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Compiling Magnetosheath Statistical Data Sets Under Specific Solar Wind Conditions: Lessons Learnt From the Dayside Kinetic Southward IMF GEM Challenge
DOI: 10.1029/2020EA001095 Bibcode: 2020E&SS....701095D

Dimmock, A. P.; Hietala, H.; Zou, Y.

The Geospace Environmental Modelling (GEM) community offers a framework for collaborations between modelers, observers, and theoreticians in the form of regular challenges. In many cases, these challenges involve model-data comparisons to provide wider context to observations or validate model results. To perform meaningful comparisons, a statisti…

2020 Earth and Space Science
Cluster 9
Open-Source Software Analysis Tool to Investigate Space Plasma Turbulence and Nonlinear DYNamics (ODYN)
DOI: 10.1029/2019EA001004 Bibcode: 2020E&SS....701004T

Echim, M. M.; Teodorescu, E.

We have designed and built a versatile modularized software library—ODYN—that wraps a comprehensive set of advanced data analysis methods meant to facilitate the study of turbulence, nonlinear dynamics, and complexity in space plasmas. The Python programming language is used for the algorithmic implementation of models and methods devised to under…

2020 Earth and Space Science
Cluster Ulysses 6
Robust Adaptive Spacecraft Array Derivative Analysis
DOI: 10.1029/2019EA000953 Bibcode: 2020E&SS....700953V

Vogt, J.; Blagau, A.; Pick, L.

Multispacecraft missions such as Cluster, Themis, Swarm, and MMS contribute to the exploration of geospace with their capability to produce gradient and curl estimates from sets of spatially distributed in situ measurements. This paper combines all existing estimators of the reciprocal vector family for spatial derivatives and their errors. The re…

2020 Earth and Space Science
Cluster 4