Abstract. Understanding the rapidly changing climate in the Arctic is limited by a lack of understanding of underlying strong feedback mechanisms that are specific to the Arctic. Progress in this field can only be obtained by process-level observations; this is the motivation for intensive ice-breakerbased campaigns such as the Arctic Summer Cloud-Ocean Study (ASCOS), described here. However, detailed field observations also have to be put in the context of the largerscale meteorology, and short field campaigns have to be analysed within the context of the underlying climate state and temporal anomalies from this.To aid in the analysis of other parameters or processes observed during this campaign, this paper provides an overview of the synoptic-scale meteorology and its climatic anomaly during the ASCOS field deployment. It also provides a statistical analysis of key features during the campaign, such as key meteorological variables, the vertical structure of the lower troposphere and clouds, and energy fluxes at the surface. In order to assess the representativity of the ASCOS results, we also compare these features to similar observations obtained during three earlier summer experiments in the Arctic Ocean: the AOE-96, SHEBA and AOE-2001 expeditions.We find that these expeditions share many key features of the summertime lower troposphere. Taking ASCOS and the previous expeditions together, a common picture emerges with a large amount of low-level cloud in a well-mixed shallow boundary layer, capped by a weak to moderately strong inversion where moisture, and sometimes also cloud top, penetrate into the lower parts of the inversion. Much of the boundary-layer mixing is due to cloud-top cooling and subsequent buoyant overturning of the cloud. The cloud layer may, or may not, be connected with surface processes depending on the depths of the cloud and surface-based boundary layers and on the relative strengths of surface-shear and cloud-generated turbulence. The latter also implies a connection between the cloud layer and the free troposphere through entrainment at cloud top.

S1 Solutions from positive matrix factorisa-1 tion 2 For this study, a four factor solution was determined to best represent the 3 measured aerosol. A two factor solution separates the Ship Emissions factor 4 from the ambient background aerosol, while a three factor solution includes 5 the Organic factor. It is only with four factors that the Marine Biogenic 6 factor is separated from the Continental factor. Additional factors either 7 identify instrumental noise, or split the existing factors. Figure S1 shows 8 the decrease in Q/Q exp as additional factors are included, where Q exp is 9 the expected Q. We see that including a 5 th factor decreases Q/Q exp by 10 identifying instrumental noise, while additional factors only serve to capture 11 episodic events, often coinciding with ship emissions. Even though Q/Q exp 12 decreased slightly from 3.36 for four factors down to 3.06 for 10 factors, 13 including more factors did not contribute additional information about the 14 measured aerosol. As such, the four factor solution was deemed to give the 15 most information about the measured ambient aerosol. 16 The robustness of the solution can be explored by either varying the initial 17 seed, which changes the set of pseudorandom values used for the initial point 18 (Paatero, 1997), or by using bootstrapping analysis, in which the rows of X 19 are randomly sampled and PMF is executed on the new dataset (as described 20 by Reff et al., 2007). Both of these methods were used and the four factor 21 solution at fPeak =-0.75 was found to be robust: 100 values for the initial 22 seed parameter in the PMF2 program resulted in 90 of the cases giving the 23 solution presented here, while 100 iterations of the bootstrapping analysis 24 S1

Abstract. The change in aerosol properties during the transition from the more polluted spring to the clean summer in the Arctic troposphere was studied. A six-year data set of observations from Ny-Ålesund on Svalbard, covering the months April through June, serve as the basis for the characterisation of this time period. In addition four-day-back trajectories were used to describe air mass histories. The observed transition in aerosol properties from an accumulationmode dominated distribution to an Aitken-mode dominated distribution is discussed with respect to long-range transport and influences from natural and anthropogenic sources of aerosols and pertinent trace gases. Our study shows that the air-mass transport is an important factor modulating the physical and chemical properties observed. However, the airmass transport cannot alone explain the annually repeated systematic and rather rapid change in aerosol properties, occurring within a limited time window of approximately 10 days. With a simplified phenomenological model, which delivers the nucleation potential for new-particle formation, we suggest that the rapid shift in aerosol microphysical properties between the Arctic spring and summer is mainly driven by the incoming solar radiation in concert with transport of precursor gases and changes in condensational sink.

Abstract. This paper describes the background, instrumentation, goals, and the regional influences on the HUMPPA-COPEC intensive field measurement campaign, conducted at the Boreal forest research station SMEAR II (Station for Measuring Ecosystem-Atmosphere Relation) in Hyytiälä, Finland from 12 July-12 August 2010. The prevailing meteorological conditions during the campaign are examined and contrasted with those of the past six years. Back trajectory analyses show that meteorological conditions at the site in 2010 were characterized by a higher proportion of southerly flow than in the other years studied. As a result the summer Correspondence to: J. Williams (jonathan.williams@mpic.de) of 2010 was anomalously warm and high in ozone making the campaign relevant for the analysis of possible future climates. A comprehensive land use analysis, provided on both 5 and 50 km scales, shows that the main vegetation types surrounding the site on both the regional and local scales are: coniferous forest (Scots pine and/or Norway spruce); mixed forest (Birch and conifers); and woodland scrub (e.g. Willows, Aspen); indicating that the campaign results can be taken as representative of the Boreal forest ecosystem. In addition to the influence of biogenic emissions, the measurement site was occasionally impacted by sources other than vegetation. Specific tracers have been used here to identify the time periods when such sources have impacted the site namely: biomass burning (acetonitrile and CO), urbanPublished by Copernicus Publications on behalf of the European Geosciences Union. 10600 J. Williams et al.: An overview of meteorological and chemical influences anthropogenic pollution (pentane and SO 2 ) and the nearby Korkeakoski sawmill (enantiomeric ratio of chiral monoterpenes). None of these sources dominated the study period, allowing the Boreal forest summertime emissions to be assessed and contrasted with various other source signatures.

Abstract. In this study the ion production rates in a boreal forest were studied based on two different methods: 1) cluster ion and particle concentration measurements, 2) external radiation and radon concentration measurements. Both methods produced reasonable estimates for ion production rates. The average ion production rate calculated from aerosol particle size distribution and air ion mobility distribution measurements was 2.6 ion pairs cm −3 s −1 , and based on external radiation and radon measurements, 4.5 ion pairs cm −3 s −1 . The first method based on ion and particle measurements gave lower values for the ion production rates especially during the day. A possible reason for this is that particle measurements started only from 3 nm, so the sink of small ions during the nucleation events was underestimated. It may also be possible that the hygroscopic growth factors of aerosol particles were underestimated. Another reason for the discrepancy is the nucleation mechanism itself. If the ions are somehow present in the nucleation process, there could have been an additional ion sink during the nucleation days.