About the project


A cartoon of the Earth's magnetosphere. The Dst or disturbance-storm-time index is a measure of the “ring current” (blue) around the Earth. The ring current is an electric current carried by charged particles trapped in the magnetosphere.

Project background

The efficient transfer of energy from solar-wind into the Earth’s magnetic field causes geomagnetic storms. The resulting ground magnetic field variations increase the errors of systems that use Earth’s natural magnetic field as a pointing reference.

The Dst or disturbance-storm-time index is a measure of the severity of the geomagnetic storm. More specifically, the negative deflection of the Earth's magnetic field due to the ring current (see the above figure) is measured by the Dst index. As a key specification of the magnetospheric dynamics, the Dst index is used to drive geomagnetic disturbance models such as NOAA/NCEI’s High Definition Geomagnetic Model - Real Time (HDGM-RT). Additionally, magnetic surveyors, government agencies, academic institutions, satellite operators, and power grid operators use the Dst index to analyze the strength and duration of geomagnetic storms.

The Dst is calculated as an average deflection of the horizontal component of the magnetic field observed at four near-equatorial ground observatories. The more intense the geomagnetic storm is, the more negative the Dst value becomes. However, the observatory-based Dst values are not very useful for the real-time magnetic modeling due to latency, instrument outages and connectivity issues. Over the past four decades, several models were proposed for solar-wind forecasting of Dst. Here, instead of relying on ground measurements, models predict the Dst values solely based on solar-wind measurements by satellites such as NOAA’s Deep Space Climate Observatory (DSCOVR) or NASA's Advanced Composition Explorer (ACE), situated approximately 1.6 million kilometers away from Earth along the Sun-Earth line. Since radio communication is faster than the solar wind, the satellite measurements at L1 provide 15-30 minutes of lead-time before the storm arrives on Earth.

The NOAA’s National Centers for Environmental Information (NCEI), in partnership with the University of Colorado’s Cooperative Institute for Research in Environmental Sciences (CIRES) is conducting an open data-science challenge to forecast Dst using the real-time solar-wind (RTSW) data in an operationally viable setup. Recent advances in machine learning research hold immediate promise for improving Dst forecasting even without formal training in space physics. The right challenge in this context can identify solutions that are both operationally viable and highly accurate.


NOAA's National Centers for Environmental Information (NCEI) hosts and provides public access to one of the most significant archives for environmental data on Earth. NCEI contributes to the NESDIS mission by developing new products and services that span the science disciplines and enable better data discovery.

At the Cooperative Institute for Research In Environmental Sciences (CIRES), more than 800 environmental scientists work to understand the dynamic Earth system, including people’s relationship with the planet. CIRES is a partnership of NOAA and the University of Colorado Boulder, and its areas of expertise include weather and climate, changes at Earth’s poles, air quality and atmospheric chemistry, water resources, and solid Earth sciences. The vision at CIRES is to be instrumental in ensuring a sustainable future environment by advancing scientific and societal understanding of the Earth system.

Additional resources