Thermal Deformation Correction for the FY-4A LMI

Affected by solar radiation in space, the FY-4A Lightning Mapping Imager (LMI) detection array exhibits daily periodic thermal expansion and contraction, leading to deviations in lightning positioning accuracy. While LMI’s detection efficiency is higher at night, the dual edge matching algorithm, which relies on surface features for correction, does not perform well during nighttime (around 3 pixels). Analysis shows that most of the lightning data corrected by this method exhibit significant deviations from the actual lightning locations in practical applications. Therefore, this paper proposes a new correction method based on high precision ground-based lightning location data from the 2019 summer World Wide Lightning Location Network (WWLLN) and the Beijing Broadband Lightning Network (BLNET). Using these datasets as reference standards, the periodic deviation of LMI is determined, and a correction curve is derived using a weighted Gaussian fitting approach. This method further improves the nighttime lightning location accuracy of LMI on the basis of the current operational algorithm. The results demonstrate that the corrected LMI data significantly reduces the positioning errors, with an accuracy within ±1 pixel in the Beijing area, as an example.

Authors

Institutions

Publication Details

Journal
Remote Sensing
Published
2026-01-04
DOI
https://doi.org/10.3390/rs18010163
Primary Topic
Lightning and Electromagnetic Phenomena
Type
article
Field-Weighted Citation Impact
0.00

Funders

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

Thermal Deformation Correction for the FY-4A LMI

D. Z. Wang, Shanfeng Yuan, Dongjie CAO, Jing Yang et al.
Remote Sensing
Lightning and Electromagnetic Phenomena
article

Thermal Deformation Correction for the FY-4A LMI

D. Z. Wang, Shanfeng Yuan, Dongjie CAO, Jing Yang, H. M. Zhang, X. Qie, Zhuling Sun, KeXin Zhu, R. X. Jiang, Dongxia Liu, Mingyuan Liu, Yuansheng Zhang
article en

Abstract

Affected by solar radiation in space, the FY-4A Lightning Mapping Imager (LMI) detection array exhibits daily periodic thermal expansion and contraction, leading to deviations in lightning positioning accuracy. While LMI’s detection efficiency is higher at night, the dual edge matching algorithm, which relies on surface features for correction, does not perform well during nighttime (around 3 pixels). Analysis shows that most of the lightning data corrected by this method exhibit significant deviations from the actual lightning locations in practical applications. Therefore, this paper proposes a new correction method based on high precision ground-based lightning location data from the 2019 summer World Wide Lightning Location Network (WWLLN) and the Beijing Broadband Lightning Network (BLNET). Using these datasets as reference standards, the periodic deviation of LMI is determined, and a correction curve is derived using a weighted Gaussian fitting approach. This method further improves the nighttime lightning location accuracy of LMI on the basis of the current operational algorithm. The results demonstrate that the corrected LMI data significantly reduces the positioning errors, with an accuracy within ±1 pixel in the Beijing area, as an example.

Remote SensingVol. 18(1)
China Meteorological Administration (CN), Chinese Academy of Sciences (CN), Institute of Atmospheric Physics (CN), University of Chinese Academy of Sciences (CN)
National Natural Science Foundation of China, Chinese Academy of Sciences
Sustainable cities and communities
Openalex Percentile: Top 94%
Lightning and Electromagnetic Phenomena
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.

Thermal Deformation Correction for the FY-4A LMI — D. Z. Wang, Shanfeng Yuan, et al. · Remote Sensing (2026) | TGRS Research Map | TGRS