Martin Archer ^1* Xueling Shi ^2,3 Maria-Theresia Walach ⁴ Michael Hartinger ^5,6 D M. Gillies ⁷ Simone Di Matteo ^8,9 Frances Staples ⁶ Katariina Nykyri ⁸

• ¹ Imperial College London, London, United Kingdom
• ² Virginia Tech, Blacksburg, Virginia, United States
• ³ National Center for Atmospheric Research (UCAR), Boulder, Colorado, United States
• ⁴ Lancaster University, Lancaster, England, United Kingdom
• ⁵ Space Science Institute (SSI), Boulder, Colorado, United States
• ⁶ University of California, Los Angeles, Los Angeles, California, United States
• ⁷ University of Calgary, Calgary, Alberta, Canada
• ⁸ Heliophysics Science Division, NASA Goddard Space Flight Center, Greenbelt, Maryland, United States
• ⁹ The Catholic University of America, Washington, D.C., District of Columbia, United States

The dynamics of Earth's magnetopause, driven by several different external/internal physical processes, plays a major role in the geospace energy budget. Given magnetopause motion couples across many space plasma regions, numerous forms of observations may provide valuable information in understanding these dynamics and their impacts. \textit{In-situ} multi-point spacecraft measurements measure the local plasma environment, dynamics and processes; with upcoming swarms providing the possibility of improved spatiotemporal reconstruction of dynamical phenomena, and multi-mission conjunctions advancing understanding of the ``mesoscale'' coupling across the geospace ``system of systems''. Soft X-ray imaging of the magnetopause should enable boundary motion to be directly remote sensed for the first time. Indirect remote sensing capabilities might be enabled through the field-aligned currents associated with disturbances to the magnetopause; by harnessing data from satellite mega-constellations in low-Earth orbit, and taking advantage of upgraded auroral imaging and ionospheric radar technology. Finally, increased numbers of closely-spaced ground magnetometers in both hemispheres may help discriminate between high-latitude processes in what has previously been a ``zone of confusion''. Bringing together these multiple modes of observations for studying magnetopause dynamics is crucial. These may also be aided by advanced data processing techniques, such as physics-based inversions and machine learning methods, along with comparisons to increasingly sophisticated geospace assimilative models and simulations.