Cosmogenic radionuclides reveal an extreme solar particle storm near a solar minimum 9125 years BP

During solar storms, the Sun expels large amounts of energetic particles (SEP) that can react with the Earth’s atmospheric constituents and produce cosmogenic radionuclides such as 14C, 10Be and 36Cl. Here we present 10Be and 36Cl data measured in ice cores from Greenland and Antarctica. The data consistently show one of the largest 10Be and 36Cl production peaks detected so far, most likely produced by an extreme SEP event that hit Earth 9125 years BP (before present, i.e., before 1950 CE), i.e., 7176 BCE. Using the 36Cl/10Be ratio, we demonstrate that this event was characterized by a very hard energy spectrum and was possibly up to two orders of magnitude larger than any SEP event during the instrumental period. Furthermore, we provide 10Be-based evidence that, contrary to expectations, the SEP event occurred near a solar minimum.

Circulatory and Nervous Diseases Mortality Patterns—Comparison of Geomagnetic Storms and Quiet Periods

The aim of this paper is to statistically examine whether there are different patterns in daily numbers of deaths during the quiet periods of solar activity, in contrast to the periods of the strong solar storms. We considered three periods of solar storms (storm of 14 July 2000 Bastille Day Event, storm of 28 October 2003 Halloween Solar Storms, and storm of 17 March 2015 St. Patrick’s Day event) and three periods of continuous very low solar activity (13 September–24 October 1996, 21 July–20 August 2008, and 31 July–31 August 2009) during the Solar Cycles No. 23 and No. 24. In particular, we focus on diseases of the nervous system (group VI from ICD-10) and diseases of the circulatory system (group IX from ICD-10) separately for both sexes and two age groups (under 39 and 40+). We demonstrate that in the resulting graphical models there was a connection between the daily number of deaths and all indices of solar and geomagnetic activity in periods of low solar activity in contrast to periods of strong solar storms in some monitored groups according to age, sex, and group of diagnosis.

Development of an in situ Acoustic Anemometer to Measure Wind in the Stratosphere for SENSOR

The Stratospheric Environmental respoNses to Solar stORms (SENSOR) campaign investigates the influence of solar storms on the stratosphere. This campaign employs a long-duration zero-pressure balloon as a platform to carry multiple types of payloads during a series of flight experiments in the mid-latitude stratosphere from 2019 to 2022. This article describes the development and testing of an acoustic anemometer for obtaining in situ wind measurements along the balloon trajectory. Developing this anemometer was necessary, as there is no existing commercial off-the-shelf product, to the authors’ knowledge, capable of obtaining in situ wind measurements on a high-altitude balloon or other similar floating platform in the stratosphere. The anemometer is also equipped with temperature, pressure, and humidity sensors from a Temperature-Pressure-Humidity measurement module, inherited from a radiosonde developed for sounding balloons. The acoustic anemometer and other sensors were used in a flight experiment of the SENSOR campaign that took place in the Da chaidan District (95.37° E, 37.74° N) on 4 September 2019. Three-dimensional wind speed observations, which were obtained during level flight at an altitude of around 25 km, are presented. A preliminary analysis of the measurements yielded by the anemometer are also discussed. In addition to wind speed measurements, temperature, pressure, and relative humidity measurements during ascent are compared to observations from a nearby radiosonde launched four hours earlier. The problems experienced by the acoustic anemometer during the 2019 experiment show that the acoustic anemometer must be improved for future experiments in the SENSOR campaign.

Long-term cost-effectiveness of interventions for loss of electricity/industry compared to artificial general intelligence safety

Extreme solar storms, high-altitude electromagnetic pulses, and coordinated cyber attacks could disrupt regional/global electricity. Since electricity basically drives industry, industrial civilization could collapse without it. This could cause anthropological civilization (cities) to collapse, from which humanity might not recover, having long-term consequences. Previous work analyzed technical solutions to save nearly everyone despite industrial loss globally, including transition to animals powering farming and transportation. The present work estimates cost-effectiveness for the long-term future with a Monte Carlo (probabilistic) model. Model 1, partly based on a poll of Effective Altruism conference participants, finds a confidence that industrial loss preparation is more cost-effective than artificial general intelligence safety of ~ 88% and ~ 99+% for the 30 millionth dollar spent on industrial loss interventions and the margin now, respectively. Model 2 populated by one of the authors produces ~ 50% and ~ 99% confidence, respectively. These confidences are likely to be reduced by model and theory uncertainty, but the conclusion of industrial loss interventions being more cost-effective was robust to changing the most important 4–7 variables simultaneously to their pessimistic ends. Both cause areas save expected lives cheaply in the present generation and funding to preparation for industrial loss is particularly urgent.

Development of an in situ Acoustic Anemometer to Measure Wind in the Stratosphere for SENSOR

The Stratospheric Environmental respoNses to Solar stORms (SENSOR) campaign investigates the influence of solar storms on the stratosphere. This campaign employs a long-duration zero-pressure balloon as a platform to carry multiple types of payloads during a series of flight experiments in the mid-latitude stratosphere from 2019 to 2022. This article describes the development and testing of an acoustic anemometer for obtaining in situ wind measurements along the balloon trajectory. Developing this anemometer was necessary, as there is no existing commercial off-the-shelf product, to the authors' knowledge, capable of obtaining in situ wind measurements on a high-altitude balloon or other similar floating platform in the stratosphere. The anemometer is also equipped with temperature, pressure, and humidity sensors from a Temperature-Pressure-Humidity measurement module, inherited from a radiosonde developed for sounding balloons. The acoustic anemometer and other sensors were used in a flight experiment of the SENSOR campaign that took place in the Da chaidan District (95.37° E, 37.74° N) on 4 September 2019. The zonal and meridional wind speed observations, which were obtained during level flight at an altitude exceeding 20 km, are presented. This is the first time that in situ wind measurements were obtained during level flight at this altitude. In addition to wind speed measurements, temperature, pressure, and relative humidity measurements during ascent are compared to observations from a nearby radiosonde launched four hours earlier. Further analysis of the wind data will presented in a subsequent publication. The problems experienced by the acoustic anemometer during the 2019 experiment show that the acoustic anemometer must be improved for future experiments in the SENSOR campaign.

Using Gradient Boosting Regressors to forecast the ambient solar wind from coronal magnetic models

<p>In this study we present a method for forecasting the ambient solar wind at L1 from coronal magnetic models. Ambient solar wind flows in interplanetary space determine how solar storms evolve through the heliosphere before reaching Earth, and accurately modelling and forecasting the ambient solar wind flow is therefore imperative to space weather awareness. We describe a novel machine learning approach in which solutions from models of the solar corona based on 12 different ADAPT magnetic maps are used to output the solar wind conditions some days later at the Earth. A feature analysis is carried out to determine which input variables are most important. The results of the forecasting model are compared to observations and existing models for one whole solar cycle in a comprehensive validation analysis. We find that the new model outperforms existing models and 27-day persistence in almost all metrics. The final model discussed here represents an extremely fast, well-validated and open-source approach to the forecasting of ambient solar wind at Earth, and is specifically well-suited for ensemble modelling or for application with other coronal models.</p>

Machine learning model of the plasmasphere to forecast satellite charging caused by solar storms.

<p>Solar storms are hazardous events consisting of a high emission of particles and radiation from the sun that can have adverse effect both in space and on Earth. In particular, the satellites can be damaged by energetic particles through surface and deep dielectric charging. The Prediction of Adverse effects of Geomagnetic storms and Energetic Radiation (PAGER) is an EU Horizon 2020 project, which aims to provide a forecast of satellite charging through a pipeline of algorithms connecting the solar activity with the satellite charging. The plasmasphere modeling is an essential component of this pipeline, as plasma density is a crucial parameter for evaluating surface charging. Moreover, plasma density in the plasmasphere has very significant scientific applications, as it controls the growth of waves and how waves interact with particles. Successful plasmasphere machine learning models have been already developed, using as input several geomagnetic indices. However, in the context of the PAGER project one is constrained to use solar wind features and Kp index, whose forecasts are provided by other components of the pipeline. Here, we develop a machine learning model of the plasma density using solar wind features and the Kp geomagnetic index. We validate and test the model by measuring its performance in particular during geomagnetic storms on independent datasets withheld from the training set and by comparing the model predictions with global images of He+ distribution in the Earth’s plasmasphere from the IMAGE Extreme UltraViolet (EUV) instrument. Finally, we present the results of both local and global plasma density reconstruction. </p>

Energy Flux and Conductance from Meso-Scale Auroral Features Observed by All-Sky-Imagers

<p>Earth’s Magnetosphere-Ionosphere-Thermosphere system is inseparably coupled, with driving from above and below by various terrestrial and space weather phenomena. Global models have done well at capturing large-scale effects, but currently do not capture the meso-scale (~10s-500 km) phenomena which often are locally more intense. As computing power improves, and modeling meso-scales now becomes possible, it is vital to provide data-informed inputs of the relevant drivers. In this presentation, we focus on the energy flux deposited into the ionosphere from the magnetosphere by precipitating particles that result in the aurora, specifically at meso-scales, and the resulting conductance. Thanks to NASA’s THEMIS mission, an array of all-sky-imagers (ASIs) across Canada monitors the majority of the nightside auroral oval at a 3 second cadence, providing a global view at temporal & spatial resolutions required to study the aurora on meso-scales. Thus, we present 2-D maps over time of the energy flux, energy, and conductance that result from the aurora during solar storms and substorms, including those features at meso-scales. We determine conductance using the ASI-determined eflux and energy as inputs to the Boltzman Three Constituent (B3C) auroral transport code, compare values with Poker Flat ISR observations, and find a good comparison. We find that meso-scale aurora contributes at least 60-70% of the total precipitated energy flux during the first ten minutes of a substorm. Our results can be utilized by the broad community, for example, as inputs to atmospheric models or as the resulting conductance from precipitation inferred by magnetospheric models or satellite observations.</p>