics. These findings have far-reaching implications for disaster preparedness, resource management, and sustainable development. Rainy season forecasts in tropical monsoon regions that incorporates largescale climate teleconnections, have higher predictive skills compared to traditional climate models and increase lead times between 4 and 10 months, according to a network-based unified forecasting system.

Authors

Institutions

Publication Details

Journal
Communications Earth & Environment
Published
2025-05-28
DOI
https://doi.org/10.1038/s43247-025-02391-1
Citations
1
Primary Topic
Climate variability and models
Type
article
Field-Weighted Citation Impact
1.11

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Tropical monsoon rainfall can be predicted with lead times up to 10 months

Jun Meng, Jingfang Fan, Guanghao Ran
1 citations
Communications Earth & Environment
Climate variability and models
1.11
article

Tropical monsoon rainfall can be predicted with lead times up to 10 months

Jun Meng, Jingfang Fan, Guanghao Ran
article en
1 citations

Abstract

Tropical monsoons play a critical role in shaping regional and global climate systems, with profound ecological and socio-economic impacts. However, their long-term prediction remains challenging due to the complex interplay of regional dynamics, global climate drivers, large-scale teleconnections, and inherent non-stationarities in the climate system. Here, we introduce a unified network-based framework for predicting monsoon precipitation across diverse tropical regions. By leveraging global 2-meter air temperature fields, this approach captures large-scale climate teleconnections, such as the El Niño-Southern Oscillation and Rossby waves, enabling accurate forecasts for four key monsoon systems: the South American, East Asian, West African, and Indian monsoons. Our framework achieves remarkable forecasting accuracy with lead times of 4-10 months, outperforming traditional systems such as Seasonal Forecast System 5 and Climate Forecast System version 2. Beyond its predictive capabilities, the framework offers flexibility for application to other regions and climate phenomena, advancing our understanding of global climate dynamics. These findings have far-reaching implications for disaster preparedness, resource management, and sustainable development. Rainy season forecasts in tropical monsoon regions that incorporates largescale climate teleconnections, have higher predictive skills compared to traditional climate models and increase lead times between 4 and 10 months, according to a network-based unified forecasting system.

Communications Earth & EnvironmentVol. 6(1)
Hong Kong Baptist University (HK), Chinese Academy of Sciences (CN), Beijing Normal University (CN), Institute of Atmospheric Physics (CN), Potsdam Institute for Climate Impact Research (DE)
National Natural Science Foundation of China, Fundamental Research Funds for the Central Universities
Climate action
Openalex Percentile: Top 24%
Climate variability and models
1.11
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.