Trend analysis of aerosol particle physical properties at Villum Research Station, Northern Greenland

2021 ◽  
Author(s):  
Jakob Pernov ◽  
Henrik Skov ◽  
Daniel Thomas ◽  
Andreas Massling
Keyword(s):  
Sea Ice ◽  
Physical Properties ◽  
The Arctic ◽  
Anthropogenic Emissions ◽  
Research Station ◽  
Sea Ice Extent ◽  
Accumulation Mode ◽  
Cloud Properties ◽  
Arctic Aerosol ◽  
Increasing Trends

<p><strong>Introduction</strong></p><p>The Arctic region is particularly sensitive to global climate change, experiencing warming at twice the rate of the global average. Anthropogenic pollution (e.g. aerosols, black carbon, ozone, and greenhouse gases), which to a large extent originates from the mid-latitudes, is suspected to be partly responsible for this warming. Atmospheric aerosols can alter the planetary radiation balance directly through scattering and absorption and indirectly through modification of cloud properties. These interactions depend on aerosol physicochemical properties. The Arctic cryosphere and atmosphere has undergone significant changes in recent decades, accompanied by reductions in anthropogenic emissions, especially in Europe and North America. These changes have important ramifications for the ambient Arctic aerosol. Understanding the direction and magnitude of recent changes in the Arctic aerosol population is key to elucidating the implications for the changing Arctic, although this remains a scientific challenge. Here we report recent trends for aerosol particle physical properties, which will aid in this understanding of the changing Arctic.</p><p><strong>Measurement Site</strong><strong> & Methods</strong></p><p>All measurements were obtained at Villum Research Station (Villum, N 81<sup>o</sup>36’ W 16<sup>o</sup>39’ 24 m a.s.l) in northeastern Greenland. Particle number size distributions (PNSD) were measured using a Scanning Mobility Particle Sizer (SMPS) from 2010–2018.</p><p>We have utilized mode fitting on daily averaged PNSDs to characterize three distinct modes (Nucleation, Aitken, and Accumulation) along with geometric mean diameters (GMD) and number concentrations (PN) for each mode.</p><p>The trends in these parameters were identified and quantified using the Mann-Kendal test and Theil Sen slope on the 90<sup>th</sup> % confidence interval. Trends in different months were analyzed using daily modal parameters.</p><p><strong>Results</strong></p><p>Statistically significant (s.s.) decreasing trends were detected for the Nucleation and Aitken modes GMDs in the winter, spring, and summer, with the only s.s. increasing trends occurring in the autumn. The Accumulation mode GMD showed a s.s. decrease in the spring and s.s. increase in the summer. For the PN of each mode, large s.s. increasing trends were detected for Nucleation and Aitken mode PN in the spring and summer. The Accumulation mode PN showed a small s.s. increase in the summer and a large s.s. decrease in the autumn.</p><p>            These results show that ultrafine modes (Nucleation and Aitken) are decreasing in diameter while simultaneously increasing in number concentration. These trends are most likely related to changes in sea ice extent, as previous research has indicated a negative correlation between new particle formation and sea ice extent. The decrease in Accumulation mode GMD in spring (during the peak of the Arctic Haze) is possibly related to decreases in anthropogenic emissions, while the increase PN during summer could signal an increase in primary biogenic aerosol emissions from the ocean surface. The large decrease in Accumulation mode PN during autumn requires further investigation. </p><p>            This work will help confirm trends of other aerosol components observed at other High Arctic sites and can offer insight into the climatic implications (i.e., radiative balance and cloud properties) for a future Arctic climate.</p>

scholarly journals Biogenic and anthropogenic sources of aerosols at the High Arctic site Villum Research Station

2019 ◽  
Vol 19 (15) ◽  
pp. 10239-10256 ◽  
Author(s):  
Ingeborg E. Nielsen ◽  
Henrik Skov ◽  
Andreas Massling ◽  
Axel C. Eriksson ◽  
Manuel Dall'Osto ◽  
...  
Keyword(s):  
Sea Ice ◽  
Organic Aerosol ◽  
High Arctic ◽  
Polar Front ◽  
Anthropogenic Sources ◽  
The Arctic ◽  
Research Station ◽  
Aerosol Formation ◽  
Sea Ice Extent ◽  
Arctic Haze

Abstract. There are limited measurements of the chemical composition, abundance and sources of atmospheric particles in the High Arctic To address this, we report 93 d of soot particle aerosol mass spectrometer (SP-AMS) data collected from 20 February to 23 May 2015 at Villum Research Station (VRS) in northern Greenland (81∘36′ N). During this period, we observed the Arctic haze phenomenon with elevated PM1 concentrations ranging from an average of 2.3, 2.3 and 3.3 µg m−3 in February, March and April, respectively, to 1.2 µg m−3 in May. Particulate sulfate (SO42-) accounted for 66 % of the non-refractory PM1 with the highest concentration until the end of April and decreasing in May. The second most abundant species was organic aerosol (OA) (24 %). Both OA and PM1, estimated from the sum of all collected species, showed a marked decrease throughout May in accordance with the polar front moving north, together with changes in aerosol removal processes. The highest refractory black carbon (rBC) concentrations were found in the first month of the campaign, averaging 0.2 µg m−3. In March and April, rBC averaged 0.1 µg m−3 while decreasing to 0.02 µg m−3 in May. Positive matrix factorization (PMF) of the OA mass spectra yielded three factors: (1) a hydrocarbon-like organic aerosol (HOA) factor, which was dominated by primary aerosols and accounted for 12 % of OA mass, (2) an Arctic haze organic aerosol (AOA) factor and (3) a more oxygenated marine organic aerosol (MOA) factor. AOA dominated until mid-April (64 %–81 % of OA), while being nearly absent from the end of May and correlated significantly with SO42-, suggesting the main part of that factor is secondary OA. The MOA emerged late at the end of March, where it increased with solar radiation and reduced sea ice extent and dominated OA for the rest of the campaign until the end of May (24 %–74 % of OA), while AOA was nearly absent. The highest O∕C ratio (0.95) and S∕C ratio (0.011) was found for MOA. Our data support the current understanding that Arctic aerosols are highly influenced by secondary aerosol formation and receives an important contribution from marine emissions during Arctic spring in remote High Arctic areas. In view of a changing Arctic climate with changing sea-ice extent, biogenic processes and corresponding source strengths, highly time-resolved data are needed in order to elucidate the components dominating aerosol concentrations and enhance the understanding of the processes taking place.

Pan-Arctic and regional trends of reflectance, clouds and fluxes: implications for Arctic Amplification

2021 ◽  
Author(s):  
Luca Lelli ◽  
Narges Khosravi ◽  
Marco Vountas ◽  
John Burrows
Keyword(s):  
Sea Ice ◽  
Radiative Forcing ◽  
The Arctic ◽  
Arctic Amplification ◽  
Sea Ice Extent ◽  
Simple Assumption ◽  
Spectral Reflectivity ◽  
Surface Warming ◽  
Cloud Properties ◽  
Regional Trends

<p>It is now well known that the sea ice extent in the Artic has been shrinking in the past three decades in the period known as the Arctic Amplification. A simple assumption would be that if the sea ice extent has been reduced, then the spectral reflectance at the top of the atmosphere - R<sub>TOA</sub> - would have also decreased across the Arctic. On the other hand, Arctic reflectivity also largely depends on the presence of clouds, shielding the underlying surface, and on changes of their optical and physical properties. Thus, the assessment of trends of spectral reflectivity and cloud properties are essential to understand those forcings and feedbacks considered drivers of Arctic Amplification as well as the interactions between the components of the Arctic cryosphere. In the reported study we observationally tackle the stated problem investigating changes of R<sub>TOA</sub> at selected wavelengths making use of spaceborne measurements of the Global Ozone Monitoring Experiment (GOME onboard ERS-2 and MetOp A/B/C) and of the Scanning Imaging Absorption Spectrometer for Atmospheric Chartography (SCIAMACHY onboard Envisat) for the period 1995-2018. We complement this record with cloud properties and fluxes at top of the atmosphere and at the surface, inferred from measurements of the post-meridiem orbits of the Advanced Very High Resolution Radiometer (AVHRR onboard POES). Although the Pan-Arctic reflectivity has decreased, the analysis of regional trends shows distinct areas where the reflectivity trends diverge. While darkening areas can be attributed to seasonal sea ice decline, an increase of Arctic brightness over sea ice free regions can be largely attributed to changes in the optical properties of clouds. While the multiyear mean of the radiative forcing by clouds points to a TOA cooling and a surface warming, its trends exhibit opposite tendencies. In the last two decades, the cloud radiative effect at TOA is expected to warm the lower latitudes (below 75 N) and to cool the circumpolar belt, while an opposite trend at BOA, amounting to 5 W m<sup>-2 </sup>per decade, cools the lower Arctic latitudes and warms the permanent sea ice region, this effect being more pronounced in spring months (April to June) than in summer months (July to September).</p>

scholarly journals Biogenic and Anthropogenic sources of Arctic Aerosols

2019 ◽  
Author(s):  
Ingeborg E. Nielsen ◽  
Henrik Skov ◽  
Andreas Massling ◽  
Axel C. Eriksson ◽  
Manuel Dall'Osto ◽  
...  
Keyword(s):  
Sea Ice ◽  
Black Carbon ◽  
Organic Aerosol ◽  
High Arctic ◽  
Anthropogenic Sources ◽  
The Arctic ◽  
Research Station ◽  
Aerosol Formation ◽  
Sea Ice Extent ◽  
Arctic Haze

Abstract. There are limited measurements of the chemical composition, abundance, and sources of black carbon (BC) containing particles in the high Arctic. To address this, we report 93 days of Soot Particle Aerosol Mass Spectrometer (SP-AMS) data collected in the high Arctic. The period spans from February 20th until May 23rd 2015 at Villum Research Station (VRS) in Northern Greenland (81°36' N). Particulate sulfate (SO42−) accounted for 66 % of the non-refractory PM1, which amounted to 2.3 µg m−3 as an average value observed during the campaign. The second most abundant species was organic matter (24 %), averaging 0.55 µg m3. Both organic aerosol (OA) and PM1, estimated from the sum of all collected species, showed a marked decrease throughout May in accordance with Arctic haze leveling off. The refractory black carbon (rBC) concentration averaged 0.1 µg m−3 over the entire campaign. Positive Matrix Factorization (PMF) of the OA mass spectra yielded three factors: (1) a Hydrocarbon-like Organic Aerosol (HOA) factor, which was dominated by primary aerosols and accounted for 12 % of OA mass; (2) an Arctic haze Organic Aerosol (AOA) factor, which accounted for 64 % of the OA and dominated until mid-April while being nearly absent from the end of May; and (3) a more oxygenated Marine Organic Aerosol (MOA) factor, which accounted for 22 % of OA. AOA correlated significantly with SO42−, suggesting the main part of that factor being secondary OA. The MOA emerged late at the end of March, where it increased with solar radiation and reduced sea ice extent, and dominated OA for the rest of the campaign until the end of May. Important differences are observed among the factors, including the highest O/C ratio (0.95) and S/C ratio (0.011) for MOA – the marine related factor. Our data supports current understanding of the Arctic summer aerosols, driven mainly by secondary aerosol formation, but with an important contribution from marine emissions. In view of a changing Arctic climate with changing sea-ice extent, biogenic processes, and corresponding source strengths, highly time-resolved data are urgently needed in order to elucidate the components dominating aerosol concentrations.

Investigations of past climate and sea-ice variability in the fjord area by Station Nord, eastern North Greenland

1969 ◽  
Vol 35 ◽  
pp. 67-70 ◽  
Author(s):  
Niels Nørgaard-Pedersen ◽  
Sofia Ribeiro ◽  
Naja Mikkelsen ◽  
Audrey Limoges ◽  
Marit-Solveig Seidenkrantz
Keyword(s):  
Sea Ice ◽  
Outer Part ◽  
Late Summer ◽  
Field Work ◽  
The Arctic ◽  
Research Station ◽  
Fjord System ◽  
Sea Bottom ◽  
Satellite Radar ◽  
North Greenland

The marine record of the Independence–Danmark fjord system extending out to the Wandel Hav in eastern North Greenland (Fig. 1A) is little known due to the almost perennial sea-ice cover, which makes the region inaccessible for research vessels (Nørgaard-Pedersen et al. 2008), and only a few depth measurements have been conducted in the area. In 2015, the Villum Research Station, a new logistic base for scientific investigations, was opened at Station Nord. In contrast to the early exploration of the region, it is now possible to observe and track the seasonal character and changes of ice in the fjord system and the Arctic Ocean through remote sensing by satellite radar systems. Satellite data going back to the early 1980s show that the outer part of the Independence–Danmark fjord system is characterised by perennial sea ice whereas both the southern part of the fjord system and an area 20–30 km west of Station Nord are partly ice free during late summer (Fig. 1B). Hence, marine-orientated field work can be conducted from the sea ice using snow mobiles, and by drilling through the ice to reach the underlying water and sea bottom.

scholarly journals Sea Ice Concentration and Sea Ice Extent Mapping with L-Band Microwave Radiometry and GNSS-R Data from the FFSCat Mission Using Neural Networks

2021 ◽  
Vol 13 (6) ◽  
pp. 1139
Author(s):  
David Llaveria ◽  
Juan Francesc Munoz-Martin ◽  
Christoph Herbert ◽  
Miriam Pablos ◽  
Hyuk Park ◽  
...  
Keyword(s):  
Sea Ice ◽  
Microwave Radiometer ◽  
Cost Effective ◽  
The Arctic ◽  
Sea Ice Concentration ◽  
Sea Ice Extent ◽  
Neural Network Approach ◽  
Ice Concentration ◽  
L Band ◽  
Moderate Cost

CubeSat-based Earth Observation missions have emerged in recent times, achieving scientifically valuable data at a moderate cost. FSSCat is a two 6U CubeSats mission, winner of the ESA S3 challenge and overall winner of the 2017 Copernicus Masters Competition, that was launched in September 2020. The first satellite, 3Cat-5/A, carries the FMPL-2 instrument, an L-band microwave radiometer and a GNSS-Reflectometer. This work presents a neural network approach for retrieving sea ice concentration and sea ice extent maps on the Arctic and the Antarctic oceans using FMPL-2 data. The results from the first months of operations are presented and analyzed, and the quality of the retrieved maps is assessed by comparing them with other existing sea ice concentration maps. As compared to OSI SAF products, the overall accuracy for the sea ice extent maps is greater than 97% using MWR data, and up to 99% when using combined GNSS-R and MWR data. In the case of Sea ice concentration, the absolute errors are lower than 5%, with MWR and lower than 3% combining it with the GNSS-R. The total extent area computed using this methodology is close, with 2.5% difference, to those computed by other well consolidated algorithms, such as OSI SAF or NSIDC. The approach presented for estimating sea ice extent and concentration maps is a cost-effective alternative, and using a constellation of CubeSats, it can be further improved.

scholarly journals Pan-Arctic aerosol number size distributions: seasonality and transport patterns

2017 ◽  
Vol 17 (13) ◽  
pp. 8101-8128 ◽  
Author(s):  
Eyal Freud ◽  
Radovan Krejci ◽  
Peter Tunved ◽  
Richard Leaitch ◽  
Quynh T. Nguyen ◽  
...  
Keyword(s):  
Arctic Ocean ◽  
Regional Scale ◽  
Arctic Region ◽  
The Arctic ◽  
Research Station ◽  
Size Distributions ◽  
Back Trajectories ◽  
Accumulation Mode ◽  
Source Regions ◽  
The Arctic Ocean

Abstract. The Arctic environment has an amplified response to global climatic change. It is sensitive to human activities that mostly take place elsewhere. For this study, a multi-year set of observed aerosol number size distributions in the diameter range of 10 to 500 nm from five sites around the Arctic Ocean (Alert, Villum Research Station – Station Nord, Zeppelin, Tiksi and Barrow) was assembled and analysed.A cluster analysis of the aerosol number size distributions revealed four distinct distributions. Together with Lagrangian air parcel back-trajectories, they were used to link the observed aerosol number size distributions with a variety of transport regimes. This analysis yields insight into aerosol dynamics, transport and removal processes, on both an intra- and an inter-monthly scale. For instance, the relative occurrence of aerosol number size distributions that indicate new particle formation (NPF) event is near zero during the dark months, increases gradually to  ∼ 40 % from spring to summer, and then collapses in autumn. Also, the likelihood of Arctic haze aerosols is minimal in summer and peaks in April at all sites.The residence time of accumulation-mode particles in the Arctic troposphere is typically long enough to allow tracking them back to their source regions. Air flow that passes at low altitude over central Siberia and western Russia is associated with relatively high concentrations of accumulation-mode particles (Nacc) at all five sites – often above 150 cm−3. There are also indications of air descending into the Arctic boundary layer after transport from lower latitudes.The analysis of the back-trajectories together with the meteorological fields along them indicates that the main driver of the Arctic annual cycle of Nacc, on the larger scale, is when atmospheric transport covers the source regions for these particles in the 10-day period preceding the observations in the Arctic. The scavenging of these particles by precipitation is shown to be important on a regional scale and it is most active in summer. Cloud processing is an additional factor that enhances the Nacc annual cycle.There are some consistent differences between the sites that are beyond the year-to-year variability. They are the result of differences in the proximity to the aerosol source regions and to the Arctic Ocean sea-ice edge, as well as in the exposure to free-tropospheric air and in precipitation patterns – to mention a few. Hence, for most purposes, aerosol observations from a single Arctic site cannot represent the entire Arctic region. Therefore, the results presented here are a powerful observational benchmark for evaluation of detailed climate and air chemistry modelling studies of aerosols throughout the vast Arctic region.

scholarly journals Arctic Sea Ice Retreat in 2007 Follows Thinning Trend

2009 ◽  
Vol 22 (1) ◽  
pp. 165-176 ◽  
Author(s):  
R. W. Lindsay ◽  
J. Zhang ◽  
A. Schweiger ◽  
M. Steele ◽  
H. Stern
Keyword(s):  
Sea Ice ◽  
Arctic Ocean ◽  
Ocean Model ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Ice Thickness ◽  
Sea Ice Extent ◽  
Pacific Side ◽  
Arctic Sea ◽  
The Arctic Ocean

Abstract The minimum of Arctic sea ice extent in the summer of 2007 was unprecedented in the historical record. A coupled ice–ocean model is used to determine the state of the ice and ocean over the past 29 yr to investigate the causes of this ice extent minimum within a historical perspective. It is found that even though the 2007 ice extent was strongly anomalous, the loss in total ice mass was not. Rather, the 2007 ice mass loss is largely consistent with a steady decrease in ice thickness that began in 1987. Since then, the simulated mean September ice thickness within the Arctic Ocean has declined from 3.7 to 2.6 m at a rate of −0.57 m decade−1. Both the area coverage of thin ice at the beginning of the melt season and the total volume of ice lost in the summer have been steadily increasing. The combined impact of these two trends caused a large reduction in the September mean ice concentration in the Arctic Ocean. This created conditions during the summer of 2007 that allowed persistent winds to push the remaining ice from the Pacific side to the Atlantic side of the basin and more than usual into the Greenland Sea. This exposed large areas of open water, resulting in the record ice extent anomaly.

scholarly journals Sea-ice induced growth decline in Arctic shrubs

2017 ◽  
Vol 13 (8) ◽  
pp. 20170122 ◽  
Author(s):  
Mads Forchhammer
Keyword(s):  
Sea Ice ◽  
Ring Width ◽  
Plant Productivity ◽  
Climatic Conditions ◽  
Arctic Sea Ice ◽  
Annual Growth ◽  
The Arctic ◽  
Growth Time ◽  
Sea Ice Extent ◽  
Negative Effect

Measures of increased tundra plant productivity have been associated with the accelerating retreat of the Arctic sea-ice. Emerging studies document opposite effects, advocating for a more complex relationship between the shrinking sea-ice and terrestrial plant productivity. I introduce an autoregressive plant growth model integrating effects of biological and climatic conditions for analysing individual ring-width growth time series. Using 128 specimens of Salix arctica , S. glauca and Betula nana sampled across Greenland to Svalbard, an overall negative effect of the retreating June sea-ice extent was found on the annual growth. The negative effect of the retreating June sea-ice was observed for younger individuals with large annual growth allocations and with little or no trade-off between previous and current year's growth.

scholarly journals Late-Twentieth-Century Simulation of Arctic Sea Ice and Ocean Properties in the CCSM4

2012 ◽  
Vol 25 (5) ◽  
pp. 1431-1452 ◽  
Author(s):  
Alexandra Jahn ◽  
Kara Sterling ◽  
Marika M. Holland ◽  
Jennifer E. Kay ◽  
James A. Maslanik ◽  
...  
Keyword(s):  
Twentieth Century ◽  
Sea Ice ◽  
Internal Variability ◽  
Ice Cover ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Motion Field ◽  
Sea Ice Extent ◽  
Arctic Sea ◽  
Ensemble Mean

To establish how well the new Community Climate System Model, version 4 (CCSM4) simulates the properties of the Arctic sea ice and ocean, results from six CCSM4 twentieth-century ensemble simulations are compared here with the available data. It is found that the CCSM4 simulations capture most of the important climatological features of the Arctic sea ice and ocean state well, among them the sea ice thickness distribution, fraction of multiyear sea ice, and sea ice edge. The strongest bias exists in the simulated spring-to-fall sea ice motion field, the location of the Beaufort Gyre, and the temperature of the deep Arctic Ocean (below 250 m), which are caused by deficiencies in the simulation of the Arctic sea level pressure field and the lack of deep-water formation on the Arctic shelves. The observed decrease in the sea ice extent and the multiyear ice cover is well captured by the CCSM4. It is important to note, however, that the temporal evolution of the simulated Arctic sea ice cover over the satellite era is strongly influenced by internal variability. For example, while one ensemble member shows an even larger decrease in the sea ice extent over 1981–2005 than that observed, two ensemble members show no statistically significant trend over the same period. It is therefore important to compare the observed sea ice extent trend not just with the ensemble mean or a multimodel ensemble mean, but also with individual ensemble members, because of the strong imprint of internal variability on these relatively short trends.

Mechanisms for and Predictability of a Drastic Reduction in the Arctic Sea Ice: APPOSITE Data with Climate Model MIROC

2019 ◽  
Vol 32 (5) ◽  
pp. 1361-1380 ◽  
Author(s):  
J. Ono ◽  
H. Tatebe ◽  
Y. Komuro
Keyword(s):  
Sea Ice ◽  
Climate Model ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Ensemble Prediction ◽  
Forecast Errors ◽  
Drastic Reduction ◽  
Sea Ice Concentration ◽  
Sea Ice Extent ◽  
Arctic Sea

Abstract The mechanisms for and predictability of a drastic reduction in the Arctic sea ice extent (SIE) are investigated using the Model for Interdisciplinary Research on Climate (MIROC) version 5.2. Here, a control (CTRL) with forcing fixed at year 2000 levels and perfect-model ensemble prediction (PRED) experiments are conducted. In CTRL, three (model years 51, 56, and 57) drastic SIE reductions occur during a 200-yr-long integration. In year 56, the sea ice moves offshore in association with a positive phase of the summer Arctic dipole anomaly (ADA) index and melts due to heat input through the increased open water area, and the SIE drastically decreases. This provides the preconditioning for the lowest SIE in year 57 when the Arctic Ocean interior is in a warm state and the spring sea ice volume has a large negative anomaly due to drastic ice reduction in the previous year. Although the ADA is one of the key mechanisms behind sea ice reduction, it does not always cause a drastic reduction. Our analysis suggests that wind direction favoring offshore ice motion is a more important factor for drastic ice reduction events. In years experiencing drastic ice reduction events, the September SIE can be skillfully predicted in PRED started from July, but not from April. This is because the forecast errors for the July sea level pressure and those for the sea ice concentration and sea ice thickness along the ice edge are large in PRED started from April.

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