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Space weather, including solar storms, can impact Earth by disturbing the geomagnetic field. Despite the known dependence of birds and other animals on geomagnetic cues for successful seasonal migrations, the potential effects of space weather on organisms that use Earth’s magnetic field for navigation have received little study. We tested whether space weather geomagnetic disturbances are associated with disruptions to bird migration at a macroecological scale. We leveraged long-term radar data to characterize the nightly migration dynamics of the nocturnally migrating North American avifauna over 22 y. We then used concurrent magnetometer data to develop a local magnetic disturbance index associated with each radar station (ΔBmax), facilitating spatiotemporally explicit analyses of the relationship between migration and geomagnetic disturbance. After controlling for effects of atmospheric weather and spatiotemporal patterns, we found a 9 to 17% decrease in migration intensity in both spring and fall during severe space weather events. During fall migration, we also found evidence for decreases in effort flying against the wind, which may represent a depression of active navigation such that birds drift more with the wind during geomagnetic disturbances. Effort flying against the wind in the fall was most reduced under both overcast conditions and high geomagnetic disturbance, suggesting that a combination of obscured celestial cues and magnetic disturbance may disrupt navigation. Collectively, our results provide evidence for community-wide avifaunal responses to geomagnetic disturbances driven by space weather during nocturnal migration.

We present a comprehensive statistical analysis of high‐frequency transient‐large‐amplitude (TLA) magnetic perturbation events that occurred at 12 high‐latitude ground magnetometer stations throughout Solar Cycle 24 from 2009 to 2019. TLA signatures are defined as one or more second‐timescale dB/dtinterval with magnitude ≥6 nT/s within an hour event window. This study characterizes high‐frequency TLA events based on their spatial and temporal behavior, relation to ring current activity, auroral substorms, and nighttime geomagnetic disturbance (GMD) events. We show that TLA events occur primarily at night, solely in the high‐latitude region above 60° geomagnetic latitude, and commonly within 30 min of substorm onsets. The largest TLA events occurred more often in the declining phase of the solar cycle when ring current activity was lower and solar wind velocity was higher, suggesting association to high‐speed streams caused by coronal holes and subsequent corotating interaction regions reaching Earth. TLA perturbations often occurred preceding or within the most extreme nighttime GMD events that have 5–10 min timescales, but the TLA intervals were often even more localized than the ∼300 km effective scale size of GMDs. We provide evidence that shows TLA‐related GMD events are associated with dipolarization fronts in the magnetotail and fast flows toward Earth and are closely temporally associated with poleward boundary intensifications (PBIs) and auroral streamers. The highly localized behavior and connection to the most extreme GMD events suggests that TLA intervals are a ground manifestation of features within rapid and complex ionospheric structures that can drive geomagnetically induced currents.

Dipolarizing flux bundles (DFBs) have been suggested to transport energy and momentum from regions of reconnection in the magnetotail to the high latitude ionosphere, where they can generate localized ionospheric currents that can produce large nighttime geomagnetic disturbances (GMDs). In this study we identified DFBs observed in the midnight sector from ∼7 to ∼10 R_Eby THEMIS A, D, and E during days in 2015–2017 whose northern hemisphere magnetic footpoints mapped to regions near Hudson Bay, Canada, and have compared them to isolated GMDs observed by ground magnetometers. We found 6 days during which one or more of these DFBs coincided to within ±3 min with ≥6 nT/s GMDs observed by latitudinally closely spaced ground‐based magnetometers located near those footpoints. Spherical elementary current systems (SECS) maps and all‐sky imager data provided further characterization of two events, showing short‐lived localized intense upward currents, auroral intensifications and/or streamers, and vortical perturbations of a westward electrojet. On all but one of these days the coincident DFB—GMD pairs occurred during intervals of high‐speed solar wind streams but low values of SYM/H. The observations reported here indicate that isolated DFBs generated under these conditions influence only limited spatial regions nearer Earth. In some events, in which the DFBs were observed closer to Earth and with lower Earthward velocities, the GMDs occurred slightly earlier than the DFBs, suggesting that braking had begun before the time of the DFB observation.

We present an automated method to identify high‐frequency geomagnetic disturbances in ground magnetometer data and classify the events by the source of the perturbations. We developed an algorithm to search for and identify changes in the surface magnetic field, dB/dt, with user‐specified amplitude and timescale. We used this algorithm to identify transient‐large‐amplitude (TLA) dB/dtevents that have timescale less than 60 s and amplitude >6 nT/s. Because these magnetic variations have similar amplitude and time characteristics to instrumental or man‐made noise, the algorithm identified a large number of noise‐type signatures as well as geophysical signatures. We manually classified these events by their sources (noise‐type or geophysical) and statistically characterized each type of event; the insights gained were used to more specifically define a TLA geophysical event and greatly reduce the number of noise‐type dB/dtidentified. Next, we implemented a support vector machine classification algorithm to classify the remaining events in order to further reduce the number of noise‐type dB/dtin the final data set. We examine the performance of our complete dB/dtsearch algorithm in widely used magnetometer databases and the effect of a common data processing technique on the results. The automated algorithm is a new technique to identify geomagnetic disturbances and instrumental or man‐made noise, enabling systematic identification and analysis of space weather related dB/dtevents and automated detection of magnetometer noise intervals in magnetic field databases.

We present a characterization of transient‐large‐amplitude (TLA) geomagnetic disturbances that are relevant to geomagnetically induced currents (GIC). TLA events are defined as one or more short‐timescale (<60 s) dB/dt signature with magnitude ≥6 nT/s. The TLA events occurred at six stations of the Magnetometer Array for Cusp and Cleft Studies throughout 2015. A semi‐automated dB/dt search algorithm was developed to identify 38 TLA events in the ground magnetometer data. While TLA dB/dts do not drive GICs directly, we show that second‐timescale dB/dts often occur in relation to or within larger impulsive geomagnetic disturbances. Sudden commencements are not the main driver, rather the events are more likely to occur 30 min after a substorm onset or within a nighttime magnetic perturbation event. The characteristics of TLA events suggest localized ionospheric source currents that may play a key role in generating some extreme geomagnetic impulses that can lead to GICs.