Overview of the Antarctic Circumnavigation Expedition: Study of Preindustrial-like Aerosols and Their Climate Effects (ACE-SPACE)

Uncertainty in radiative forcing caused by aerosol–cloud interactions is about twice as large as for CO2 and remains the least well understood anthropogenic contribution to climate change. A major cause of uncertainty is the poorly quantified state of aerosols in the pristine preindustrial atmosphere, which defines the baseline against which anthropogenic effects are calculated. The Southern Ocean is one of the few remaining near-pristine aerosol environments on Earth, but there are very few measurements to help evaluate models. The Antarctic Circumnavigation Expedition: Study of Preindustrial-like Aerosols and their Climate Effects (ACE-SPACE) took place between December 2016 and March 2017 and covered the entire Southern Ocean region (Indian, Pacific, and Atlantic Oceans; length of ship track >33,000 km) including previously unexplored areas. In situ measurements covered aerosol characteristics [e.g., chemical composition, size distributions, and cloud condensation nuclei (CCN) number concentrations], trace gases, and meteorological variables. Remote sensing observations of cloud properties, the physical and microbial ocean state, and back trajectory analyses are used to interpret the in situ data. The contribution of sea spray to CCN in the westerly wind belt can be larger than 50%. The abundance of methanesulfonic acid indicates local and regional microbial influence on CCN abundance in Antarctic coastal waters and in the open ocean. We use the in situ data to evaluate simulated CCN concentrations from a global aerosol model. The extensive, available ACE-SPACE dataset (https://zenodo.org/communities/spi-ace?page=1&size=20) provides an unprecedented opportunity to evaluate models and to reduce the uncertainty in radiative forcing associated with the natural processes of aerosol emission, formation, transport, and processing occurring over the pristine Southern Ocean.

Exploring the coupled ocean and atmosphere system with a data science approach applied to observations from the Antarctic Circumnavigation Expedition

Andrea Baccarini, Irina Gorodetskaya, Christel Sybille Hassler, Sebastian Johannes Heinz-Josef Landwehr, Katherine Colby Leonard, Robin Lewis Modini, Fernando Perez Cruz, Julia Schmale, Jenny Thomas

The Southern Ocean is a critical component of Earth's climate system, but its remoteness makes it challenging to develop a holistic understanding of its processes from the small scale to the large scale. As a result, our knowledge of this vast region remains largely incomplete. The Antarctic Circumnavigation Expedition (ACE, austral summer 2016/2017) surveyed a large number of variables describing the state of the ocean and the atmosphere, the freshwater cycle, atmospheric chemistry, and ocean biogeochemistry and microbiology. This circumpolar cruise included visits to 12 remote islands, the marginal ice zone, and the Antarctic coast. Here, we use 111 of the observed variables to study the latitudinal gradients, seasonality, shorter-term variations, geographic setting of environmental processes, and interactions between them over the duration of 90 d. To reduce the dimensionality and complexity of the dataset and make the relations between variables interpretable we applied an unsupervised machine learning method, the sparse principal component analysis (sPCA), which describes environmental processes through 14 latent variables. To derive a robust statistical perspective on these processes and to estimate the uncertainty in the sPCA decomposition, we have developed a bootstrap approach. Our results provide a proof of concept that sPCA with uncertainty analysis is able to identify temporal patterns from diurnal to seasonal cycles, as well as geographical gradients and “hotspots” of interaction between environmental compartments. While confirming many well known processes, our analysis provides novel insights into the Southern Ocean water cycle (freshwater fluxes), trace gases (interplay between seasonality, sources, and sinks), and microbial communities (nutrient limitation and island mass effects at the largest scale ever reported). More specifically, we identify the important role of the oceanic circulations, frontal zones, and islands in shaping the nutrient availability that controls biological community composition and productivity; the fact that sea ice controls sea water salinity, dampens the wave field, and is associated with increased phytoplankton growth and net community productivity possibly due to iron fertilisation and reduced light limitation; and the clear regional patterns of aerosol characteristics that have emerged, stressing the role of the sea state, atmospheric chemical processing, and source processes near hotspots for the availability of cloud condensation nuclei and hence cloud formation. A set of key variables and their combinations, such as the difference between the air and sea surface temperature, atmospheric pressure, sea surface height, geostrophic currents, upper-ocean layer light intensity, surface wind speed and relative humidity played an important role in our analysis, highlighting the necessity for Earth system models to represent them adequately. In conclusion, our study highlights the use of sPCA to identify key ocean–atmosphere interactions across physical, chemical, and biological processes and their associated spatio-temporal scales. It thereby fills an important gap between simple correlation analyses and complex Earth system models. The sPCA processing code is available as open-access from the following link: https://renkulab.io/gitlab/ACE-ASAID/spca-decomposition (last access: 29 March 2021). As we show here, it can be used for an exploration of environmental data that is less prone to cognitive biases (and confirmation biases in particular) compared to traditional regression analysis that might be affected by the underlying research question.

2021

Aerosol Transport and Distribution

Quentin Bourgeois

The fourth report of the Intergovernmental Panel of Climate Change (IPCC) unambiguously indicates that the climate is changing. Climate change is induced by changes in atmospheric abundances of greenhouse gases and aerosols, solar radiation and land surface properties, which all alter the radiative balance of the Earth. Among them, greenhouse gases and aerosols are likely the compounds affecting the climate the most. While greenhouse gases warm the Earth, aerosols influence its radiative balance by scattering and absorbing solar radiation (the direct effect), and by modifying cloud amount and properties (the indirect effect). The radiative forcing of aerosols on the climate is however the less understood among the various forcings currently considered in the IPCC assessment. This is likely related to the lack of comprehensive and accurate observations of aerosols (and in particular of their vertical distribution) which thus makes global aerosol models difficult to constrain. Recent model intercomparisons have indicated that different assumptions regarding aerosol emissions, formation and growing properties, and removal processes generate large diversities within models. These large diversities are found in particular in the Arctic and the upper troposphere region where extreme surrounding conditions take place, limiting instrument sensitivity and accuracy. The objectives of this thesis are to better quantify the processes driving the aerosol distribution in regions where the uncertainties are the largest, including the Arctic region and the upper troposphere, and to assess the quality of CALIOP observations. For this purpose, we used the fully coupled global climate-aerosol-chemistry ECHAM5-HAMMOZ model conjointly with a suite of remote sensing observations including the CALIOP satellite instrument, which provides the vertical distribution of aerosols. The model predicts the size distribution and composition of aerosols as well as the number concentration of cloud droplets and ice crystals. We first investigated the processes that drive the transport of soluble and insoluble compounds toward the Arctic in the ECHAM5-HAMMOZ model. Recognizing that scavenging processes may be an issue in global models, we "re-visited" their properties in ECHAM5-HAMMOZ. We find that the model better reproduces the aerosol vertical distribution in the northern mid- and high-latitudes, especially in the free troposphere, by decreasing aerosol scavenging coefficients in the model. Using smaller aerosol scavenging coefficients results in an increase of aerosol burden and lifetime, especially in the Arctic. In addition, the Arctic haze phenomenon is better represented in the simulation using decreased aerosol scavenging coefficients. The relative contributions of different processes governing the transport of aerosols from the midlatitudes toward the Arctic together with the relative contributions of different geopolitical source regions were then quantified. We find that Europe and Siberia contribute the most to the Arctic pollution even though Asian anthropogenic emissions are much larger. The model suggests that BC emitted in Siberia and Europe is ten times more efficiently deposited onto the Arctic than BC emitted in Asia. We next investigated an aerosol layer that forms in the vicinity of the tropical tropopause layer (TTL) over the southern Asian and Indian Ocean region. Aerosols in this layer are observed with the CALIOP instrument even though ice clouds partly mask their signal. The aerosol layer follows the Inter Tropical Convergence Zone (ITCZ), which indicates that these aerosols are likely transported during convective processes. The ECHAM5.5-HAM2 model reproduces such an aerosol layer in the TTL over the same region but clearly overestimates CALIOP data. Model results suggest that aerosols in this layer are mostly sulfate particles transported during convective processes and originating from natural sources. The shortwave forcing of this aerosol layer is estimated. Finally, we assessed the accuracy of aerosol extinction retrievals from the CALIOP satellite instrument by comparing them with remote sensing observations such as AERONET, MODIS and MISR over the last four years. Overall, standard CALIOP products underestimate by 50% observed aerosol extinctions. However, this comparison is substantially improved by screening CALIOP data. The comparison of the CALIOP screened product with the ECHAM5.5-HAM2 model shows large disparities in model results. The model reproduces quite well the observed interannual variability and vertical distribution of aerosols in Europe and North Africa while it underestimates them in America and Asia. This is likely due to an underestimate of dust and anthropogenic emissions in North America and Asia.

EPFL2012

Iodine Drives New Particle Formation in the Central Arctic Ocean

Andrea Baccarini, Julia Schmale

The Arctic is warming faster than Earth on average (Arctic amplification) and the extent of the sea ice coverage has decreased dramatically over the past decades, especially in summer. However, the underlying processes behind this amplification are not well understood because of many feedback mechanisms between the ocean, the atmosphere and the cryosphere. Clouds are an important player in the Arctic radiative budget, as they almost always have a net surface warming effect. However, models struggle to reproduce Arctic clouds partly because aerosol processes and aerosol sources in this area are poorly understood. This is particularly true in the central Arctic Ocean where aerosols can reach extremely low concentrations and clouds may even become limited by cloud condensation nuclei (CCN) availability. New particle formation (NPF) has been identified as a potential source of CCN in this region, and a modelling study showed that NPF is needed to explain the observed Aitken mode particle concentration. However, no conclusive results were reported concerning the nature of these NPF events and the chemical composition of the nucleating vapours. In this contribution we present the first comprehensive physicochemical characterization of several NPF events in the central Arctic Ocean during the Arctic Ocean 2018 expedition. We identified a marked increase of the iodic acid concentration towards the end of the summer, potentially associated with the onset of the freeze-up season and a concurrent increase of the ozone concentration. Moreover, our results indicate that iodic acid is a main driver for the formation of new particles and their early growth. The frequency of new particle formation events follows the same seasonal trend as the ultrafine particle concentration, which is one order of magnitude higher in fall compared to summer. In addition, we developed a simple parametrization that describes iodic acid variability, providing an estimate of the iodine precursor emission rates. Finally, we also provide direct evidences that Aitken mode particles activate as cloud condensation nuclei suggesting that iodine NPF can influence the formation of clouds and their properties in the central Arctic.

2020