5G基站网络同化作为超密集大气传感器用于推进强降雨预报

IF 5 1区地球科学 Q1 GEOSCIENCES, MULTIDISCIPLINARY

Geophysical Research Letters Pub Date : 2026-10-14 DOI:10.1029/2026gl124477

Jian Yin,Xiefei Zhi,Danni Huang,Chunqing Shang,Hong Liang,Kezuan Wang

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引用次数: 0

摘要

利用5G基础设施的广泛全球部署，从5G通信基站获取的天顶总延迟（ZTD）为数值天气预报（NWP）提供了一种新的观测源。在这项研究中，首次实现了5G - ZTD观测到高分辨率NWP系统的直接同化。选择两个降水事件来评估5G - ZTD同化对短期降水预报的影响。同化5G - ZTD数据纠正了初始水汽场的干燥偏差，并改善了两种情况下的降水预报，证明了其在短期强降雨预报中的实用性，以及其低成本和广泛覆盖范围的业务潜力。

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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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来源期刊

Geophysical Research Letters 地学-地球科学综合

CiteScore

9.00

自引率

9.60%

发文量

1588

审稿时长

2.2 months

期刊介绍： Geophysical Research Letters (GRL) publishes high-impact, innovative, and timely research on major scientific advances in all the major geoscience disciplines. Papers are communications-length articles and should have broad and immediate implications in their discipline or across the geosciences. GRLmaintains the fastest turn-around of all high-impact publications in the geosciences and works closely with authors to ensure broad visibility of top papers.