Compiling Magnetosheath Statistical Data Sets Under Specific Solar Wind Conditions: Lessons Learnt From the Dayside...

Area of Science:

• Space Physics and Geospace Science
• Plasma Physics
• Computational Modeling and Simulation

Background:

• The Geospace Environmental Modelling (GEM) community facilitates collaboration through challenges, often involving model-data comparisons.
• Statistical data analysis is vital for validating models and contextualizing observations, particularly in complex regions like the magnetosheath.
• Previous studies have highlighted challenges in data compilation for specific solar wind and Interplanetary Magnetic Field (IMF) conditions.

Purpose of the Study:

• To provide statistical context for compiling data for the southward IMF GEM challenge.
• To assess the impact of specific upstream conditions on statistical data compilation.
• To offer guidance for future model-data comparison studies and GEM challenges.

Main Methods:

• Analysis of data compilation strategies for the southward IMF GEM challenge.
• Investigation into the effects of imposing strict limits on solar wind parameters.
• Evaluation of the influence of defining IMF conditions, spacecraft selection, and region identification methods.

Main Results:

• Imposing strict limits on multiple solar wind parameters can significantly affect statistical data availability.
• The definition of specific IMF conditions, spacecraft choice, and region identification methods are critical factors.
• Balancing global statistical perspectives with the relevance to extreme individual events presents a significant challenge.

Conclusions:

• Future studies must carefully consider data availability in relation to upstream criteria early in the research process.
• Clear and consistent definitions for IMF conditions and regions of interest are essential for robust comparisons.
• The findings offer valuable lessons for conducting meaningful model-data comparisons in geospace science and space weather research.