Large contribution of organics to condensational growth and formation of cloud condensation nuclei (CCN) in the remote marine boundary layer Atmospheric Chemistry and Physics DOI 10.5194/acp-20-12515-2020 27 November 2020 Condensational growth of Aitken-mode particles is a major source of cloud condensation nuclei in the remote marine boundary layer. It has been long thought that over remote oceans, condensation growth is dominated by sulfate that derives from ocean-emitted dimethyl sulfide. In this study, we present the first long-term observational evidence that, contrary to conventional thinking, organics play an even more important role than sulfate in particle growth over remote oceans throughout the year. CCN) in the remote marine boundary layer">Read more
Beaching patterns of plastic debris along the Indian Ocean rim Ocean Science DOI 10.5194/os-16-1317-2020 26 November 2020 A large percentage of global ocean plastic enters the Indian Ocean through rivers, but the fate of these plastics is generally unknown. In this paper, we use computer simulations to show that floating plastics beach and end up on coastlines throughout the Indian Ocean. Coastlines where a lot of plastic enters the ocean are heavily affected by beaching plastic, but plastics can also beach far from the source on remote islands and countries that contribute little plastic pollution of their own. Read more
Reviews and syntheses: The mechanisms underlying carbon storage in soil Biogeosciences DOI 10.5194/bg-17-5223-2020 25 November 2020 The 4 per 1000 initiative aims to restore carbon storage in soils to both mitigate climate change and contribute to food security. The French National Institute for Agricultural Research conducted a study to determine the carbon storage potential in French soils and associated costs. This paper is a part of that study. It reviews recent advances concerning the mechanisms that controls C stabilization in soils. Synthetic figures integrating new concepts should be of pedagogical interest. Read more
Global modeling of cloud water acidity, precipitation acidity, and acidinputs to ecosystems Atmospheric Chemistry and Physics DOI 10.5194/acp-20-12223-2020 24 November 2020 Cloud water pH affects atmospheric chemistry, and acid rain damages ecosystems. We use model simulations along with observations to present a global view of cloud water and precipitation pH. Sulfuric acid, nitric acid, and ammonia control the pH in the northern midlatitudes, but carboxylic acids and dust cations are important in the tropics and subtropics. The acid inputs to many nitrogen-saturated ecosystems are high enough to cause acidification, with ammonium as the main acidifying species. Read more
The Making of the New European Wind Atlas – Part 2: Production and evaluation Geoscientific Model Development DOI 10.5194/gmd-13-5079-2020 23 November 2020 This is the second of two papers that document the creation of the New European Wind Atlas (NEWA). The paper includes a detailed description of the technical and practical aspects that went into running the mesoscale simulations and the microscale downscaling for generating the climatology. A comprehensive evaluation of each component of the NEWA model chain is presented using observations from a large set of tall masts located all over Europe. Read more
A technical description of the Balloon Lidar Experiment (BOLIDE) Atmospheric Measurement Techniques DOI 10.5194/amt-13-5681-2020 19 November 2020 The Balloon Lidar Experiment was the first lidar dedicated to measurements in the mesosphere flown on a balloon. During a 6 d flight, it made high-resolution observations of polar mesospheric clouds which form at high latitudes during summer at ~ 83 km altitude and are the highest clouds in Earth’s atmosphere. We describe the instrument and assess its performance. We could detect fainter clouds with higher resolution than what is possible with ground-based instruments. BOLIDE)">Read more
Topographic controls on divide migration, stream capture, anddiversification in riverine life Earth Surface Dynamics DOI 10.5194/esurf-8-893-2020 18 November 2020 Organisms evolve in ever-changing environments under complex process interactions. We applied a new software modelling tool to assess how changes in river course impact the evolution of riverine species. Models illustrate the climatically and tectonically forced landscape changes that can drive riverine biodiversity, especially where topographic relief is low. This research demonstrates that river course changes can contribute to the high riverine biodiversity found in real-world lowland basins. Read more
Climate change as an incentive for future human migration Earth System Dynamics DOI 10.5194/esd-11-875-2020 17 November 2020 We examine the implications of future motivation for humans to migrate by analyzing today’s relationships between climatic factors and population density, with all other factors held constant. Such analyses are unlikely to make accurate predictions but can still be useful for informing discussions about the broad range of incentives that might influence migration decisions. Areas with the highest projected population growth rates tend to be the areas most adversely affected by climate change. Read more
Resolving multiple geological events using in situ Rb–Sr geochronology:implications for metallogenesis at Tropicana, Western Australia Geochronology DOI 10.5194/gchron-2-283-2020 17 November 2020 Using a relatively new dating technique, in situ Rb–Sr geochronology, we constrain the ages of two generations of mineral assemblages from the Tropicana Zone, Western Australia. The first, dated at ca. 2535 Ma, is associated with exhumation of an Archean craton margin and gold mineralization. The second, dated at ca. 1210 Ma, has not been previously documented in the Tropicana Zone. It is probably associated with Stage II of the Albany–Fraser Orogeny and additional gold mineralization. Read more
A feasibility study to use machine learning as an inversion algorithm for aerosol profile and property retrieval from multi-axis differentialabsorption spectroscopy measurements Atmospheric Measurement Techniques DOI 10.5194/amt-13-5537-2020 12 November 2020 This paper is about a feasibility study of applying a machine learning technique to derive aerosol properties from a single MAX-DOAS sky scan, which detects sky-scattered UV–visible photons at multiple elevation angles. Evaluation of retrieved aerosol properties shows good performance of the ML algorithm, suggesting several advantages of a ML-based inversion algorithm such as fast data inversion, simple implementation and the ability to extract information not available using other algorithms. Read more
