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    Characterization of organic aerosol across the global remote troposphere: A comparison of ATom measurements and global chemistry models
    (Katlenburg-Lindau : EGU, 2020) Hodzic, Alma; Campuzano-Jost, Pedro; Bian, Huisheng; Chin, Mian; Colarco, Peter R.; Day, Douglas A.; Froyd, Karl D.; Heinold, Bernd; Katich, Joseph M.; Jo, Duseong S.; Kodros, John K.; Nault, Benjamin A.; Pierce, Jeffrey R.; Ray, Eric; Schacht, Jacob; Schill, Gregory P.; Schroder, Jason C.; Schwarz, Joshua P.; Sueper, Donna T.; Tegen, Ina; Tilmes, Simone; Tsigaridis, Kostas; Yu, Pengfei; Jimenez, Jose L.
    The spatial distribution and properties of submicron organic aerosol (OA) are among the key sources of uncertainty in our understanding of aerosol effects on climate. Uncertainties are particularly large over remote regions of the free troposphere and Southern Ocean, where very few data have been available and where OA predictions from AeroCom Phase II global models span 2 to 3 orders of magnitude, greatly exceeding the model spread over source regions. The (nearly) pole-to-pole vertical distribution of nonrefractory aerosols was measured with an aerosol mass spectrometer onboard the NASA DC-8 aircraft as part of the Atmospheric Tomography (ATom) mission during the Northern Hemisphere summer (August 2016) and winter (February 2017). This study presents the first extensive characterization of OA mass concentrations and their level of oxidation in the remote atmosphere. OA and sulfate are the major contributors by mass to submicron aerosols in the remote troposphere, together with sea salt in the marine boundary layer. Sulfate was dominant in the lower stratosphere. OA concentrations have a strong seasonal and zonal variability, with the highest levels measured in the lower troposphere in the summer and over the regions influenced by biomass burning from Africa (up to 10 μgsm-3). Lower concentrations (~ 0:1 0.3 μgsm-3) are observed in the northern middle and high latitudes and very low concentrations (< 0:1 μgsm-3) in the southern middle and high latitudes. The ATom dataset is used to evaluate predictions of eight current global chemistry models that implement a variety of commonly used representations of OA sources and chemistry, as well as of the AeroCom-II ensemble. The current model ensemble captures the average vertical and spatial distribution of measured OA concentrations, and the spread of the individual models remains within a factor of 5. These results are significantly improved over the AeroCom-II model ensemble, which shows large overestimations over these regions. However, some of the improved agreement with observations occurs for the wrong reasons, as models have the tendency to greatly overestimate the primary OA fraction and underestimate the sec-ondary fraction. Measured OA in the remote free troposphere is highly oxygenated, with organic aerosol to organic carbon (OA= OC) ratios of ~ 2.2 2.8, and is 30 % 60% more oxygenated than in current models, which can lead to significant errors in OA concentrations. The model measurement comparisons presented here support the concept of a more dynamic OA system as proposed by Hodzic et al. (2016), with enhanced removal of primary OA and a stronger production of secondary OA in global models needed to provide better agreement with observations. © 2020 IEEE Computer Society. All rights reserved.
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    Ship-based measurements of ice nuclei concentrations over the Arctic, Atlantic, Pacific and Southern oceans
    (Katlenburg-Lindau : EGU, 2020) Welti, André; Bigg, Keith E.; DeMott, Paul J.; Gong, Xianda; Hartmann, Markus; Harvey, Mike; Henning, Silvia; Herenz, Paul; Hill, Thomas C.J.; Hornblow, Blake; Leck, Caroline; Löffler, Mareike; McCluskey, Christina S.; Rauker, Anne Marie; Schmale, Julia; Tatzelt, Christian; van Pinxteren, Manuela; Stratmann, Frank
    Ambient concentrations of ice-forming particles measured during ship expeditions are collected and summarised with the aim of determining the spatial distribution and variability in ice nuclei in oceanic regions. The presented data from literature and previously unpublished data from over 23 months of ship-based measurements stretch from the Arctic to the Southern Ocean and include a circumnavigation of Antarctica. In comparison to continental observations, ship-based measurements of ambient ice nuclei show 1 to 2 orders of magnitude lower mean concentrations. To quantify the geographical variability in oceanic areas, the concentration range of potential ice nuclei in different climate zones is analysed by meridionally dividing the expedition tracks into tropical, temperate and polar climate zones. We find that concentrations of ice nuclei in these meridional zones follow temperature spectra with similar slopes but vary in absolute concentration. Typically, the frequency with which specific concentrations of ice nuclei are observed at a certain temperature follows a log-normal distribution. A consequence of the log-normal distribution is that the mean concentration is higher than the most frequently measured concentration. Finally, the potential contribution of ship exhaust to the measured ice nuclei concentration on board research vessels is analysed as function of temperature. We find a sharp onset of the influence at approximately 36 C but none at warmer temperatures that could bias ship-based measurements. © Author(s) 2020. This work is distributed under the Creative Commons Attribution 4.0 License.
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    North African mineral dust sources: New insights from a combined analysis based on 3D dust aerosol distributions, surface winds and ancillary soil parameters
    (Katlenburg-Lindau : EGU, 2020) Vandenbussche, Sophie; Callewaert, Sieglinde; Schepanski, Kerstin; De Mazière, Martine
    Mineral dust aerosol is a key player in the climate system. Determining dust sources and the spatio-temporal variability of dust emission fluxes is essential for estimating the impact of dust on the atmospheric radiation budget, cloud and precipitation formation processes, the bio-productivity and, ultimately, the carbon cycle. Although much effort has been put into determining dust sources from satellite observations, geo-locating active dust sources is still challenging and uncertainties in space and time are evident. One major source of uncertainty is the lack of clear differentiation between near-source dust aerosol and transported dust aerosol. In order to reduce this uncertainty, we use 3D information on the distribution of dust aerosol suspended in the atmosphere calculated from spectral measurements obtained by the Infrared Atmospheric Sounding Interferometer (IASI) by using the Mineral Aerosols Profiling from Infrared Radiance (MAPIR) algorithm. In addition to standard dust products from satellite observations, which provide 2D information on the horizontal distribution of dust, MAPIR allows for the retrieval of additional information on the vertical distribution of dust plumes. This ultimately enables us to separate between near-source and transported dust plumes. Combined with information on near-surface wind speed and surface properties, low-altitude dust plumes can be assigned to dust emission events and low-altitude transport regimes can be excluded. Consequently, this technique will reduce the uncertainty in automatically geo-locating active dust sources. The findings of our study illustrate the spatio-temporal distribution of North African dust sources based on 9 years of data, allowing for the observation of a full seasonal cycle of dust emissions, differentiating morning and afternoon/evening emissions and providing a first glance at long-term changes. In addition, we compare the results of this new method to the results from Schepanski et al. (2012), who manually identified dust sources from Spinning Enhanced Visible and InfraRed Imager (SEVIRI) red-green-blue (RGB) images. The comparison illustrates that each method has its strengths and weaknesses that must be taken into account when using the results. This study is of particular importance for understanding future environmental changes due to a changing climate. © Author(s) 2020
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    The Earth system model CLIMBER-X v1.0 - Part 2: The global carbon cycle
    (Katlenburg-Lindau : Copernicus, 2023) Willeit, Matteo; Ilyina, Tatiana; Liu, Bo; Heinze, Christoph; Perrette, Mahé; Heinemann, Malte; Dalmonech, Daniela; Brovkin, Victor; Munhoven, Guy; Börker, Janine; Hartmann, Jens; Romero-Mujalli, Gibran; Ganopolski, Andrey
    The carbon cycle component of the newly developed Earth system model of intermediate complexity CLIMBER-X is presented. The model represents the cycling of carbon through the atmosphere, vegetation, soils, seawater and marine sediments. Exchanges of carbon with geological reservoirs occur through sediment burial, rock weathering and volcanic degassing. The state-of-the-art HAMOCC6 model is employed to simulate ocean biogeochemistry and marine sediment processes. The land model PALADYN simulates the processes related to vegetation and soil carbon dynamics, including permafrost and peatlands. The dust cycle in the model allows for an interactive determination of the input of the micro-nutrient iron into the ocean. A rock weathering scheme is implemented in the model, with the weathering rate depending on lithology, runoff and soil temperature. CLIMBER-X includes a simple representation of the methane cycle, with explicitly modelled natural emissions from land and the assumption of a constant residence time of CH4 in the atmosphere. Carbon isotopes 13C and 14C are tracked through all model compartments and provide a useful diagnostic for model-data comparison. A comprehensive evaluation of the model performance for the present day and the historical period shows that CLIMBER-X is capable of realistically reproducing the historical evolution of atmospheric CO2 and CH4 but also the spatial distribution of carbon on land and the 3D structure of biogeochemical ocean tracers. The analysis of model performance is complemented by an assessment of carbon cycle feedbacks and model sensitivities compared to state-of-the-art Coupled Model Intercomparison Project Phase 6 (CMIP6) models. Enabling an interactive carbon cycle in CLIMBER-X results in a relatively minor slow-down of model computational performance by ∼ 20 % compared to a throughput of ∼ 10 000 simulation years per day on a single node with 16 CPUs on a high-performance computer in a climate-only model set-up. CLIMBER-X is therefore well suited to investigating the feedbacks between climate and the carbon cycle on temporal scales ranging from decades to >100000 years.