Detecting heavy rainfall using anomaly-based percentile thresholds of predictors derived from GNSS-PWV-Reference-Cited by-同舟云学术

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Detecting heavy rainfall using anomaly-based percentile thresholds of predictors derived from GNSS-PWV

Published:2022-01 Issue: Volume:265 Page:105912
ISSN:0169-8095
Container-title:Atmospheric Research
language:en
Short-container-title:Atmospheric Research

Author:

Li Haobo,Wang Xiaoming,Choy Suelynn,Jiang Chenhui,Wu Suqin,Zhang Jinglei,Qiu Cong,Zhou Kai,Li Li,Fu Erjiang,Zhang Kefei

Funder

National Natural Science Foundation of China

Publisher

Elsevier BV

Subject

Atmospheric Science

Reference82 articles.

1. Estimation of tropospheric delay for microwaves from surface weather data;Askne;Radio Sci.,1987

2. Ground-based GPS water vapour estimation: potential for meteorological forecasting;Baker;J. Atmos. Sol.-Terr. Phy.,2001

3. Detection of water vapor time variations associated with heavy rain in northern Italy by geodetic and low-cost GNSS receivers;Barindelli;Earth Planets Space.,2018

4. On the inclusion of GPS precipitable water vapour in the nowcasting of rainfall;Benevides;Nat. Hazard Earth Syst.,2015

5. Neural network approach to forecast hourly intense rainfall using GNSS precipitable water vapor and meteorological sensors;Benevides;Remote Sens.,2019

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3. A GRNN-Based Model for ERA5 PWV Adjustment with GNSS Observations Considering Seasonal and Geographic Variations;Remote Sensing;2024-07-01

4. Revealing the water vapor transport during the Henan “7.20” heavy rainstorm based on ERA5 and Real-Time GNSS;The Egyptian Journal of Remote Sensing and Space Sciences;2024-06

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