Abstract
<p>The marine boundary layer offers a unique opportunity to investigate the electrical properties of the atmosphere, as the effect of natural radioactivity in driving near surface ionization is significantly reduced over the ocean, and the concentration of aerosols is also typically lower than over land. This work addresses the temporal variability of the atmospheric electric field in the South Atlantic marine boundary layer based on measurements from the SAIL (Space-Atmosphere-Ocean Interactions in the marine boundary Layer) project. The SAIL monitoring campaign took place on board the Portuguese navy tall ship NRP Sagres during its circumnavigation expedition in 2020.  Two identical field mills (CS110, Campbell Scientific) were installed on the same mast but at different heights (about 5 and 22 meters), recording the atmospheric electric field every 1-second. Hourly averages of the atmospheric electric field are analyzed for the ship’s leg from 3<sup>rd</sup> to 25<sup>th</sup> March, between Buenos Aires (South America) and Cape Town (South Africa). The median daily curve of the electric field has a shape compatible with the Carnegie curve, but significant variability is found in the daily pattern of individual days, with only about 30% of the days exhibiting a diurnal pattern consistent with the Carnegie curve.</p>

Abstract
<p>Atmospheric new particle formation (NPF) generates secondary aerosol particles into the lower atmosphere via gas-to-particle phase transition. Secondary aerosol particles dominate the total particle number concentration and are an important source for cloud condensation nuclei <sup>[1]</sup>. NPF typically begins with clustering among gaseous molecules. Once the newly formed clusters attain a size larger than the critical cluster size (~1.5 nm), their growth to larger sizes is energetically favoured and eventually they become nanoparticles <sup>[2]</sup>. NPF is often observed with the participation of air ions <sup>[3]</sup> and sometimes is induced by ions <sup>[4]</sup>. Air ions are a constituent of atmospheric electricity. The presence of the Earth-atmosphere electric field poses an electrical force on air ions. The earth-atmosphere electric field exhibits variability at different time scales under fair-weather conditions <sup>[5]</sup>. It is therefore interesting to understand whether the Earth-atmosphere electric field influences atmospheric new particle formation.</p> <p>We analysed the Earth-atmosphere electric field together with the number size distribution data of air ions and aerosol particles under fair-weather conditions measured at Hyytiälä SMEAR II station in Southern Finland <sup>[6]</sup>. The electric field were measured by two Campbell CS 110 field mills in parallel. Air ion data were obtained with a Balance Scanning Mobility Analyser (BSMA) and a Neutral and Air Ion Spectrometer (NAIS), and aerosol particle data with a Differential Mobility Particle Sizer (DMPS). We used condensation Sinks (CS) derived from the DMPS measurement, air temperature, relative humidity, wind speed, global radiation as well as brightness derived from the global radiation measurement to assist the analysis. The measured earth-atmosphere electric field on NPF days was higher than on non-NPF days. We found that under low CS conditions, the electric field can enhance the formation of 1.7-3 nm air ions, but the concentration of 1.7-3 nm ions decreased with an increasing electric field under high CS conditions.</p> <p>References:</p> <p>[1]       Kerminen V.-M. et al., Environ. Res. Lett. <strong>2018</strong>, 13, 103003.</p> <p>[2]       Kulmala M. et al., Science <strong>2013</strong>, 339, 943-946.</p> <p>[3]       Manninen H. E. et al., Atmos. Chem. Phys. <strong>2010</strong>, 10, 7907-7927.</p> <p>[4]       Jokinen T. et al., Science Advances <strong>2018</strong>, 4, eaat9744.</p> <p>[5]       Bennett A. J., Harrison R. G., Journal of Physics: Conference Series <strong>2008</strong>, 142, 012046.</p> <p>[6]       Hari P., Kulmala M., Boreal Environ. Res. <strong>2005</strong>, 10, 315-322.</p>

Abstract
<p>Although the Earth system is described to react relatively abruptly to present anthropogenic forcings, the notion of abruptness remains questionable as it refers to a time scale that is difficult to constrain properly. Recognizing this issue, the tipping elements as listed in Lenton et al. (2008) rely on long-term observations under controlled conditions, which enabled the associated tipping points to be identified. For example, there is evidence nowadays that if the rate of deforestation from forest fires and the climate change does not decrease, the Amazonian forest will reach a tipping point towards savanna (Nobre, 2019), which would impact the regional and global climate systems as well as various other ecosystems, directly or indirectly (Magalhães et al., 2020). However, if the present tipping elements, which are now evidenced, are mostly related to the present climate change and thus directly or indirectly related to anthropogenic forcing, their interpretation must still rely on former cases detected in the past, and especially from studies of abrupt climatic transitions evidenced in paleoclimate proxy records. Moreover, recent studies of past changes have shown that addressing abrupt transitions in the past raises the issue of data quality of individual records, including the precision of the time scale and the quantification of associated uncertainties. Investigating past abrupt transitions and the mechanisms involved requires the best data quality possible. This can be a serious limitation when considering the sparse spatial coverage of high resolution paleo-records where dating is critical and corresponding errors often challenging to control. In theory, this would therefore almost limit our investigations to ice-core records of the last climate cycle, because they offer the best possible time resolution. However, evidence shows that abrupt transitions can also be identified in deeper time with lower resolution records, but still revealing changes or transitions that have impacted the dynamics of the Earth system globally. TiPES Work Package 1 will address these issues and collect paleorecords permitting to evidence the temporal behavior of tipping elements in past climates, including several examples.</p> <p>Lenton T. et al. (2008). PNAS 105, 1786-1793.</p> <p>Nobre C. (2019). Nature 574, 455.</p> <p>Magalhães N.d. et al. (2020). Sci. Rep. 16914 (2019) doi:10.1038/s41598-019-53284-1</p> <p>This work is performed under the TiPES project funded by the European Union’s Horizon 2020 research and innovation program under grant agreement # 820970 <https://tipes.sites.ku.dk/></p>

Abstract

Abstract

Abstract
Greenland ice core records display abrupt transitions, designated as Dansgaard-Oeschger (DO) events, characterised by episodes of rapid warming (typically decades) followed by a slower cooling. The identification of abrupt transitions is hindered by the typical low resolution and small size of paleoclimate records, and their significant temporal variability. Furthermore, the amplitude and duration of the DO events varies substantially along the last glacial period, which further hinders the objective identification of abrupt transitions from ice core records Automatic, purely data-driven methods, have the potential to foster the identification of abrupt transitions in palaeoclimate time series in an objective way, complementing the traditional identification of transitions by visual inspection of the time series.In this study we apply an algorithmic time series method, the Matrix Profile approach, to the analysis of the NGRIP Greenland ice core record, focusing on:- the ability of the method to retrieve in an automatic way abrupt transitions, by comparing the anomalies identified by the matrix profile method with the expert-based identification of DO events;- the characterisation of DO events, by classifying DO events in terms of shape and identifying events with similar warming/cooling temporal patternThe results for the NGRIP time series show that the matrix profile approach struggles to retrieve all the abrupt transitions that are identified by experts as DO events, the main limitation arising from the diversity in length of DO events and the method’s dependence on fixed-size sub-sequences within the time series. However, the matrix profile method is able to characterise the similarity of shape patterns between DO events in an objective and consistent way.