Abstract
<p>A novel ionisation detector, previously deployed on meteorological radiosonde flights, has demonstrated responsivity to X-rays and gamma radiation, and additionally, is thought to be sensitive to ionising radiation from cosmic rays. The PiN detector, composed of a 1x1x0.8 cm<sup>3 </sup>CsI(Tl) microscintillator coupled to a PiN photodiode, was deployed on the NRP Sagres sailing vessel on a cruise in the Atlantic between Portugal and the Azores in 2021. The instrument can determine both the count rate and energy of incoming ionising radiation particles.</p><p>The instrument was operational during the voyage in November 2021 when a coronal mass ejection event induced a sudden decrease in the observed cosmic ray intensity, known as a Forbush decrease. We present data recorded by the ionisation detector during this period, to characterise the instrument’s ability to detect cosmic ray events, and we compare the performance with neutron monitoring stations Oulu in Finland, and Dourbes in Belgium. As the PiN detector provides spectral and count rate data, it is possible to group events by their energy, and investigate the count rates of specific energy regimes. This approach is useful as many sources – including high and low energy ionising radiation from cosmic rays – contribute to the background energy spectrum. As a result, more meaningful comparisons and relationships can be established with the neutron monitoring stations.</p>

Abstract
<p><br>The automatic classification of peaks in gamma radiation time series is relevant for both scientific and practical applications. From the practical perspective, the classification of  peaks is fundamental for  early-warning systems for radiation protection and detection of radioactive material. From the scientific point of view, peaks in gamma radiation are often driven by precipitation  and consequent  scavenging of airborne radon progeny radionuclides to the ground (mainly Pb-214 and Bi-214). Thus measurements of gamma radiation at the earth's surface have the potential to provide information on micro-physical processes occurring high above in the clouds, as the dominant source of radon progeny is thought to be associated with in-cloud processes – nucleation scavenging and interstitial aerosol collection by cloud or rain droplets. </p><p>The present study addresses the classification of peaks in high-resolution (1-minute) gamma radiation time series from the GRM (Gamma Radiation Monitoring) campaign, which is being carried out since 2015 at the Eastern North Atlantic (ENA) station of the ARM (Atmospheric Radiation Measurements) programme. In addition to the gamma time series, precipitation information from laser disdrometer measurements is considered, including rain rate, liquid water content, median drop diameter and droplet concentration. Diverse machine learning algorithms are examined with the goal to identify and classify gamma peaks driven by precipitation events, and further examine the association between precipitation characteristics and the resulting gamma radiation peak on the ground.</p><p> </p>

Abstract
<p>Radon and its progeny are well-documented sources of natural radioactivity which can be used as benchmarks for testing a novel ionisation detector. The miniaturised ionisation detector was deployed aboard the NRP Sagres on a SAIL mission in July 2021 which travelled between the Açores and Lisbon in the North Atlantic Ocean. On its voyage, the detector profiled natural background radiation and in-directly detected cosmic ray muons, providing both spectroscopic energy discrimination and count rate data. The detector was simultaneously run with a NaI(Tl) gamma ray counter and other meteorological instruments.</p><p>The small form factor and low-power detector, composed of a 1x1x0.8 cm<sup>3 </sup>CsI(Tl) microscintillator coupled to a PiN photodiode, was able to identify gamma peaks from Bi-214 and K-40, having been calibrated using laboratory gamma sources up to 1.3 MeV. This research aims to investigate the performance of the ionisation detector and behaviour of discrete gamma energies over the duration of the voyage. Additionally, we will show a comparison of the CsI(Tl) based ionisation detector against the gamma ray counter which features a larger NaI(Tl) scintillator.</p>

Abstract
<p>The Dansgaard-Oeschger (DO) events are one of the most striking examples of abrupt climate change in the Earth's history, representing temperature oscillations of about 8 to 16 degrees Celsius within a few decades. DO events have been studied extensively in paleoclimatic records, particularly in ice core proxies. Examples include the Greenland NGRIP record of oxygen isotopic composition.<br>This work addresses the anticipation of DO events using machine learning algorithms. We consider the NGRIP time series from 20 to 60 kyr b2k with the GICC05 timescale and 20-year temporal resolution. Forecasting horizons range from 0 (nowcasting) to 400 years. We adopt three different machine learning algorithms (random forests, support vector machines, and logistic regression) in training windows of 5 kyr. We perform validation on subsequent test windows of 5 kyr, based on timestamps of previous DO events' classification in Greenland by Rasmussen et al. (2014). We perform experiments with both sliding and growing windows.<br>Results show that predictions on sliding windows are better overall, indicating that modelling is affected by non-stationary characteristics of the time series. The three algorithms' predictive performance is similar, with a slightly better performance of random forest models for shorter forecast horizons. The prediction models' predictive capability decreases as the forecasting horizon grows more extensive but remains reasonable up to 120 years. Model performance deprecation is mostly related to imprecision in accurately determining the start and end time of events and identifying some periods as DO events when such is not valid.</p>

Abstract
<p>Air ions are ubiquitous in the atmosphere. These charge carriers can be found in various forms as charged molecules, nanoclusters as well as aerosol particles. The population of air ions normally concentrates in the cluster size range (0.8 – 1.7 nm in mobility equivalent diameters) in the absence of particle formation processes. A concentration burst in the intermediate size range (1.7 – 7 nm) can be typically observed during atmospheric new particle formation (NPF) and in precipitation episodes <sup>1</sup>. Contrary to the intermediate ions formed during NPF that favour growth to larger sizes, intermediate ion bursts resulting from precipitation tend to shrink <sup>2,3</sup>. The production of intermediate ions during precipitation has been attributed to the Lenard effect and they are usually referred to as the balloelectric ions <sup>3</sup>.</p><p>During precipitation the rain-out and wash-out of radon progeny increase the gamma dose at ground level <sup>4</sup>. Being a type of ionising radiation, gamma creates positive and negative charges in the air. These charges are either lost in recombination or transformed into air ions. It is therefore interesting to understand whether the precipitation-associated elevation in gamma radiation plays any role in forming or neutralising the balloelectric ions. At SMEAR II station in Hyytiälä, Finland <sup>5</sup>, we have conducted measurements of air ions, gamma radiation, precipitation together with other meteorological parameters. A similar establishment of the measurement set stands also at SMEAR Estonia station in Jarvseljä, Estonia <sup>6</sup>. The data collected at Hyytiälä from 2017.7 to 2018.8 show that the intermediate ion concentration correlates with rainfall only when the precipitation intensity is greater than 1 mm/h. For milder rainfall with the precipitation intensity being 0.1-1 mm/h, the intermediate ion concentration increases with an increase in the gamma counts. The work is under progress and we intend to extend the analysis to Jarvseljä data for a comprehensive understanding of the observations.</p><p>Acknowledgements: This work received financial supports from European Regional Development Fund (project MOBTT42) under the Mobilitas Pluss programme and from Estonian Research Council project PRG714.</p><p>References:</p><p>1. Tammet, H., Komsaare, K. & Hõrrak, U. Intermediate ions in the atmosphere. Atmospheric Research <strong>135-136</strong>, 263-273, doi:10.1016/j.atmosres.2012.09.009 (2014).</p><p>2. Hõrrak, U. et al. Formation of Charged Nanometer Aerosol Particles Associated with Rainfall: Atmospheric Measurements and Lab Experiment. Report Series in Aerosol Science <strong>80</strong>, 180-185 (2006).</p><p>3. Tammet, H., Hõrrak, U. & Kulmala, M. Negatively charged nanoparticles produced by splashing of water. Atmos. Chem. Phys. <strong>9</strong>, 357–367 (2009).</p><p>4. Paatero, J. & Hatakka, J. Wet deposition efficiency of short-lived radon-222 progeny in central Finland. Boreal Env. Res. <strong>4</strong>, 285-293 (1999).</p><p>5. Hari, P. & Kulmala, M. Station for measuring ecosystem-atmosphere relations (SMEAR II). Boreal Environ. Res. <strong>10</strong>, 315-322 (2005).</p><p>6. Noe, S. M. et al. SMEAR Estonia: Perspectives of a large-scale forest ecosystem – atmosphere research infrastructure. Forestry Studies <strong>63</strong>, doi:10.1515/fsmu-2015-0009 (2015).</p>

Abstract
<p>Ambient radioactivity reflects a wide range of physical processes, including atmospheric and geological processes, as well as space weather and solar conditions. Gamma radiation near the Earth’s surface comes from diverse sources, including space (cosmic radiation), the earth’s atmosphere, and solid earth. In addition to the terrestrial gamma radiation originating from the radioactive decay of primordial radionuclides present in every soil and rock, gamma radiation is also continuously produced in the atmosphere from the interaction of secondary cosmic rays and upper-atmosphere gases, as well as from the decay of airborne radon (Rn-222) progeny. Therefore the temporal variability of gamma radiation contains information on a wide range of physical processes and space-earth interactions, but disentangling the different contributions remains a challenging endeavor. Continuous monitoring of gamma radiation at sea enables to remove both the terrestrial and radon exhalation contributions, allowing to examine in detail the space and atmospheric sources of ambient gamma radiation.</p><p>Gamma radiation over the Atlantic Ocean was measured on board the ship-rigged sailing ship NRP Sagres in the framework of the SAIL (Space-Atmosphere-Ocean Interactions in the marine boundary Layer) project. The measurements were performed continuously (every 1-second) with a NaI(Tl) scintillator counting all the gamma rays from 475 keV to 3 MeV. The casing of the instrument was adapted in order to endure the harsh oceanic conditions and installed in the mizzen mast of the ship. The counts were linked to a rigorous temporal reference frame and precise positioning through GNSS.</p><p>Here preliminary results based on the gamma radiation measurements performed from January 5<sup>th</sup> to May 9<sup>th </sup>2020 are presented, corresponding to the journey of the ship from Lisboa to Cabo Verde, Rio de Janeiro, Montevideu, Cape Town, and back to Lisboa. The data exhibit a clear transition from the coastal to the marine environment, enabling to study in detail the temporal variation of gamma radiation in the marine boundary layer, as well as the interface between land and marine conditions in terms of environmental radioactivity.</p>