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Arctic clouds are poorly represented in climate models partly due to a lack of understanding of their source and nucleating capability of natural aerosol in the high Arctic. Recent field campaigns provided evidence of a source of sea salt aerosol (SSA) from blowing snow above sea ice, which can account for SSA winter/spring maxima observed in the polar regions. SSA emissions from sea ice sources can potentially influence regional climate via the indirect radiative effect, but contributions to cloud-forming particles, in particular, ice-nucleating particles (INP), are unknown. Here we report the first online spring-time observations of INPs in the Central Arctic. INP concentrations were on the order of a few tens [particle m-3] activating between -38 and -15°C and were often associated with high wind speeds. Initial offline droplet assay analysis of snow on sea ice indicates the presence of potential INPs in winter/spring activating at -29 to -25°C. This is evidence that snow on sea ice represents a viable reservoir of INPs, which can be physically released via the blowing snow mechanism to the air above. We discuss sea ice sources of coarse SSA and INPs and their role in the lower atmosphere with a focus on blowing snow. To do this, we consider the comprehensive set of MOSAiC observations, including aerosol size and composition, airborne snow particles, and chemical and physical properties of both aerosol and snow on sea ice.

10 pages, 3 figures, 1 table, supporting information https://doi.org/10.1021/acs.est.1c07796, Atmospheric aerosols are important drivers of Arctic climate change through aerosol–cloud–climate interactions. However, large uncertainties remain on the sources and processes controlling particle numbers in both fine and coarse modes. Here, we applied a receptor model and an explainable machine learning technique to understand the sources and drivers of particle numbers from 10 nm to 20 μm in Svalbard. Nucleation, biogenic, secondary, anthropogenic, mineral dust, sea salt and blowing snow aerosols and their major environmental drivers were identified. Our results show that the monthly variations in particles are highly size/source dependent and regulated by meteorology. Secondary and nucleation aerosols are the largest contributors to potential cloud condensation nuclei (CCN, particle number with a diameter larger than 40 nm as a proxy) in the Arctic. Nonlinear responses to temperature were found for biogenic, local dust particles and potential CCN, highlighting the importance of melting sea ice and snow. These results indicate that the aerosol factors will respond to rapid Arctic warming differently and in a nonlinear fashion, This research was supported by the Natural Environment Research Council (grant no. NE/S00579X/1) and endorsed by the Surface Ocean-Lower Atmosphere Study (SOLAS), With the institutional support of the ‘Severo Ochoa Centre of Excellence’ accreditation (CEX2019-000928-S)

The SPectrometer for Ice Nuclei (SPIN) is a commercially available ice nucleating particle (INP) counter manufactured by Droplet Measurement Technologies in Boulder, CO. The SPIN is a continuous flow diffusion chamber with parallel plate geometry based on the Zurich Ice Nucleation Chamber and the Portable Ice Nucleation Chamber. This study presents a standard description for using the SPIN instrument and also highlights methods to analyze measurements in more advanced ways. It characterizes and describes the behavior of the SPIN chamber, reports data from laboratory measurements, and quantifies uncertainties associated with the measurements. Experiments with ammonium sulfate are used to investigate homogeneous freezing of deliquesced haze droplets and droplet breakthrough. Experiments with kaolinite, NX illite, and silver iodide are used to investigate heterogeneous ice nucleation. SPIN nucleation results are compared to those from the literature. A machine learning approach for analyzing depolarization data from the SPIN optical particle counter is also presented (as an advanced use). Overall, we report that the SPIN is able to reproduce previous INP counter measurements., Atmospheric Measurement Techniques, 9 (7), ISSN:1867-1381, ISSN:1867-8548

A recent study on cloud observations reports an increase in total cloud cover at Faraday/Vernadsky since 1960 in the annual and wintertime data. The aim of this present study is to investigate whether this increase in total cloud cover has influenced the precipitation in this region. For this purpose, precipitation observations at the Antarctic base Faraday/Vernadsky between 1960 and 1999 were analysed. A positive trend, significant at the 5% level, was found in the number of precipitation events recorded during winter, showing an increase of 13 events per decade. The annual number of precipitation days has increased by 5.7 per decade during the period of investigation, with highest increase rates being observed in winter and autumn. The characteristics of these findings confirm that results previously published though trends presented here are ∼50% smaller due to a more thorough data quality control of the observational data. These results indicate that an increase in total cloud cover at Faraday/Vernadsky observed since 1960 in the annual and wintertime data is reflected in higher numbers of precipitation events and days. Analyses of the precipitation type found an increase in the proportion of events of non-frozen precipitation, which is significant (1% level) on an annual basis as well as in spring and autumn (both significant at 5% level). This is a clear manifestation of the year round temperature increase observed over the Antarctic Peninsula. The increase in non-frozen precipitation will have reduced the albedo in the region and will thus have contributed to the temperature-albedo feedback. To refreeze rain that is draining through glaciers energy is extracted from the surrounding ice, thereby physically corroding the ice. This will have contributed to the observed retreat of glaciers around the Antarctic Peninsula. As non-frozen precipitation falling on frozen ground cannot be stored but instead runs off, less water will be available for the ecosystem.

The regional model REMO, which is the atmospheric component of the coupled atmosphere–ice–ocean–land climate model system BALTIMOS, is tested with respect to its ability to simulate the atmospheric boundary layer over the open and ice-covered Baltic Sea. REMO simulations are compared to ship, radiosonde, and aircraft observations taken during eight field experiments. The main results of the comparisons are: (1) The sharpness and strength of the temperature inversion are underestimated by REMO. Over open water, this is connected with an overestimation of cloud coverage and moisture content above the inversion. (2) The vertical temperature stratification in the lowest 200 m over sea ice is too stable. (3) The horizontal inhomogeneity of sea ice concentration as observed by aircraft could not be properly represented by the prescribed ice concentration in REMO; large differences in the surface heat fluxes arise especially under cold-air advection conditions. The results of the comparisons suggest a reconsideration of the parameterization of subgrid-scale vertical exchange both under unstable und stable conditions.

This paper presents results of a combined analysis of cloud observations made at the Antarctic base Faraday/Vernadsky between 1960 and 2005 and sea ice concentration from the HadISST1 data set. The annual total cloud cover has increased significantly during this period with the strongest and most significant positive trend found in winter, and positive tendencies observable in all seasons. This trend is associated with a decrease in sea ice concentration in the area of the Western Antarctic Peninsula. Though the observed sea ice reduction is actually larger and more significant in summer and autumn, there is actually a significant relation between total cloud cover and sea ice concentration only in winter. The increase in the total cloud cover is neither reflected in the low cloud amount nor in the number of records for low, medium or high level clouds. It is therefore thought that the increase in the total cloud cover is caused by an increase in the amount of medium and/or high level clouds. Instead, records for the low cloud amount show a redistribution from cases of extreme cloud cover (0, 1, 7 and 8 okta), which account for up to 90% of annual records, to cases of moderate cloud cover. In accordance with the decrease in sea ice, this may indicate a shift from low-level stratiform towards convective clouds. Copyright © 2009 Royal Meteorological Society

For some beech ( Fagus sylvatica L.) stands with different stand densities the plant area index (PAI) was measured by means of a Licor LAI-2000 plant canopy analyser. The stands are located on the slopes of a valley in south-west Germany and had been treated by different types of silvicultural management (heavy shelterwood felling, light shelterwood felling, control plot). The analyser was used (a) to investigate the light conditions on plots of the same thinning regime, (b) to quantify the differences between the different treatments and (c) to obtain absolute values of PAI for interdisciplinary research. PAI was measured at three different phenological stages (leafless, leaf-unfolding and fully leafed season in 2000) and was found to be about 5.2 for the fully developed canopy on the control plots, 3.2 on the light fellings and about 2.0 for the heavy fellings. In the leafless period PAI was between 1.1 (control) and 0.4 (heavy felling). Measurements made in summer 2000 and summer 2002 were compared, and showed an increase of PAI, especially on the thinned plots. Measurements of photosynthetically active radiation (PAR) above and below the canopy in combination with measured PAI were used to apply Beer's Law of radiation extinction to calculate the extinction coefficient k for different sky conditions and for the different growing seasons on the control plots. The extinction coefficient k for the beech stands was found to be between 0.99 and 1.39 in the leafless period, 0.62 to 0.91 during leaf unfolding and between 0.68 and 0.83 in the fully leafed period. Using PAR measurements and the k values obtained, the annual cycle of PAI was modelled inverting Beer's Law.