Cloud observations over the past decade from six Arctic atmospheric observatories are investigated to derive estimates of cloud occurrence fraction, vertical distribution, persistence in time, diurnal cycle, and boundary statistics. Each observatory has some combination of cloud lidar, radar, ceilometer, and/or interferometer for identifying and characterizing clouds. By optimally combining measurements from these instruments, it is found that annual cloud occurrence fractions are 58%-83% at the Arctic observatories. There is a clear annual cycle wherein clouds are least frequent in the winter and most frequent in the late summer and autumn. Only in Eureka, Nunavut, Canada, is the annual cycle shifted such that the annual minimum is in the spring with the maximum in the winter. Intersite monthly variability is typically within 10%-15% of the all-site average. Interannual variability at specific sites is less than 13% for any given month and, typically, is less than 3% for annual total cloud fractions. Low-level clouds are most persistent at the observatories. The median cloud persistence for all observatories is 3-5 h; however, 5% of cloud systems at far western Arctic sites are observed to occur for longer than 100 consecutive hours. Weak diurnal variability in cloudiness is observed at some sites, with a daily minimum in cloud occurrence near solar noon for those seasons for which the sun is above the horizon for at least part of the day.

Abstract. Several types of filter-based instruments are used to estimate aerosol light absorption coefficients. Two significant results are presented based on Aethalometer measurements at six Arctic stations from 2012 to 2014. First, an alternative method of post-processing the Aethalometer data is presented, which reduces measurement noise and lowers the detection limit of the instrument more effectively than boxcar averaging. The biggest benefit of this approach can be achieved if instrument drift is minimised. Moreover, by using an attenuation threshold criterion for data post-processing, the relative uncertainty from the electronic noise of the instrument is kept constant. This approach results in a time series with a variable collection time ( t) but with a

The Arctic is a sentinel of global change. This region is influenced by multiple physical and socio-economic drivers and feedbacks, impacting both the natural and human environment. Air pollution is one such driver that impacts Arctic climate change, ecosystems and health but significant uncertainties still surround quantification of these effects. Arctic air pollution includes harmful trace gases (e.g. tropospheric ozone) and particles (e.g. black carbon, sulphate) and toxic substances (e.g. polycyclic aromatic hydrocarbons) that can be transported to the Arctic from emission sources located far outside the region, or emitted within the Arctic from activities including shipping, power production, and other industrial activities. This paper qualitatively summarizes the complex science issues motivating the creation of a new international initiative, PACES (air Pollution in the Arctic: Climate, Environment and Societies). Approaches for coordinated, international and interdisciplinary research on this topic are described with the goal to improve predictive capability via new understanding about sources, processes, feedbacks and impacts of Arctic air pollution. Overarching research actions are outlined, in which we describe our recommendations for 1) the development of trans-disciplinary approaches combining social and economic research with investigation of the chemical and physical aspects Arctic air pollution: Challenges and opportunities for the next decade of Arctic air pollution; 2) increasing the quality and quantity of observations in the Arctic using long-term monitoring and intensive field studies, both at the surface and throughout the troposphere; and 3) developing improved predictive capability across a range of spatial and temporal scales. Domain Editor-in-Chief

Abstract. Given the sensitivity of the Arctic climate to short-lived climate forcers, long-term in situ surface measurements of aerosol parameters are useful in gaining insight into the magnitude and variability of these climate forcings. Seasonality of aerosol optical properties -including the aerosol light-scattering coefficient, absorption coefficient, single-scattering albedo, scattering Ångström exponent, and asymmetry parameter -are presented for six monitoring sites throughout the Arctic: Alert, Canada; Barrow, USA; Pallas, Finland; Summit, Greenland; Tiksi, Russia; and Zeppelin Mountain, Ny-Ålesund, Svalbard, Norway. Results show annual variability in all parameters, though the seasonality of each aerosol optical property varies from site to site. There is a large diversity in magnitude and variability of scattering coefficient at all sites, reflecting differences in aerosol source, transport, and removal at different locations throughout the Arctic. Of the Arctic sites, the highest annual mean scattering coefficient is measured at Tiksi (12.47 Mm −1 ), and the lowest annual mean scattering coefficient is measured at Summit (1.74 Mm −1 ). At most sites, aerosol absorption peaks in the winter and spring, and has a minimum throughout the Arctic in the summer, indicative of the Arctic haze phenomenon; however, nuanced variations in seasonalities suggest that this phenomenon is not identically observed in all regions of the Arctic. The highest annual mean absorption coefficient is measured at Pallas (0.48 Mm −1 ), and Summit has the lowest annual mean absorption coefficient (0.12 Mm −1 ). At the Arctic monitoring stations analyzed here, mean annual single-scattering albedo ranges from 0.909 (at Pallas) to 0.960 (at Barrow), the mean annual scattering Ångström exponent ranges from 1.04 (at Barrow) to 1.80 (at Summit), and the mean asymmetry parameter ranges from 0.57 (at Alert) to 0.75 (at Summit). Systematic variability of aerosol optical properties in the Arctic supports the notion that the sites presented here measure a variety of aerosol populations, which also experience different removal mechanisms. A robust conclusion from the seasonal cycles presented is that the Arctic cannot be treated as one common and uniform environment but rather is a region with ample spatiotemporal variability in aerosols. This notion is important in considering the design or aerosol monitoring networks in the region and is important for informing climate models to better represent short-lived aerosol climate forcers in order to yield more accurate climate predictions for the Arctic.

48Recent studies suggest that the atmosphere conditions Arctic sea-ice properties in spring in 49 a way that may be an important factor in predetermining autumn sea ice concentrations. 50Here, the role of clouds in this system is analyzed using surface-based observations from 51Barrow, Alaska. Barrow is a coastal location situated adjacent to the region where 52interannual sea ice variability is largest. Barrow is also along a main transport pathway 53 through which springtime advection of atmospheric energy from lower latitudes to the 54Arctic Ocean occurs. The cloud contribution is quantified using the observed surface 55 radiative fluxes and cloud radiative forcing (CRF) derived therefrom, which can be positive 56 or negative. In low sea ice years enhanced positive CRF (increased cloud cover enhancing 57longwave forcing) in April is followed by decreased negative CRF (decreased cloud cover 58 allowing a relative increase in shortwave forcing) in May and June. The opposite is true in 59 high sea ice years. In either case, the combination and timing of these early and late spring 60 cloud radiative processes can serve to enhance the atmospheric preconditioning of sea ice. 61The net CRF (April and May) measured at Barrow from 1993 through 2014 is negatively 62 correlated with sea ice extent in the following autumn (r 2 = 0.33, p < 0.01). Reanalysis data 63 appears to capture the general timing and sign of the observed CRF anomalies at Barrow 64 and suggests that the anomalies occur over a large region of the central Arctic Ocean, which 65supports the link between radiative processes observed at Barrow and the broader Arctic 66 sea ice extent.

G lobal climate change is visibly and tangibly manifested through the Arctic cryospheric system: sea ice loss, earlier spring snowmelts, thawing permafrost, retreating glaciers, and coastal erosion. While not as visibly manifest, the role of the atmosphere is also a critical component in determining the trajectory of the Arctic system. The atmosphere not only drives change, but is reciprocally being modified through a complex web of feedbacks, and is the fast-track mechanism for the transport of energy and moisture through the global system that links climate and weather. For decades, it has been recognized that fundamental components of the atmospheric system such as clouds, atmospheric trace gases, aerosols, and atmosphere-surface exchange processes compose some of the major uncertainties that limit the diagnostic or predictive skill of coupled atmosphere-ice-ocean-terrestrial models (IPCC 2013, chapter 9). Arctic nations have responded in recent decades by establishing  A micrometeorological tower in Tiksi, Russia is used to determine the atmospheric-surface energy balance. (Photo credit: Vasily Kustov)

Given the sensitivity of the Arctic climate to short-lived climate forcers, long-term in-situ surface measurements of aerosol parameters are useful in gaining insight into the magnitude and variability of these climate forcings. Systematic variability of aerosol optical properties in the Arctic supports the notion that the sites presented here 40 measure a variety of aerosol populations, which also experience different removal mechanisms. A robust conclusion from the seasonal cycles presented is that the Arctic cannot be treated as one common and uniform environment, but 2 rather is a region with ample spatio-temporal variability in aerosols. This notion is important in considering the design or aerosol monitoring networks in the region, and is important for informing climate models to better represent short-lived aerosol climate forcers in order to yield more accurate climate predictions for the Arctic.

Rapid Arctic warming drives profound change in the marine environment that have significant socio-economic impacts within the Arctic and beyond, including climate and weather hazards, food security, transportation, infrastructure planning and resource extraction. These concerns drive efforts to understand and predict Arctic environmental change and motivate development of an Arctic Region Component of the Global Ocean Observing System (ARCGOOS) capable of collecting the broad, sustained observations needed to support these endeavors. This paper provides a roadmap for establishing the ARCGOOS. ARCGOOS development must be underpinned by a broadly endorsed framework grounded in high-level policy drivers and the scientific and operational objectives that stem from them. This should be guided by a transparent, internationally accepted governance structure with recognized authority and organizational relationships with the national agencies that ultimately execute network plans. A governance model for ARCGOOS must guide selection of objectives, assess performance and fitness-to-purpose, and advocate for resources. A requirements-based framework for an ARCGOOS begins with the Societal Benefit