Eligible research projects must involve the interdisciplinary analysis and evaluation of space mission data. They may also draw on complementary ground-based data and/or theoretical modelling where this adds scientific value.
This call is open to all scientists, regardless of nationality or institutional affiliation, who are actively involved in any of the following research fields:
A research team brought together by ISSI has made significant strides in solving a key question in space physics: how ultra-low frequency (ULF) waves generated in Earth’s foreshock region transmit into the magnetosphere, influencing space weather around our planet.
Plasma environments across the universe are often separated by sharp boundaries that are in almost constant wave-like motion, like waves on water or the vibrations of a drum. These surface waves play a crucial role in regulating how energy passes through the boundaries, making their role in responding to external forces critically important for universal applications. A series of new papers from ISSI Team #546 outlines future directions for advancing our understanding of surface waves within the natural laboratory of Earth’s magnetosphere and beyond.
New Nature study by ISSI & ISSI-Beijing Team uncovers unexpected interaction between Mars and the solar wind.
The Earth’s magnetosphere shields our planet from hazardous space weather effects caused by solar disturbances and energetic particles. However, the global structure of the magnetosphere is still extremely difficult to describe. Major challenges include the scarcity of data sets, as well as the breadth of physical processes that need to be taken into account. Our ISSI Team explores various approaches that help to mitigate these challenges. Recent publications from our ISSI Team provide new insights into how to extract information about global magnetospheric and ionospheric structures, and how to combine global data analysis and global modeling in meaningful ways. The new results suggest potentially transformative ways to work with global datasets, develop new global models, and improve the accuracy of the current global models.
