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1. Numerical Simulations of the Geospace Response to the Arrival of an Idealized Perfect Interplanetary Coronal Mass Ejection

   https://doi.org/10.1029/2020SW002489  

   Welling, Daniel T. ; Love, Jeffrey J. ; Rigler, E. Joshua ; Oliveira, Denny M. ; Komar, Colin M. ; Morley, Steven K. ( February 2021 , Space Weather)

   Previously, Tsurutani and Lakhina (2014,https://doi.org/10.1002/2013GL058825) created estimates for a “perfect” interplanetary coronal mass ejection and performed simple calculations for the response of geospace, including. In this study, these estimates are used to drive a coupled magnetohydrodynamic‐ring current‐ionosphere model of geospace to obtain more physically accurate estimates of the geospace response to such an event. The sudden impulse phase is examined and compared to the estimations of Tsurutani and Lakhina (2014,https://doi.org/10.1002/2013GL058825). The physics‐based simulation yields similar estimates for Dst rise, magnetopause compression, and equatorialvalues as the previous study. However, results diverge away from the equator.values in excess of 30 nT/s are found as low asmagnetic latitude. Under southward interplanetary magnetic field conditions, magnetopause erosion combines with strong region one Birkeland currents to intensify theresponse. Values obtained here surpass those found in historically recorded events and set the upper threshold of extreme geomagnetically induced current activity at Earth.

    

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2. A Daily Determination of B Z Using the Russell‐McPherron Effect to Forecast Geomagnetic Activity

   https://doi.org/10.1029/2018SW002098  

   Jackson, B. V. ; Yu, H. ‐S. ; Buffington, A. ; Hick, P. P. ; Tokumaru, M. ; Fujiki, K. ; Kim, J. ; Yun, J. ( April 2019 , Space Weather)

   Since the middle of the last decade, UCSD has incorporated magnetic field data in its Institute for Space‐Earth Environmental Research interplanetary scintillation tomographic analysis. These data are extrapolated upward from the solar surface using the Current Sheet Source Surface model (Zhao & Hoeksema, 1995,https://doi.org/10.1029/94JA02266) to provide predictions of the interplanetary field in RTN coordinates. Over the years this technique has become ever more sophisticated, and allows different types of magnetogram data (SOLIS, Global Oscillation Network Group, etc.,) to be incorporated in the field extrapolations. At Earth, these fields can be displayed in a variety of ways, including Geocentric Solar Magnetospheric (GSM) B_x, B_y, and B_zcoordinates. Displayed daily, the Current Sheet Source Surface model‐derived GSM B_zshows a significant positive correlation with the low‐resolution (few day variation) in situ measurements of the B_zfield. The nano‐Tesla variations of B_zmaximize in spring and fall as Russell and McPherron (1973,https://doi.org/10.1029/JA078i001p00092) have shown. More significantly, we find that the daily variations are correlated with geomagnetic Kp and Dst index variations, and that a decrease from positive to negative B_zhas a high correlation with minor‐to‐moderate geomagnetic storm activity, as defined by NOAA Space Weather Prediction Center planetary Kp values. Here we provide an 11‐year study of the predicted B_zfield, from the extrapolation of the Global Oscillation Network Group‐magnetograms. We provide a skill‐score analysis of the technique's geomagnetic storm prediction capability, which allows forecasts of moderate enhanced geomagnetic storm activity. UCSD and the Korean Space Weather Center currently operate a website that predicts this low‐resolution GSM B_zfield component variation several days in advance.

    

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3. Solar Flare Intensity Prediction With Machine Learning Models

   https://doi.org/10.1029/2020SW002440  

   Jiao, Zhenbang ; Sun, Hu ; Wang, Xiantong ; Manchester, Ward ; Gombosi, Tamas ; Hero, Alfred ; Chen, Yang ( July 2020 , Space Weather)

   We develop a mixed long short‐term memory (LSTM) regression model to predict the maximum solar flare intensity within a 24‐hr time window 0–24, 6–30, 12–36, and 24–48 hr ahead of time using 6, 12, 24, and 48 hr of data (predictors) for each Helioseismic and Magnetic Imager (HMI) Active Region Patch (HARP). The model makes use of (1) the Space‐Weather HMI Active Region Patch (SHARP) parameters as predictors and (2) the exact flare intensities instead of class labels recorded in the Geostationary Operational Environmental Satellites (GOES) data set, which serves as the source of the response variables. Compared to solar flare classification, the model offers us more detailed information about the exact maximum flux level, that is, intensity, for each occurrence of a flare. We also consider classification models built on top of the regression model and obtain better results in solar flare classifications as compared to Chen et al. (2019,https://doi.org/10.1029/2019SW002214). Our results suggest that the most efficient time period for predicting the solar activity is within 24 hr before the prediction time using the SHARP parameters and the LSTM model.

    

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4. External and Internal Causes of the Stormtime Intensification of the Dawnside Westward Auroral Electrojet

   https://doi.org/10.1029/2023JA031457  

   Ohtani, S. ; Sorathia, K. ; Merkin, V. G. ; Frey, H. U. ; Gjerloev, J. W. ( October 2023 , Journal of Geophysical Research: Space Physics)

   The dawn‐dusk asymmetry of magnetic depression is a characteristic feature of the storm main phase. Recently Ohtani (2021,https://doi.org/10.1029/2021JA029643) reported that its magnitude is correlated with the dawnside westward auroral electrojet (AEJ) intensity, and suggested that the dawnside AEJ intensification is a fundamental process of the stormtime magnetosphere‐ionosphere coupling. In this study we observationally address the cause of the dawnside AEJ intensification in terms of four scenarios. That is, the dawnside AEJ intensifies because (a) the external driving of global convection strengthens, (b) solar wind compression enhances energetic electron precipitation, and therefore, ionospheric conductance, through wave‐particle interaction, (c) the substorm current wedge forms in the dawn sector, and (d) energetic electrons injected by nightside substorms drift dawnward, and the subsequent precipitation enhances ionospheric conductance. We find an event that fits each scenario, and therefore, none of these scenarios can be precluded. However, the result of a superposed epoch analysis shows that some causes are more prevalent than others. More specifically, (a) although the enhancement of external driving may precondition the dawnside AEJ intensification, it is rarely the direct cause; (b) external compression probably explains only a small fraction of the events; (c) prior to the dawnside AEJ intensification, the westward AEJ tends to intensify in the midnight sector along with mid‐latitude positive bays, which suggests that the substorm injection of energetic electrons is the most prevalent cause. This last result may also be explained by the dawnside expansion of the substorm current wedge, which, however, is arguably far less common.

    

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5. Understanding the Origins of Problem Geomagnetic Storms Associated with “Stealth” Coronal Mass Ejections

   https://doi.org/10.1007/s11214-021-00857-0  

   Nitta, Nariaki V. ; Mulligan, Tamitha ; Kilpua, Emilia K. J. ; Lynch, Benjamin J. ; Mierla, Marilena ; O’Kane, Jennifer ; Pagano, Paolo ; Palmerio, Erika ; Pomoell, Jens ; Richardson, Ian G. ; et al ( November 2021 , Space Science Reviews)

   Geomagnetic storms are an important aspect of space weather and can result in significant impacts on space- and ground-based assets. The majority of strong storms are associated with the passage of interplanetary coronal mass ejections (ICMEs) in the near-Earth environment. In many cases, these ICMEs can be traced back unambiguously to a specific coronal mass ejection (CME) and solar activity on the frontside of the Sun. Hence, predicting the arrival of ICMEs at Earth from routine observations of CMEs and solar activity currently makes a major contribution to the forecasting of geomagnetic storms. However, it is clear that some ICMEs, which may also cause enhanced geomagnetic activity, cannot be traced back to an observed CME, or, if the CME is identified, its origin may be elusive or ambiguous in coronal images. Such CMEs have been termed “stealth CMEs”. In this review, we focus on these “problem” geomagnetic storms in the sense that the solar/CME precursors are enigmatic and stealthy. We start by reviewing evidence for stealth CMEs discussed in past studies. We then identify several moderate to strong geomagnetic storms (minimum Dst$< -50$$<-50$ nT) in solar cycle 24 for which the related solar sources and/or CMEs are unclear and apparently stealthy. We discuss the solar and in situ circumstances of these events and identify several scenarios that may account for their elusive solar signatures. These range from observational limitations (e.g., a coronagraph near Earth may not detect an incoming CME if it is diffuse and not wide enough) to the possibility that there is a class of mass ejections from the Sun that have only weak or hard-to-observe coronal signatures. In particular, some of these sources are only clearly revealed by considering the evolution of coronal structures over longer time intervals than is usually considered. We also review a variety of numerical modelling approaches that attempt to advance our understanding of the origins and consequences of stealthy solar eruptions with geoeffective potential. Specifically, we discuss magnetofrictional modelling of the energisation of stealth CME source regions and magnetohydrodynamic modelling of the physical processes that generate stealth CME or CME-like eruptions, typically from higher altitudes in the solar corona than CMEs from active regions or extended filament channels.

    

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