Application of CCM SOCOL-AERv2-BE to cosmogenic beryllium isotopes: description and validation for polar regions

The short-living cosmogenic isotope 7Be, which is produced by cosmic rays in the atmosphere, is often used as a tracer for atmospheric dynamics, with precise and high-resolution measurements covering the recent decades. The long-living isotope 10Be, as measured in polar ice cores with an annual resolution, is a proxy for long-term cosmic-ray variability, whose signal can, however, be distorted by atmospheric transport and deposition that need to be properly modeled to be accounted for. While transport of 7Be can be modeled with high accuracy using the known meteorological fields, atmospheric transport of 10Be was typically modeled using case-study-specific simulations or simplified box models based on parameterizations. Thus, there is a need for a realistic model able to simulate atmospheric transport and deposition of beryllium with a focus on polar regions and (inter)annual timescales that is potentially able to operate in a self-consistent mode without the prescribed meteorology. Since measurements of 10Be are extremely laborious and hence scarce, it is difficult to compare model results directly with measurement data. On the other hand, the two beryllium isotopes are believed to have similar transport and deposition properties, being different only in production and lifetime, and thus the results of 7Be transport can be generally applied to 10Be. Here we present a new model, called CCM SOCOL-AERv2-BE, to trace isotopes of 7Be and 10Be in the atmosphere based on the chemistry–climate model (CCM) SOCOL (SOlar Climate Ozone Links), which has been improved by including modules for the production, deposition, and transport of 7Be and 10Be. Production of the isotopes was modeled for both galactic and solar cosmic rays by applying the CRAC (Cosmic Ray Atmospheric Cascade) model. Transport of 7Be was modeled without additional gravitational settling due to the submicron size of the background aerosol particles. An interactive deposition scheme was applied including both wet and dry deposition. Modeling was performed using a full nudging to the meteorological fields for the period of 2002–2008 with a spin-up period of 1996–2001. The modeled concentrations of 7Be in near-ground air were compared with the measured ones at a weekly time resolution in four nearly antipodal high-latitude locations: two in the Northern (Finland and Canada) and two in the Southern (Chile and the Kerguelen Islands) Hemisphere. The model results agree with the measurements in the absolute level within error bars, implying that the production, decay, and lateral deposition are correctly reproduced. The model also correctly reproduces the temporal variability of 7Be concentrations on annual and sub-annual scales, including the presence and absence of the annual cycle in the Northern and Southern Hemisphere, respectively. We also modeled the production and transport of 7Be for a major solar energetic particle event (SPE) on 20 January 2005, which appears insufficient to produce a measurable signal but may serve as a reference event for historically known extreme SPEs. Thus, a new full 3D time-dependent model, based on CCM SOCOL, of 7Be and 10Be atmospheric production, transport, and deposition has been developed. Comparison with real data on the 7Be concentration in the near-ground air validates the model and its accuracy.

Solar Energetic Particle Event occurrence prediction using Solar Flare Soft X-ray measurements and Machine Learning

The prediction of the occurrence of Solar Energetic Particle (SEP) events has been investigated over many years and multiple works have presented significant advances in this problem. The accurate and timely prediction of SEPs is of interest to the scientific community as well as mission designers, operators, and industrial partners due to the threat SEPs pose to satellites, spacecrafts and crewed missions. In this work we present a methodology for the prediction of SEPs from the soft X-rays of solar flares associated with SEPs that were measured in 1 AU. We use an expansive dataset covering 25 years of solar activity, 1988-2013, which includes thousands of flares and more than two hundred identified and catalogued SEPs. Neural networks are employed as the predictors in the model providing probabilities for the occurrence or not of an SEP which are converted to yes/no predictions. The neural networks are designed using current and state-of the-art tools integrating recent advances in the machine learning field. The results of the methodology are extensively evaluated and validated using all the available data and it is shown that we achieve very good levels of accuracy with correct SEP occurrence prediction higher than 85% and correct no-SEP predictions higher than 92%. Finally we discuss further work towards potential improvements and the applicability of our model in real life conditions.

Tree Rings Show Record of Newly Identified Extreme Solar Activity Event

Mass spectroscopy of tree ring material indicates a sharp, single-year rise in carbon-14 concentrations consistent with an extreme solar energetic particle event that occurred around 5410 BCE.

Chemistry-climate model SOCOL-AERv2-BEv1 with the cosmogenic Beryllium-7 isotope cycle

Short-living cosmogenic isotope 7Be, produced by cosmic rays in the atmosphere, is often used as a probe for atmospheric dynamics. Previously, modelling of the beryllium atmospheric transport was performed using simplified box-models or air back-tracing codes. While the ability of full atmospheric dynamics models to model beryllium transport was demonstrated earlier, no such ready-to-use model is currently available. Here we present the chemistry-climate model SOCOL-AERv2-BEv1 to trace isotopes of beryllium in the atmosphere. The SOCOL (SOlar Climate Ozone Links) model has been improved by including modules for the production, deposition, and transport of beryllium. Production was modelled considering both galactic and solar cosmic rays, by applying the CRAC (Cosmic-Ray induced Atmospheric Cascade) model. Radioactive decay of 7Be was explicitly taken into account. Beryllium transport was modelled without additional gravitational settling due to the small size of the background aerosol particles. An interactive deposition scheme was applied including both wet and dry depositions. The modelling was performed, using a full nudging to the meteorological fields, for the period of 2003–2008 with a spin-up period of 1996–2002. The modelled concentrations of 7Be in near-ground air were compared with the measured, at a weekly cadence, ones in four nearly antipodal high-latitude locations, two in Northern (Finland and Canada) and two in Southern (Chile and Kerguelen Island) hemispheres. The model results agree with the measurements in the absolute level within error bars, implying that the production, decay and lateral deposition are correctly reproduced by the model. The model also correctly reproduces the temporal variability of 7Be concentrations on the annual and sub-annual scales, including a perfect reproduction of the annual cycle, dominating data in the Northern hemisphere. We also modelled the production and transport of 7Be for a major solar energetic-particle event of 20-Jan-2005. Concluding, a new full 3D time-dependent model, based on the SOCOL-AERv2, of beryllium atmospheric production, transport and deposition has been developed. Comparison with the real data of 7Be concentration in the near-ground air fully validates the model and its high accuracy.