Assimilation of 5G Base Station Networks as Ultra‐Dense Atmospheric Sensors for Advancing Heavy Rainfall Prediction

Abstract The zenith total delay (ZTD) retrieved from 5G communication base stations represents a novel observation source for numerical weather prediction (NWP), leveraging the extensive global deployment of 5G infrastructure. In this study, the direct assimilation of 5G‐ZTD observations into a high‐resolution NWP system was accomplished for the first time. Two precipitation events were selected to evaluate the impact of 5G‐ZTD assimilation on short‐term precipitation forecasting. Assimilating 5G‐ZTD data corrected the dry bias in the initial water vapor field and improved precipitation forecasts in both cases, demonstrating its practical utility for short‐term heavy rainfall forecasts and operational potential given its low cost and extensive coverage.

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Publication Details

Journal
Geophysical Research Letters
Published
2026-10-14
DOI
https://doi.org/10.1029/2026gl124477
Primary Topic
Meteorological Phenomena and Simulations
Type
article
Field-Weighted Citation Impact
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article

Assimilation of 5G Base Station Networks as Ultra‐Dense Atmospheric Sensors for Advancing Heavy Rainfall Prediction

王科钻, Dengjie Huang, Xiefei Zhi, Hong Yan Liang et al.
Geophysical Research Letters
Meteorological Phenomena and Simulations
article

Assimilation of 5G Base Station Networks as Ultra‐Dense Atmospheric Sensors for Advancing Heavy Rainfall Prediction

王科钻, Dengjie Huang, Xiefei Zhi, Hong Yan Liang, Jian Yin, Chunqing Shang
article en

Abstract

Abstract The zenith total delay (ZTD) retrieved from 5G communication base stations represents a novel observation source for numerical weather prediction (NWP), leveraging the extensive global deployment of 5G infrastructure. In this study, the direct assimilation of 5G‐ZTD observations into a high‐resolution NWP system was accomplished for the first time. Two precipitation events were selected to evaluate the impact of 5G‐ZTD assimilation on short‐term precipitation forecasting. Assimilating 5G‐ZTD data corrected the dry bias in the initial water vapor field and improved precipitation forecasts in both cases, demonstrating its practical utility for short‐term heavy rainfall forecasts and operational potential given its low cost and extensive coverage.

Geophysical Research LettersVol. 53(20)
China Meteorological Administration (CN), Shenzhen Metro (China) (CN), Shenzhen Bay Laboratory (CN), Zhejiang Institute of Communications (CN), China Communications Construction Company (China) (CN), Institute of Urban Meteorology (CN)
Climate action, Industry, innovation and infrastructure
Openalex Percentile: Top 21%
Meteorological Phenomena and Simulations
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