We combine wavelet analysis and data fusion to investigate geomagnetically induced currents (GICs) on the Mäntsälä pipeline and the associated horizontal geomagnetic field, BH, variations during the late main phase of the 17 March 2013 geomagnetic storm. The wavelet analysis decomposes the GIC and BH signals at increasing ‘scales’ to show distinct multi-minute spectral features around the GIC spikes. Four GIC spikes > 10 A occurred while the pipeline was in the dusk sector – the first sine-wave-like spike at ~16 UT was ‘compound.’ It was followed by three ‘self-similar’ spikes two hours later. The contemporaneous multi-resolution observations from ground-(magnetometer, SuperMAG, SuperDARN), and space-based (AMPERE, TWINS) platforms capture multi-scale activity to reveal two magnetospheric modes causing the spikes. The GIC at ~16 UT occurred in two parts with the negative spike associated with a transient sub-auroral eastward electrojet that closed a developing partial ring current (PRC) loop, whereas the positive spike developed with the arrival of the associated mesoscale flow-channel in the auroral zone. The three spikes between 18-19 UT were due to bursty bulk flows (BBFs). We attribute all spikes to flow-channel injections (substorms) of varying scales. We use previously published MHD simulations of the event to substantiate our conclusions, given the dearth of timely in-situ satellite observations. Our results show that multi-scale magnetosphere-ionosphere activity that drives GICs can be understood using multi-resolution analysis. This new framework of combining wavelet analysis with multi-platform observations opens a research avenue for GIC investigations and other space weather impacts.

The monthly mean sunspot number has been larger in June-July 2023 than the double peak of solar cycle 24 (146 in February 2014 and 139 in November 2011) and brings us back to the sunspot level of solar cycle 23. However, the number of rocket launches, satellites in orbit and private space companies has increased dramatically in the past 20 years. Additionally, there is a growing interest for space exploration beyond Earth’s orbit, to the Moon and beyond, which comes with higher risk of being affected by space weather. Here, we discuss some of these trends and the role of the journal to improve awareness of space weather impacts.

A document by Bhagyashree Waghule. Click on the document to view its contents.

This editorial aims to improve awareness of the current best practices in open research, and stimulate discussion on the practical implementation of AGU's data and software policy in key areas of space weather research. We also further aim to encourage authors to take additional steps to ensure clear credit to all contributors to the work, whether that is underlying data, key software, or direct contributions to the manuscript.

The commercial sector of space science is thriving. Exciting examples come to mind more easily today than ever before, including commercial spaceflight and launches, ride shares for public-sector missions, and the deployment of countless satellites that support communications and human infrastructure. What may be surprising to some is the breadth and depth of the private sector contribution that goes beyond the largest, most high-profile examples. Companies, large and small, are doing fundamental science, and becoming high-quality data providers.

The next decadal survey process for space and solar physics will start soon with white papers due during the second half of 2022 and the committees and panels working over all of 2023. Space weather science and operations will play an essential role in this survey. Therefore, the community is invited to prepare white papers and get involved in advancing space weather research and capabilities in the upcoming decades. A summary of the recommendations related to space weather from the last two decadal surveys is also provided.

Science is fueled by data. Throughout history, scientists have operated sensors-from astronomical observatories to particle accelerators-that accumulate observations for analysis or to evaluate a hypothesis. However, as available technologies have increased both the volume of data and the efficiency of data storage and transmission, a new model of data access has emerged. The concept of a data buy is where an entity purchases access to a set of data or a data stream, instead of operating the sensors themselves. But why might a data consumer, whether a researcher or an end-user, prefer this kind of data access over the more traditional methods of running a network themselves? The simple answer, in some cases, is efficiency and, possibly, cost. Space weather forecasting and analysis has a growing private sector, and the extension to data gathering can be considered as a natural next step in the maturation of the field and the growing public-private partnerships. Operational applications require consistent, clean, and (in some cases) real-time data access that can be hard to support through the existing model of sensor deployment. Even in scientific applications, where access to raw information can be critical to discovery, there are benefits to the data buy model. Consistent access to a trusted data set allows more time to be spent on the scientific analysis, instead of maintaining machines that require consistent development, maintenance, and monitoring. The outsourcing of data infrastructure and pipelines can be particularly beneficial when the sensors are in distributed networks, spread over wide areas, and when there is a need to provide local data in observational gaps in existing networks. In the ideal case, a data buy can supplement the traditional observational networks in a beneficial and symbiotic way. It is important to note that data buys should not replace traditional observational networks, nor compete for funding with future observatories and infrastructure that the scientific community has deemed necessary (for example, through decadal survey processes).