Ground-based and airborne in-situ measurements of the Eyjafjallajökull volcanic aerosol plume in Switzerland in spring 2010

The volcanic aerosol plume resulting from the Eyjafjallajökull eruption in Iceland in April and May 2010 was detected in clear layers above Switzerland during two periods (17–19 April 2010 and 16–19 May 2010). In-situ measurements of the airborne volcanic plume were performed both within ground-based monitoring networks and with a research aircraft up to an altitude of 6000 m a.s.l. The wide range of aerosol and gas phase parameters studied at the high altitude research station Jungfraujoch (3580 m a.s.l.) allowed for an in-depth characterization of the detected volcanic aerosol. Both the data from the Jungfraujoch and the aircraft vertical profiles showed a consistent volcanic ash mode in the aerosol volume size distribution with a mean optical diameter around 3 ± 0.3 μm. These particles were found to have an average chemical composition very similar to the trachyandesite-like composition of rock samples collected near the volcano. Furthermore, chemical processing of volcanic sulfur dioxide into sulfate clearly contributed to the accumulation mode of the aerosol at the Jungfraujoch. The combination of these in-situ data and plume dispersion modeling results showed that a significant portion of the first volcanic aerosol plume reaching Switzerland on 17 April 2010 did not reach the Jungfraujoch directly, but was first dispersed and diluted in the planetary boundary layer. The maximum PM10 mass concentrations at the Jungfraujoch reached 30 μgm−3 and 70 μgm−3 (for 10-min mean values) duri ng the April and May episode, respectively. Even low-altitude monitoring stations registered up to 45 μgm−3 of volcanic ash related PM10 (Basel, Northwestern Switzerland, 18/19 April 2010). The flights with the research aircraft on 17 April 2010 showed one order of magnitude higher number concentrations over the northern Swiss plateau compared to the Jungfraujoch, and a mass concentration of 320 (200–520) μgm−3 on 18 May 2010 over the northwestern Swiss plateau. The presented data significantly contributed to the time-critical assessment of the local ash layer properties during the initial eruption phase. Furthermore, dispersion models benefited from the detailed information on the volcanic aerosol size distribution and its chemical composition.

Age modeling of young non-varved lake sediments: methods and limits. Examples from two lakes in Central Chile

High-resolution and highly precise age models for recent lake sediments (last 100–150 years) are essential for quantitative paleoclimate research. These are particularly important for sedimentological and geochemical proxies, where transfer functions cannot be established and calibration must be based upon the relation of sedimentary records to instrumental data. High-precision dating for the calibration period is most critical as it determines directly the quality of the calibration statistics. Here, as an example, we compare radionuclide age models obtained on two high-elevation glacial lakes in the Central Chilean Andes (Laguna Negra: 33°38′S/70°08′W, 2,680 m a.s.l. and Laguna El Ocho: 34°02′S/70°19′W, 3,250 m a.s.l.). We show the different numerical models that produce accurate age-depth chronologies based on 210Pb profiles, and we explain how to obtain reduced age-error bars at the bottom part of the profiles, i.e., typically around the end of the 19th century. In order to constrain the age models, we propose a method with five steps: (i) sampling at irregularly-spaced intervals for 226Ra, 210Pb and 137Cs depending on the stratigraphy and microfacies, (ii) a systematic comparison of numerical models for the calculation of 210Pb-based age models: constant flux constant sedimentation (CFCS), constant initial concentration (CIC), constant rate of supply (CRS) and sediment isotope tomography (SIT), (iii) numerical constraining of the CRS and SIT models with the 137Cs chronomarker of AD 1964 and, (iv) step-wise cross-validation with independent diagnostic environmental stratigraphic markers of known age (e.g., volcanic ash layer, historical flood and earthquakes). In both examples, we also use airborne pollutants such as spheroidal carbonaceous particles (reflecting the history of fossil fuel emissions), excess atmospheric Cu deposition (reflecting the production history of a large local Cu mine), and turbidites related to historical earthquakes. Our results show that the SIT model constrained with the 137Cs AD 1964 peak performs best over the entire chronological profile (last 100–150 years) and yields the smallest standard deviations for the sediment ages. Such precision is critical for the calibration statistics, and ultimately, for the quality of the quantitative paleoclimate reconstruction. The systematic comparison of CRS and SIT models also helps to validate the robustness of the chronologies in different sections of the profile. Although surprisingly poorly known and under-explored in paleolimnological research, the SIT model has a great potential in paleoclimatological reconstructions based on lake sediments

Sensitivity of atmospheric CO2 and climate to explosive volcanic eruptions

Impacts of low-latitude, explosive volcanic eruptions on climate and the carbon cycle are quantified by forcing a comprehensive, fully coupled carbon cycle-climate model with pulse-like stratospheric aerosol optical depth changes. The model represents the radiative and dynamical response of the climate system to volcanic eruptions and simulates a decrease of global and regional atmospheric surface temperature, regionally distinct changes in precipitation, a positive phase of the North Atlantic Oscillation, and a decrease in atmospheric CO2 after volcanic eruptions. The volcanic-induced cooling reduces overturning rates in tropical soils, which dominates over reduced litter input due to soil moisture decrease, resulting in higher land carbon inventories for several decades. The perturbation in the ocean carbon inventory changes sign from an initial weak carbon sink to a carbon source. Positive carbon and negative temperature anomalies in subsurface waters last up to several decades. The multi-decadal decrease in atmospheric CO2 yields a small additional radiative forcing that amplifies the cooling and perturbs the Earth System on longer time scales than the atmospheric residence time of volcanic aerosols. In addition, century-scale global warming simulations with and without volcanic eruptions over the historical period show that the ocean integrates volcanic radiative cooling and responds for different physical and biogeochemical parameters such as steric sea level or dissolved oxygen. Results from a suite of sensitivity simulations with different magnitudes of stratospheric aerosol optical depth changes and from global warming simulations show that the carbon cycle-climate sensitivity γ, expressed as change in atmospheric CO2 per unit change in global mean surface temperature, depends on the magnitude and temporal evolution of the perturbation, and time scale of interest. On decadal time scales, modeled γ is several times larger for a Pinatubo-like eruption than for the industrial period and for a high emission, 21st century scenario.

Proposing new approaches for dating young volcanic eruptions by luminescence methods

The application of luminescence dating to young volcanic sediments has been first investigated over three decades ago, but it was only with the technical innovations of the last decade that such analyses became viable. While current analytical procedures show promise for dating late Quaternary volcanic events, most efforts have been aimed at unconsolidated volcanic tephra. Investigations into direct dating of lava flows or of non-heated volcanoclastics like phreatic explosion layers, however, remain scarce. These volcanic deposits are of common occurrence and represent important chrono- and volcanostratigraphic markers. Their age determination is therefore of great importance in volcanologic, tectonic, geomorphological and climate studies. In this article, we propose the use of phreatic explosion deposits and xenolithic inclusions in lava flows as target materials for luminescence dating applications. The main focus is on the crucial criterion whether it is probable that such materials experience complete luminescence signal resetting during the volcanic event to be dated. This is argued based on the findings from existing literature, model calculations and laboratory tests.

Synchronisation of the EDML and EDC ice cores for the last 52 kyr by volcanic signature matching

A common time scale for the EPICA ice cores from Dome C (EDC) and Dronning Maud Land (EDML) has been established. Since the EDML core was not drilled on a dome, the development of the EDML1 time scale for the EPICA ice core drilled in Dronning Maud Land was based on the creation of a detailed stratigraphic link between EDML and EDC, which was dated by a simpler 1D ice-flow model. The synchronisation between the two EPICA ice cores was done through the identification of several common volcanic signatures. This paper describes the rigorous method, using the signature of volcanic sulfate, which was employed for the last 52 kyr of the record. We estimated the discrepancies between the modelled EDC and EDML glaciological age scales during the studied period, by evaluating the ratio R of the apparent duration of temporal intervals between pairs of isochrones. On average R ranges between 0.8 and 1.2 corresponding to an uncertainty of up to 20% in the estimate of the time duration in at least one of the two ice cores. Significant deviations of R up to 1.4–1.5 are observed between 18 and 28 kyr before present (BP), where present is defined as 1950. At this stage our approach does not allow us unequivocally to find out which of the models is affected by errors, but assuming that the thinning function at both sites and accumulation history at Dome C (which was drilled on a dome) are correct, this anomaly can be ascribed to a complex spatial accumulation variability (which may be different in the past compared to the present day) upstream of the EDML core.