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Abstract Reconnection at Earth's magnetopause drives magnetospheric convection and provides mass and energy input into the magnetosphere/ionosphere system thereby driving the coupling between solar wind and terrestrial magnetosphere. Despite its importance, the factors governing the location of dayside magnetopause reconnection are not well understood. Though a few models can predict X‐line locations reasonably well, the underlying physics is still unresolved. In this study we present results from a comparative analysis of 274 magnetic reconnection events as observed by the Magnetospheric Multiscale (MMS) mission to determine what quantities affect the accuracy of such models and are most strongly associated with the occurrence of dayside magnetopause reconnection. We also attempt to determine under what upstream solar wind conditions each global X‐line model becomes least reliable. 

Unlike the vast majority of astrophysical plasmas, the solar wind is accessible to spacecraft, which for decades have carried in-situ instruments for directly measuring its particles and fields. Though such measurements provide precise and detailed information, a single spacecraft on its own cannot disentangle spatial and temporal fluctuations. Even a modest constellation of in-situ spacecraft, though capable of characterizing fluctuations at one or more scales, cannot fully determine the plasma’s 3-D structure. We describe here a concept for a new mission, the Magnetic Topology Reconstruction Explorer (MagneToRE), that would comprise a large constellation of in-situ spacecraft and would, for the first time, enable 3-D maps to be reconstructed of the solar wind’s dynamic magnetic structure. Each of these nanosatellites would be based on the CubeSat form-factor and carry a compact fluxgate magnetometer. A larger spacecraft would deploy these smaller ones and also serve as their telemetry link to the ground and as a host for ancillary scientific instruments. Such an ambitious mission would be feasible under typical funding constraints thanks to advances in the miniaturization of spacecraft and instruments and breakthroughs in data science and machine learning.