State of the Art of Martian Weather–Climate Modeling and Open Challenges

Mars climatology is a growing interest domain for planetary research and for operational missions. In the last three decades, Martian General Circulation Models have been developed to support the interpretation of spacecraft and telescopic observations and for the advancement of theoretical understanding of the climate. They have been designed to represent key processes, such as dust cycle, seasonal CO2 condensation, and interaction between boundary layer and surface. At the same time, new observations from orbiters and landers have enhanced the diagnostics, but several uncertainties in the parameterization, especially in dust representation and turbulent mixing, require further improvements. This review represents a synthesis of the state of the art of existing global and regional models, comparing numerical and physical approaches, identifying the main challenges for the next years, with particular attention to the needs of operational missions and machine learning techniques.

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Publication Details

Journal
Atmosphere
Published
2026-05-18
DOI
https://doi.org/10.3390/atmos17050514
Primary Topic
Planetary Science and Exploration
Type
article
Field-Weighted Citation Impact
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article

State of the Art of Martian Weather–Climate Modeling and Open Challenges

Atmosphere
Planetary Science and Exploration
article

State of the Art of Martian Weather–Climate Modeling and Open Challenges

article en

Abstract

Mars climatology is a growing interest domain for planetary research and for operational missions. In the last three decades, Martian General Circulation Models have been developed to support the interpretation of spacecraft and telescopic observations and for the advancement of theoretical understanding of the climate. They have been designed to represent key processes, such as dust cycle, seasonal CO2 condensation, and interaction between boundary layer and surface. At the same time, new observations from orbiters and landers have enhanced the diagnostics, but several uncertainties in the parameterization, especially in dust representation and turbulent mixing, require further improvements. This review represents a synthesis of the state of the art of existing global and regional models, comparing numerical and physical approaches, identifying the main challenges for the next years, with particular attention to the needs of operational missions and machine learning techniques.

AtmosphereVol. 17(5)
Italian Aerospace Research Centre (IT)
Climate action
Openalex Percentile: Top 5%
Planetary Science and Exploration
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