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Modern civilization relies on a complex, globally interconnected industrial agriculture system to produce food. Its unprecedented yields hinge on external inputs like machinery, fertilizers, and pesticides, rendering it vulnerable to disruptions in production and international trade. Such a disruption could be caused by large‐scale damage to the electrical grid. Solar storms, nuclear detonations in the upper atmosphere, pandemics, or cyber‐attacks, could cause this severe damage to electrical infrastructure. To assess the impact of such a global catastrophic infrastructure loss on major food crops (corn, rice, soybean, wheat), we employ a generalized linear model. The predictions show a crop‐specific yield reduction between 15% and 37% in phase 1, the year after the catastrophe, assuming rationed use of fertilizers, pesticides, and fuel stocks. In phase 2, when all stocks are depleted, yields decrease by 35%–48%. Soybean is less affected in phase 1, while all crops experience strong declines in phase 2. Europe, North and South America, and parts of India, China, and Indonesia face major yield reductions, potentially up to 75%, while most African countries are less affected. These findings underscore the necessity for preparation by highlighting the vulnerability of the food system. [ABSTRACT FROM AUTHOR]

Under nominal solar wind conditions, a tenuous wake forms downstream of the lunar nightside. However, the lunar plasma environment undergoes a transformation as the Moon passes through the Earth's magnetotail, with hot subsonic plasma causing the wake structure to disappear. We investigate the lunar wake response during a passing coronal mass ejection (CME) on March 8, 2012 while crossing the Earth's magnetotail using both a magnetohydrodynamic (MHD) model of the terrestrial magnetosphere and a three‐dimensional hybrid plasma model of the lunar wake. The CME arrives at 1 AU around 10:30 UT and its impact is first detected inside the geomagnetic tail after 11:10 UT by the Acceleration, Reconnection, Turbulence and Electrodynamics of the Moon's Interaction with the Sun (THEMIS‐ARTEMIS) satellites in lunar orbit. A global magnetospheric MHD simulation using Wind data for upstream conditions with the OpenGGCM model reveals the magnetosheath compression to the lunar position from 11:20–12:00 UT, accompanied by multiple flux rope or plasmoid‐like features developing and propagating tailward. MHD results support plasma changes observed by the THEMIS‐ARTEMIS satellites. Lunar‐scale simulations using the Amitis hybrid code show a short and misaligned plasma wake during the Moon's brief entry into the magnetosheath at 11:20 UT, with plasma expansion into the void being aided by the higher plasma temperatures. Sharply accelerated flow speed and a compressed magnetic field lead to an enhanced electric field in the lunar wake capable of generating sudden changes to the nightside near‐surface electric potential.Key Points: Passing coronal mass ejection (CME) during a Full Moon distorts the magnetopause and magnetosheath, resulting in the Moon's removal from the geomagnetic tailCME arrival results in the redevelopment of a short optically misaligned lunar plasma wakeEvent conditions are favorable for the development of flux‐rope like plasmoids in the magnetotail capable of being detected at the Moon [ABSTRACT FROM AUTHOR]

We present a solar‐centric approach to estimating the probability of extreme coronal mass ejections (CME) using the Solar and Heliospheric Observatory (SOHO)/Large Angle and Spectrometric Coronagraph Experiment (LASCO) CME Catalog observations updated through May 2018 and an updated list of near‐Earth interplanetary coronal mass ejections (ICME). We examine robust statistical approaches to the estimation of extreme events. We then assume a variety of time‐independent distributions fitting, and then comparing, the different probability distributions to the relevant regions of the cumulative distributions of the observed CME speeds. Using these results, we then obtain the probability that the velocity of a CME exceeds a particular threshold by extrapolation. We conclude that about 1.72% of the CMEs recorded with SOHO LASCO arrive at the Earth over the time both data sets overlap (November 1996 to September 2017). Then, assuming that 1.72% of all CMEs pass the Earth, we can obtain a first‐order estimate of the probability of an extreme space weather event on Earth. To estimate the probability over the next decade of a CME, we fit a Poisson distribution to the complementary cumulative distribution function. We inferred a decadal probability of between 0.01 and 0.09 for an event of at least the size of the large 2012 event, and a probability between 0.0002 and 0.016 for the size of the 1859 Carrington event. [ABSTRACT FROM AUTHOR]