Characteristics and sources of fluorescent aerosols in the central Arctic Ocean

The Arctic is sensitive to cloud radiative forcing. Due to the limited number of aerosols present throughout much of the year, cloud formation is susceptible to the presence of cloud condensation nuclei and ice nucleating particles (INPs). Primary biological aerosol particles (PBAP) contribute to INPs and can impact cloud phase, lifetime, and radiative properties. We present yearlong observations of hyperfluorescent aerosols (HFA), tracers for PBAP, conducted with a Wideband Integrated Bioaerosol Sensor, New Electronics Option during the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition (October 2019–September 2020) in the central Arctic. We investigate the influence of potential anthropogenic and natural sources on the characteristics of the HFA and relate our measurements to INP observations during MOSAiC. Anthropogenic sources influenced HFA during the Arctic haze period. But surprisingly, we also found sporadic “bursts” of HFA with the characteristics of PBAP during this time, albeit with unclear origin. The characteristics of HFA between May and August 2020 and in October 2019 indicate a strong contribution of PBAP to HFA. Notably from May to August, PBAP coincided with the presence of INPs nucleating at elevated temperatures, that is, &amp;gt;−9°C, suggesting that HFA contributed to the “warm INP” concentration. The air mass residence time and area between May and August and in October were dominated by the open ocean and sea ice, pointing toward PBAP sources from within the Arctic Ocean. As the central Arctic changes drastically due to climate warming with expected implications on aerosol–cloud interactions, we recommend targeted observations of PBAP that reveal their nature (e.g., bacteria, diatoms, fungal spores) in the atmosphere and in relevant surface sources, such as the sea ice, snow on sea ice, melt ponds, leads, and open water, to gain further insights into the relevant source processes and how they might change in the future.</jats:p

Heatwave responses of Arctic phytoplankton communities are driven by combined impacts of warming and cooling.

Marine heatwaves are increasing in frequency and intensity as climate change progresses, especially in the highly productive Arctic regions. Although their effects on primary producers will largely determine the impacts on ecosystem services, mechanistic understanding on phytoplankton responses to these extreme events is still very limited. We experimentally exposed Arctic phytoplankton assemblages to stable warming, as well as to repeated heatwaves, and measured temporally resolved productivity, physiology, and composition. Our results show that even extreme stable warming increases productivity, while the response to heatwaves depends on the specific scenario applied and is not predictable from stable warming responses. This appears to be largely due to the underestimated impact of the cool phase following a heatwave, which can be at least as important as the warm phase for the overall response. We show that physiological and compositional adjustments to both warm and cool phases drive overall phytoplankton productivity and need to be considered mechanistically to predict overall ecosystem impacts

Arctic sea ice algae differ markedly from phytoplankton in their ecophysiological characteristics

Photophysiological and biochemical characteristics were investigated in natural communities of Arctic sea ice algae and phytoplankton to understand their respective responses towards variable irradiance and nutrient regimes. This study revealed large differences in photosynthetic efficiency and capacity between the 2 types of algal assemblages. Sea ice algal assemblages clearly displayed increased photoprotective energy dissipation under the highest daily average irradiance levels (>8 µmol photons m-2 s-1). In contrast, phytoplankton assemblages were generally light-limited within the same irradiance ranges. Furthermore, phytoplankton assemblages exhibited more efficient carbon assimilation rates in the low irradiance range compared to sea ice algae, possibly explaining the ability of phytoplankton to generate substantial under-ice blooms. They were also able to readily adjust and increase their carbon production to higher irradiances. The Arctic is warming more rapidly than any other oceanic region on the planet, and as a consequence, irradiance levels experienced by microalgae are expected to increase due to declining ice thickness and snow cover, as well as enhanced stratification. The results of this study suggest that sea ice algae may have less capacity to adapt to the expected environmental changes compared to phytoplankton. We therefore anticipate a change in sea ice-based vs. pelagic primary production with respect to timing and quantity in a future Arctic. The clearly distinct responses of sea ice algae vs. phytoplankton need to be incorporated into model scenarios of current and future Arctic algal blooms and considered when predicting implications for the entire ecosystem and associated biogeochemical fluxes

Annual cycle observations of aerosols capable of ice formation in central Arctic clouds.

The Arctic is warming faster than anywhere else on Earth, prompting glacial melt, permafrost thaw, and sea ice decline. These severe consequences induce feedbacks that contribute to amplified warming, affecting weather and climate globally. Aerosols and clouds play a critical role in regulating radiation reaching the Arctic surface. However, the magnitude of their effects is not adequately quantified, especially in the central Arctic where they impact the energy balance over the sea ice. Specifically, aerosols called ice nucleating particles (INPs) remain understudied yet are necessary for cloud ice production and subsequent changes in cloud lifetime, radiative effects, and precipitation. Here, we report observations of INPs in the central Arctic over a full year, spanning the entire sea ice growth and decline cycle. Further, these observations are size-resolved, affording valuable information on INP sources. Our results reveal a strong seasonality of INPs, with lower concentrations in the winter and spring controlled by transport from lower latitudes, to enhanced concentrations of INPs during the summer melt, likely from marine biological production in local open waters. This comprehensive characterization of INPs will ultimately help inform cloud parameterizations in models of all scales

The MOSAiC Distributed Network: Observing the coupled Arctic system with multidisciplinary, coordinated platforms

Central Arctic properties and processes are important to the regional and global coupled climate system. The Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) Distributed Network (DN) of autonomous ice-tethered systems aimed to bridge gaps in our understanding of temporal and spatial scales, in particular with respect to the resolution of Earth system models. By characterizing variability around local measurements made at a Central Observatory, the DN covers both the coupled system interactions involving the ocean-ice-atmosphere interfaces as well as three-dimensional processes in the ocean, sea ice, and atmosphere. The more than 200 autonomous instruments (“buoys”) were of varying complexity and set up at different sites mostly within 50 km of the Central Observatory. During an exemplary midwinter month, the DN observations captured the spatial variability of atmospheric processes on sub-monthly time scales, but less so for monthly means. They show significant variability in snow depth and ice thickness, and provide a temporally and spatially resolved characterization of ice motion and deformation, showing coherency at the DN scale but less at smaller spatial scales. Ocean data show the background gradient across the DN as well as spatially dependent time variability due to local mixed layer sub-mesoscale and mesoscale processes, influenced by a variable ice cover. The second case (May–June 2020) illustrates the utility of the DN during the absence of manually obtained data by providing continuity of physical and biological observations during this key transitional period. We show examples of synergies between the extensive MOSAiC remote sensing observations and numerical modeling, such as estimating the skill of ice drift forecasts and evaluating coupled system modeling. The MOSAiC DN has been proven to enable analysis of local to mesoscale processes in the coupled atmosphere-ice-ocean system and has the potential to improve model parameterizations of important, unresolved processes in the future.</jats:p