Julia Schmale

Dr. Julia Schmale


Research Focus & Metrics

Academic Career Length

19Years (2008-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

View All Publications
8 February 2021 in Nature Climate Change
Verified
Journal Article
Closed access
PDF file
JSJulia Schmale
Julia Schmale
PZPaul Zieger
Paul Zieger
AEAnnica M. L. Ekman
Annica M. L. Ekman

7 February 2022 in Elementa: Science of the Anthropocene
Verified
Journal Article
Open access
PDF file
MSMatthew D. Shupe
Matthew D. Shupe
MRMarkus Rex
Markus Rex
BBByron Blomquist
Byron Blomquist
PPP. Ola G. Persson
P. Ola G. Persson
JSJulia Schmale
Julia Schmale
FYFange Yue
Fange Yue
With the Arctic rapidly changing, the needs to observe, understand, and model the changes are essential. To support these needs, an annual cycle of observations of atmospheric properties, processes, and interactions were made while drifting with the sea ice across the central Arctic during the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition from October 2019 to September 2020. An international team designed and implemented the comprehensive program to document and characterize all aspects of the Arctic atmospheric system in unprecedented detail, using a variety of approaches, and across multiple scales. These measurements were coordinated with other observational teams to explore cross-cutting and coupled interactions with the Arctic Ocean, sea ice, and ecosystem through a variety of physical and biogeochemical processes. This overview outlines the breadth and complexity of the atmospheric research program, which was organized into 4 subgroups: atmospheric state, clouds and precipitation, gases and aerosols, and energy budgets. Atmospheric variability over the annual cycle revealed important influences from a persistent large-scale winter circulation pattern, leading to some storms with pressure and winds that were outside the interquartile range of past conditions suggested by long-term reanalysis. Similarly, the MOSAiC location was warmer and wetter in summer than the reanalysis climatology, in part due to its close proximity to the sea ice edge. The comprehensiveness of the observational program for characterizing and analyzing atmospheric phenomena is demonstrated via a winter case study examining air mass transitions and a summer case study examining vertical atmospheric evolution. Overall, the MOSAiC atmospheric program successfully met its objectives and was the most comprehensive atmospheric measurement program to date conducted over the Arctic sea ice. The obtained data will support a broad range of coupled-system scientific research and provide an important foundation for advancing multiscale modeling capabilities in the Arctic.

1 October 2020 in Nature Communications
Verified
Journal Article
Open access
PDF file
ABAndrea Baccarini
Andrea Baccarini
LKLinn Karlsson
Linn Karlsson
JDJosef Dommen
Josef Dommen
PDPatrick Duplessis
Patrick Duplessis
JVJutta Vüllers
Jutta Vüllers
JSJulia Schmale
Julia Schmale
In the central Arctic Ocean the formation of clouds and their properties are sensitive to the availability of cloud condensation nuclei (CCN). The vapors responsible for new particle formation (NPF), potentially leading to CCN, have remained unidentified since the first aerosol measurements in 1991. Here, we report that all the observed NPF events from the Arctic Ocean 2018 expedition are driven by iodic acid with little contribution from sulfuric acid. Iodic acid largely explains the growth of ultrafine particles (UFP) in most events. The iodic acid concentration increases significantly from summer towards autumn, possibly linked to the ocean freeze-up and a seasonal rise in ozone. This leads to a one order of magnitude higher UFP concentration in autumn. Measurements of cloud residuals suggest that particles smaller than 30 nm in diameter can activate as CCN. Therefore, iodine NPF has the potential to influence cloud properties over the Arctic Ocean.

28 February 2018 in Atmospheric Chemistry and Physics
Verified
Journal Article
Open access
PDF file
JSJulia Schmale
Julia Schmale
SHSilvia Henning
Silvia Henning
SDStefano Decesari
Stefano Decesari
BHBas Henzing
Bas Henzing
HKHelmi Keskinen
Helmi Keskinen
MGMartin Gysel
Martin Gysel
Aerosol–cloud interactions (ACI) constitute the single largest uncertainty in anthropogenic radiative forcing. To reduce the uncertainties and gain more confidence in the simulation of ACI, models need to be evaluated against observations, in particular against measurements of cloud condensation nuclei (CCN). Here we present a data set – ready to be used for model validation – of long-term observations of CCN number concentrations, particle number size distributions and chemical composition from 12 sites on 3 continents. Studied environments include coastal background, rural background, alpine sites, remote forests and an urban surrounding. Expectedly, CCN characteristics are highly variable across site categories. However, they also vary within them, most strongly in the coastal background group, where CCN number concentrations can vary by up to a factor of 30 within one season. In terms of particle activation behaviour, most continental stations exhibit very similar activation ratios (relative to particles > 20 nm) across the range of 0.1 to 1.0 % supersaturation. At the coastal sites the transition from particles being CCN inactive to becoming CCN active occurs over a wider range of the supersaturation spectrum. Several stations show strong seasonal cycles of CCN number concentrations and particle number size distributions, e.g. at Barrow (Arctic haze in spring), at the alpine stations (stronger influence of polluted boundary layer air masses in summer), the rain forest (wet and dry season) or Finokalia (wildfire influence in autumn). The rural background and urban sites exhibit relatively little variability throughout the year, while short-term variability can be high especially at the urban site. The average hygroscopicity parameter, κ, calculated from the chemical composition of submicron particles was highest at the coastal site of Mace Head (0.6) and lowest at the rain forest station ATTO (0.2–0.3). We performed closure studies based on κ–Köhler theory to predict CCN number concentrations. The ratio of predicted to measured CCN concentrations is between 0.87 and 1.4 for five different types of κ. The temporal variability is also well captured, with Pearson correlation coefficients exceeding 0.87. Information on CCN number concentrations at many locations is important to better characterise ACI and their radiative forcing. But long-term comprehensive aerosol particle characterisations are labour intensive and costly. Hence, we recommend operating migrating-CCNCs to conduct collocated CCN number concentration and particle number size distribution measurements at individual locations throughout one year at least to derive a seasonally resolved hygroscopicity parameter. This way, CCN number concentrations can only be calculated based on continued particle number size distribution information and greater spatial coverage of long-term measurements can be achieved.

8 March 2022 in Atmospheric Chemistry and Physics
Verified
Journal Article
Open access
PDF file
JSJulia Schmale
Julia Schmale
SSSangeeta Sharma
Sangeeta Sharma
SDStefano Decesari
Stefano Decesari
Jakob PernovJakob Pernov
Jakob Pernov
AMAndreas Massling
Andreas Massling
PHPhilip K. Hopke
Philip K. Hopke
Even though the Arctic is remote, aerosol properties observed there are strongly influenced by anthropogenic emissions from outside the Arctic. This is particularly true for the so-called Arctic haze season (January through April). In summer (June through September), when atmospheric transport patterns change, and precipitation is more frequent, local Arctic sources, i.e., natural sources of aerosols and precursors, play an important role. Over the last few decades, significant reductions in anthropogenic emissions have taken place. At the same time a large body of literature shows evidence that the Arctic is undergoing fundamental environmental changes due to climate forcing, leading to enhanced emissions by natural processes that may impact aerosol properties. In this study, we analyze 9 aerosol chemical species and 4 particle optical properties from 10 Arctic observatories (Alert, Kevo, Pallas, Summit, Thule, Tiksi, Barrow/Utqiaġvik, Villum, and Gruvebadet and Zeppelin Observatory – both at Ny-Ålesund Research Station) to understand changes in anthropogenic and natural aerosol contributions. Variables include equivalent black carbon, particulate sulfate, nitrate, ammonium, methanesulfonic acid, sodium, iron, calcium and potassium, as well as scattering and absorption coefficients, single scattering albedo and scattering Ångström exponent. First, annual cycles are investigated, which despite anthropogenic emission reductions still show the Arctic haze phenomenon. Second, long-term trends are studied using the Mann–Kendall Theil–Sen slope method. We find in total 41 significant trends over full station records, i.e., spanning more than a decade, compared to 26 significant decadal trends. The majority of significantly declining trends is from anthropogenic tracers and occurred during the haze period, driven by emission changes between 1990 and 2000. For the summer period, no uniform picture of trends has emerged. Twenty-six percent of trends, i.e., 19 out of 73, are significant, and of those 5 are positive and 14 are negative. Negative trends include not only anthropogenic tracers such as equivalent black carbon at Kevo, but also natural indicators such as methanesulfonic acid and non-sea-salt calcium at Alert. Positive trends are observed for sulfate at Gruvebadet. No clear evidence of a significant change in the natural aerosol contribution can be observed yet. However, testing the sensitivity of the Mann–Kendall Theil–Sen method, we find that monotonic changes of around 5 % yr−1 in an aerosol property are needed to detect a significant trend within one decade. This highlights that long-term efforts well beyond a decade are needed to capture smaller changes. It is particularly important to understand the ongoing natural changes in the Arctic, where interannual variability can be high, such as with forest fire emissions and their influence on the aerosol population. To investigate the climate-change-induced influence on the aerosol population and the resulting climate feedback, long-term observations of tracers more specific to natural sources are needed, as well as of particle microphysical properties such as size distributions, which can be used to identify changes in particle populations which are not well captured by mass-oriented methods such as bulk chemical composition.

20 June 2022 in Nature Communications
Verified
Journal Article
Open access
PDF file
JCJessie Creamean
Jessie Creamean
KBKevin Barry
Kevin Barry
THTom Hill
Tom Hill
CHCarson Hume
Carson Hume
PDPaul J. DeMott
Paul J. DeMott
OPOla Persson
Ola Persson
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.