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- ItemThe Global Aerosol Synthesis and Science Project (GASSP): Measurements and Modeling to Reduce Uncertainty(Boston, Mass. : ASM, 2017) Reddington, C.L.; Carslaw, K.S.; Stier, P.; Schutgens, N.; Coe, H.; Liu, D.; Allan, J.; Browse, J.; Pringle, K.J.; Lee, L.A.; Yoshioka, M.; Johnson, J.S.; Regayre, L.A.; Spracklen, D.V.; Mann, G.W.; Clarke, A.; Hermann, M.; Henning, S.; Wex, H.; Kristensen, T.B.; Leaitch, W.R.; Pöschl, U.; Rose, D.; Andreae, M.O.; Schmale, J.; Kondo, Y.; Oshima, N.; Schwarz, J.P.; Nenes, A.; Anderson, B.; Roberts, G.C.; Snider, J.R.; Leck, C.; Quinn, P.K.; Chi, X.; Ding, A.; Jimenez, J.L.; Zhang, Q.The largest uncertainty in the historical radiative forcing of climate is caused by changes in aerosol particles due to anthropogenic activity. Sophisticated aerosol microphysics processes have been included in many climate models in an effort to reduce the uncertainty. However, the models are very challenging to evaluate and constrain because they require extensive in situ measurements of the particle size distribution, number concentration, and chemical composition that are not available from global satellite observations. The Global Aerosol Synthesis and Science Project (GASSP) aims to improve the robustness of global aerosol models by combining new methodologies for quantifying model uncertainty, to create an extensive global dataset of aerosol in situ microphysical and chemical measurements, and to develop new ways to assess the uncertainty associated with comparing sparse point measurements with low-resolution models. GASSP has assembled over 45,000 hours of measurements from ships and aircraft as well as data from over 350 ground stations. The measurements have been harmonized into a standardized format that is easily used by modelers and nonspecialist users. Available measurements are extensive, but they are biased to polluted regions of the Northern Hemisphere, leaving large pristine regions and many continental areas poorly sampled. The aerosol radiative forcing uncertainty can be reduced using a rigorous model–data synthesis approach. Nevertheless, our research highlights significant remaining challenges because of the difficulty of constraining many interwoven model uncertainties simultaneously. Although the physical realism of global aerosol models still needs to be improved, the uncertainty in aerosol radiative forcing will be reduced most effectively by systematically and rigorously constraining the models using extensive syntheses of measurements.
- ItemInterfacial photochemistry at the ocean surface is a global source of organic vapors and aerosols([London] : Nature Publishing Group UK, 2018) Brüggemann, Martin; Hayeck, Nathalie; George, ChristianThe surface of the oceans acts as a global sink and source for trace gases and aerosol particles. Recent studies suggest that photochemical reactions at this air/water interface produce organic vapors, enhancing particle formation in the atmosphere. However, current model calculations neglect this abiotic source of reactive compounds and account only for biological emissions. Here we show that interfacial photochemistry serves as a major abiotic source of volatile organic compounds (VOCs) on a global scale, capable to compete with emissions from marine biology. Our results indicate global emissions of 46.4-184 Tg C yr-1 of organic vapors from the oceans into the marine atmosphere and a potential contribution to organic aerosol mass of more than 60% over the remote ocean. Moreover, we provide global distributions of VOC formation potentials, which can be used as simple tools for field studies to estimate photochemical VOC emissions depending on location and season.
- ItemCRAAS: A European Cloud Regime dAtAset Based on the CLAAS-2.1 Climate Data Record(Basel : MDPI, 2022) Tzallas, Vasileios; Hünerbein, Anja; Stengel, Martin; Meirink, Jan Fokke; Benas, Nikos; Trentmann, Jörg; Macke, AndreasGiven the important role of clouds in our planet’s climate system, it is crucial to further improve our understanding of their governing processes as well as the resulting spatio-temporal variability of their properties. This co-variability of different cloud optical properties is adequately represented through the well-established concept of cloud regimes. The focus of the present study lies on the creation of a cloud regime dataset over Europe, named “Cloud Regime dAtAset based on the CLAAS-2.1 climate data record” (CRAAS), in order to analyze their variability and their changes at different spatio-temporal scales. In addition, co-occurrences between the cloud regimes and large-scale weather patterns are investigated. The CLoud property dAtAset using Spinning Enhanced Visible and Infrared (SEVIRI) edition 2.1 (CLAAS-2.1) data record, which is produced by the Satellite Application Facility on Climate Monitoring (CM SAF), was used as the basis for the derivation of the cloud regimes over Europe for a 14-year period (2004–2017). In particular, the cloud optical thickness (COT) and cloud top pressure (CTP) products of CLAAS-2.1 were used in order to compute 2D histograms. Then, the k-means clustering algorithm was applied to the generated 2D histograms in order to derive the cloud regimes. Eight cloud regimes were identified, which, along with the geographical distribution of their frequency of occurrence, assisted in providing a detailed description of the climate of the cloud properties over Europe. The annual and diurnal variabilities of the eight cloud regimes were studied, and trends in their frequency of occurrence were also examined. Larger changes in the frequency of occurrence of the produced cloud regimes were found for a regime associated to alto- and nimbo-type clouds and for a regime connected to shallow cumulus clouds and fog (−0.65% and +0.70% for the time period of the study, respectively).