Statistical Study of Rainfall Inversion Using the Earth-Space Link at the Ku Band: Optimization and Validation for 1 Year of Data

The large-scale monitoring of rainfall is of great significance in the research of meteorology, hydrology, and atmospheric measurement science. In recent years, with the quick development of communication satellite constellation, the use of earth-space link (ESL) to measure rainfall in the atmospher...

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Main Authors: Yingcheng Zhao, Xichuan Liu, Minghao Xian, Taichang Gao
Format: Article
Language:English
Published: IEEE 2021-01-01
Series:IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Subjects:
Online Access:https://ieeexplore.ieee.org/document/9534681/
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author Yingcheng Zhao
Xichuan Liu
Minghao Xian
Taichang Gao
author_facet Yingcheng Zhao
Xichuan Liu
Minghao Xian
Taichang Gao
author_sort Yingcheng Zhao
collection DOAJ
description The large-scale monitoring of rainfall is of great significance in the research of meteorology, hydrology, and atmospheric measurement science. In recent years, with the quick development of communication satellite constellation, the use of earth-space link (ESL) to measure rainfall in the atmosphere is expected to be a potential approach for the large-scale monitoring of global rainfall. In this article, to verify the long-term performance of rainfall measurement using ESL, the data of an ESL at the Ku band and a Thies Laser Precipitation Monitor (LPM) in Nanjing were collected. The rainfall inversion model using ESL was optimized according to the height of 0 °C-layer from the radiosonde data of ten years, and the inversion results in the different types of rainfall were discussed. The results show that the rainfall inversed by the optimized ESL model are in good agreement with the rainfall measured by LPM (correlative coefficient is 0.985), the relative errors of rain intensity inversed by ESL in light rain, moderate rain, heavy rain, and extreme rain are 20%, 15.17%, 8.93%, and 8.99%, respectively. The average relative errors of rain intensity measured by the ESL in convective rainfall and stratiform rainfall are 16.01% and 26.59%, respectively.
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spelling doaj.art-00fdcf48b6f14df38b1f3a32c891ac482022-12-21T19:29:40ZengIEEEIEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing2151-15352021-01-01149486949410.1109/JSTARS.2021.31113369534681Statistical Study of Rainfall Inversion Using the Earth-Space Link at the Ku Band: Optimization and Validation for 1 Year of DataYingcheng Zhao0https://orcid.org/0000-0002-3744-820XXichuan Liu1https://orcid.org/0000-0002-3393-3988Minghao Xian2https://orcid.org/0000-0003-2364-272XTaichang Gao3https://orcid.org/0000-0003-3629-1893College of Meteorology and Oceanography, National University of Defense Technology, Changsha, ChinaCollege of Meteorology and Oceanography, National University of Defense Technology, Changsha, ChinaCollege of Meteorology and Oceanography, National University of Defense Technology, Changsha, ChinaCollege of Meteorology and Oceanography, National University of Defense Technology, Changsha, ChinaThe large-scale monitoring of rainfall is of great significance in the research of meteorology, hydrology, and atmospheric measurement science. In recent years, with the quick development of communication satellite constellation, the use of earth-space link (ESL) to measure rainfall in the atmosphere is expected to be a potential approach for the large-scale monitoring of global rainfall. In this article, to verify the long-term performance of rainfall measurement using ESL, the data of an ESL at the Ku band and a Thies Laser Precipitation Monitor (LPM) in Nanjing were collected. The rainfall inversion model using ESL was optimized according to the height of 0 °C-layer from the radiosonde data of ten years, and the inversion results in the different types of rainfall were discussed. The results show that the rainfall inversed by the optimized ESL model are in good agreement with the rainfall measured by LPM (correlative coefficient is 0.985), the relative errors of rain intensity inversed by ESL in light rain, moderate rain, heavy rain, and extreme rain are 20%, 15.17%, 8.93%, and 8.99%, respectively. The average relative errors of rain intensity measured by the ESL in convective rainfall and stratiform rainfall are 16.01% and 26.59%, respectively.https://ieeexplore.ieee.org/document/9534681/Earth-space link (ESL)long-term performancerainfall attenuationrainfall inversionstatistical analysis
spellingShingle Yingcheng Zhao
Xichuan Liu
Minghao Xian
Taichang Gao
Statistical Study of Rainfall Inversion Using the Earth-Space Link at the Ku Band: Optimization and Validation for 1 Year of Data
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Earth-space link (ESL)
long-term performance
rainfall attenuation
rainfall inversion
statistical analysis
title Statistical Study of Rainfall Inversion Using the Earth-Space Link at the Ku Band: Optimization and Validation for 1 Year of Data
title_full Statistical Study of Rainfall Inversion Using the Earth-Space Link at the Ku Band: Optimization and Validation for 1 Year of Data
title_fullStr Statistical Study of Rainfall Inversion Using the Earth-Space Link at the Ku Band: Optimization and Validation for 1 Year of Data
title_full_unstemmed Statistical Study of Rainfall Inversion Using the Earth-Space Link at the Ku Band: Optimization and Validation for 1 Year of Data
title_short Statistical Study of Rainfall Inversion Using the Earth-Space Link at the Ku Band: Optimization and Validation for 1 Year of Data
title_sort statistical study of rainfall inversion using the earth space link at the ku band optimization and validation for 1 year of data
topic Earth-space link (ESL)
long-term performance
rainfall attenuation
rainfall inversion
statistical analysis
url https://ieeexplore.ieee.org/document/9534681/
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AT minghaoxian statisticalstudyofrainfallinversionusingtheearthspacelinkatthekubandoptimizationandvalidationfor1yearofdata
AT taichanggao statisticalstudyofrainfallinversionusingtheearthspacelinkatthekubandoptimizationandvalidationfor1yearofdata