Seasonal Variation of the Martian Dayside Ionosphere

Abstract The Martian ionosphere has many similarities and differences compared to Earth, attracting significant attention. This paper utilizes radio occultation data from the Mars Global Surveyor (MGS), Mars Atmosphere and Volatile Evolution Mission (MAVEN), and ESA Mars Express mission (MEX), associated with the measurements from Mars Advanced Radar for Subsurface and Ionosphere Sounding (MARSIS) aboard MEX, to investigate the seasonal variation of the Martian dayside ionosphere. Data preprocessing is performed first to isolate the influence of solar zenith angle and solar radiation, the seasonal variation of the Martian dayside ionosphere explored in this study. The results suggest that the peak electron density reaches its minimum and maximum at LS = 70.2° and LS = 250.2°, respectively, with an amplitude of 16.5% concerning the average (LS is referred to as the solar longitude of Mars). The peak altitude experiences its minimum at LS = 78.4° and maximum at LS = 258.4°, and its relative amplitude is 12.1%. The outcomes suggest that the seasonal variations in the Martian ionosphere are primarily attributed to the Mars‐Sun distance change, which is different from the situation on Earth. This study will benefit both Martian ionosphere modeling and Earth’s ionosphere understanding in the future.

Authors

Institutions

Publication Details

Journal
Journal of Geophysical Research Space Physics
Published
2024-10-01
DOI
https://doi.org/10.1029/2024ja032794
Primary Topic
Planetary Science and Exploration
Type
article
Field-Weighted Citation Impact
0.00

Funders

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

Seasonal Variation of the Martian Dayside Ionosphere

Haibing Ruan, Haohui Zhai
Journal of Geophysical Research Space Physics
Planetary Science and Exploration
article

Seasonal Variation of the Martian Dayside Ionosphere

Haibing Ruan, Haohui Zhai
article en

Abstract

Abstract The Martian ionosphere has many similarities and differences compared to Earth, attracting significant attention. This paper utilizes radio occultation data from the Mars Global Surveyor (MGS), Mars Atmosphere and Volatile Evolution Mission (MAVEN), and ESA Mars Express mission (MEX), associated with the measurements from Mars Advanced Radar for Subsurface and Ionosphere Sounding (MARSIS) aboard MEX, to investigate the seasonal variation of the Martian dayside ionosphere. Data preprocessing is performed first to isolate the influence of solar zenith angle and solar radiation, the seasonal variation of the Martian dayside ionosphere explored in this study. The results suggest that the peak electron density reaches its minimum and maximum at LS = 70.2° and LS = 250.2°, respectively, with an amplitude of 16.5% concerning the average (LS is referred to as the solar longitude of Mars). The peak altitude experiences its minimum at LS = 78.4° and maximum at LS = 258.4°, and its relative amplitude is 12.1%. The outcomes suggest that the seasonal variations in the Martian ionosphere are primarily attributed to the Mars‐Sun distance change, which is different from the situation on Earth. This study will benefit both Martian ionosphere modeling and Earth’s ionosphere understanding in the future.

Journal of Geophysical Research Space PhysicsVol. 129(10)
Chinese Academy of Sciences (CN), Nanjing University of Information Science and Technology (CN), Chinese Academy of Meteorological Sciences (CN)
National Natural Science Foundation of China, National Key Research and Development Program of China
Life below water
Openalex Percentile: Top 87%
Planetary Science and Exploration
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.