Performance assessment of a volcanic ash transport model mini-ensemble used for inverse modeling of the 2010 Eyjafjallajökull eruption

The requirement to forecast volcanic ash concentrations was amplified as a response to the 2010 Eyjafjallajökull eruption when ash safety limits for aviation were introduced in the European area. The ability to provide accurate quantitative forecasts relies to a large extent on the source term which is the emissions of ash as a function of time and height. This study presents source term estimations of the ash emissions from the Eyjafjallajökull eruption derived with an inversion algorithm which constrains modeled ash emissions with satellite observations of volcanic ash. The algorithm is tested with input from two different dispersion models, run on three different meteorological input data sets. The results are robust to which dispersion model and meteorological data are used. Modeled ash concentrations are compared quantitatively to independent measurements from three different research aircraft and one surface measurement station. These comparisons show that the models perform reasonably well in simulating the ash concentrations, and simulations using the source term obtained from the inversion are in overall better agreement with the observations (rank correlation = 0.55, Figure of Merit in Time (FMT) = 25–46%) than simulations using simplified source terms (rank correlation = 0.21, FMT = 20–35%). The vertical structures of the modeled ash clouds mostly agree with lidar observations, and the modeled ash particle size distributions agree reasonably well with observed size distributions. There are occasionally large differences between simulations but the model mean usually outperforms any individual model. The results emphasize the benefits of using an ensemble-based forecast for improved quantification of uncertainties in future ash crises.

Mechanisms linking volcanic aerosols to the Atlantic meridional overturning circulation

This study examines the sensitivity of the climate system to volcanic aerosol forcing in the third climate configuration of the Met Office Unified Model (HadCM3). The main test case was based on the 1880s when there were several volcanic eruptions, the well-known Krakatau being the largest. These eruptions increased atmospheric aerosol concentrations and induced a period of global cooling surface temperatures. In this study, an ensemble of HadCM3 has been integrated with the standard set of radiative forcings and aerosols from the Intergovernmental Panel on Climate Change Fourth Assessment Report simulations, from 1860 to present. A second ensemble removes the volcanic aerosols from 1880 to 1899. The all-forcings ensemble shows an attributable 1.2-Sv (1 Sv ≡ 106 m3 s−1) increase in the Atlantic meridional overturning circulation (AMOC) at 45°N—with a 0.04-PW increase in meridional heat transport at 40°N and increased northern Atlantic SSTs—starting around 1894, approximately 11 years after the first eruption, and lasting a further 10 years at least. The mechanisms responsible are traced to the Arctic, with suppression of the global water cycle (high-latitude precipitation), which leads to an increase in upper-level Arctic and Greenland Sea salinities. This then leads to increased convection in the Greenland–Iceland–Norwegian (GIN) Seas, enhanced Denmark Strait overflows, and AMOC changes with density anomalies traceable southward along the western Atlantic boundary. The authors investigate whether a similar response to the Pinatubo eruption in 1991 could still be ongoing, but do not find strong evidence.

Quantifying volcanic ash dispersal and impact of the Campanian Ignimbrite super-eruption

1] We apply a novel computational approach to assess, for the first time, volcanic ash dispersal during the Campanian Ignimbrite (Italy) super-eruption providing insights into eruption dynamics and the impact of this gigantic event. The method uses a 3D time-dependent computational ash dispersion model, a set of wind fields, and more than 100 thickness measurements of the CI tephra deposit. Results reveal that the CI eruption dispersed 250–300 km3 of ash over ∼3.7 million km2. The injection of such a large quantity of ash (and volatiles) into the atmosphere would have caused a volcanic winter during the Heinrich Event 4, the coldest and driest climatic episode of the Last Glacial period. Fluorine-bearing leachate from the volcanic ash and acid rain would have further affected food sources and severely impacted Late Middle-Early Upper Paleolithic groups in Southern and Eastern Europe

Topographic and thermal mapping of volcanic terrain using AVTIS ground-based 94-GHz dual-mode radar/radiometric imager

The All-Weather Volcano Topography Imaging Sensor remote sensing instrument is a custom-built millimeter-wave (MMW) sensor that has been developed as a practical field tool for remote sensing of volcanic terrain at active lava domes. The portable instrument combines active and passive MMW measurements to record topographic and thermal data in almost all weather conditions from ground-based survey points. We describe how the instrument is deployed in the field, the quality of the primary ranging and radiometric measurements, and the postprocessing techniques used to derive the geophysical products of the target terrain, surface temperature, and reflectivity. By comparison of changing topography, we estimate the volume change and the lava extrusion rate. Validation of the MMW radiometry is also presented by quantitative comparison with coincident infrared thermal imagery.

Triboelectric charging of volcanic ash from the 2011 Grímsvötn eruption

The plume from the 2011 eruption of Grímsvötn was highly electrically charged, as shown by the considerable lightning activity measured by the United Kingdom Met Office’s low-frequency lightning detection network. Previous measurements of volcanic plumes have shown that ash particles are electrically charged up to hundreds of kilometers away from the vent, which indicates that the ash continues to charge in the plume [R. G. Harrison, K. A. Nicoll, Z. Ulanowski, and T. A. Mather, Environ. Res. Lett. 5 024004 (2010); H. Hatakeyama J. Meteorol. Soc. Jpn. 27 372 (1949)]. In this Letter, we study triboelectric charging of different size fractions of a sample of volcanic ash experimentally. Consistently with previous work, we find that the particle size distribution is a determining factor in the charging. Specifically, our laboratory experiments demonstrate that the normalized span of the particle size distribution plays an important role in the magnitude of charging generated. The influence of the normalized span on plume charging suggests that all ash plumes are likely to be charged, with implications for remote sensing and plume lifetime through scavenging effects.

Aircraft observations and model simulations of concentration and particle size distribution in the Eyjafjallajökull volcanic ash cloud

The Eyjafjallajökull volcano in Iceland emitted a cloud of ash into the atmosphere during April and May 2010. Over the UK the ash cloud was observed by the FAAM BAe-146 Atmospheric Research Aircraft which was equipped with in-situ probes measuring the concentration of volcanic ash carried by particles of varying sizes. The UK Met Office Numerical Atmospheric-dispersion Modelling Environment (NAME) has been used to simulate the evolution of the ash cloud emitted by the Eyjafjallajökull volcano during the period 4–18 May 2010. In the NAME simulations the processes controlling the evolution of the concentration and particle size distribution include sedimentation and deposition of particles, horizontal dispersion and vertical wind shear. For travel times between 24 and 72 h, a 1/t relationship describes the evolution of the concentration at the centre of the ash cloud and the particle size distribution remains fairly constant. Although NAME does not represent the effects of microphysical processes, it can capture the observed decrease in concentration with travel time in this period. This suggests that, for this eruption, microphysical processes play a small role in determining the evolution of the distal ash cloud. Quantitative comparison with observations shows that NAME can simulate the observed column-integrated mass if around 4% of the total emitted mass is assumed to be transported as far as the UK by small particles (< 30 μm diameter). NAME can also simulate the observed particle size distribution if a distal particle size distribution that contains a large fraction of < 10 μm diameter particles is used, consistent with the idea that phraetomagmatic volcanoes, such as Eyjafjallajökull, emit very fine particles.

Climate models without pre-industrial volcanic forcing underestimate historical ocean thermal expansion

Episodic explosive volcanic eruptions are a natural part of the climate system but are often omitted from atmosphere-ocean general circulation model (AOGCM) preindustrial spin-up and control experiments. This omission imposes a negative bias on ocean heat uptake in simulations of the historical period. In models of a range of complexity, we find that global-mean sea level rise due to thermal expansion during the last ∼ 150 years is consequently underestimated by 5–30 mm, which is a substantial proportion of the model mean of 50 mm in Coupled Model Intercomparison Project Phase 3 AOGCMs with anthropogenic forcing only, and is therefore important in accounting for 20th century sea level rise. We test and recommend a procedure for removing the bias.

Counteracting the climate effects of volcanic eruptions using short-lived greenhouse gases

A large volcanic eruption might constitute a climate emergency, significantly altering global temperature and precipitation for several years. Major future eruptions will occur, but their size or timing cannot be predicted. We show, for the first time, that it may be possible to counteract these climate effects through deliberate emissions of short-lived greenhouse gases, dampening the abrupt impact of an eruption. We estimate an emission pathway countering a hypothetical eruption 3 times the size of Mount Pinatubo in 1991. We use a global climate model to evaluate global and regional responses to the eruption, with and without counteremissions. We then raise practical, financial, and ethical questions related to such a strategy. Unlike the more commonly discussed geoengineering to mitigate warming from long-lived greenhouse gases, designed emissions to counter temporary cooling would not have the disadvantage of needing to be sustained over long periods. Nevertheless, implementation would still face significant challenges.

Speleothems as sensitive recorders of volcanic eruptions - the Bronze Age Minoan eruption recorded in a stalagmite from Turkey

Mounting evidence exists that variations in sulphur content in stalagmites are closely linked to changes in volcanic or anthropogenic atmospheric sulphur. The strong dependency of sulphur on soil pH and ecosystem storage, however, can result in a delay of several years to decades in the registration of volcanic eruptions and anthropogenic emissions by stalagmites. Here we present synchrotron-radiation based trace element analysis performed on a precisely-dated section of a stalagmite from Sofular Cave in Northern Turkey. As this section covers the time interval of the intensively studied Minoan volcanic eruption between 1600 and 1650 BC, we can test whether this vigorous eruption can be traced in a stalagmite. Of all measured trace elements, only bromine shows a clear short-lived peak at 1621±251621±25 BC, whereas sulphur and molybdenum show peaks later at 1617±251617±25 and 1589±251589±25 respectively. We suggest that all trace element peaks are related to the Minoan eruption, whereas the observed phasing of bromine, molybdenum and sulphur is related to differences in their retention rates in the soil above Sofular Cave. For the first time, we can show that bromine appears to be an ideal volcanic tracer in stalagmites, as it is a prominent volatile component in volcanic eruptions, can be easily leached in soils and rapidly transferred from the atmosphere through the soil and bedrock into the cave and stalagmite respectively. Highly resolved oxygen and carbon isotope profiles indicate that the Minoan eruption had no detectable climatic and environmental impact in Northern Turkey.

Volcanic ash layer depth: processes and mechanisms

The long duration of the 2010 Eyjafjallajökull eruption provided a unique opportunity to measure a widely dispersed volcanic ash cloud. Layers of volcanic ash were observed by the European Aerosol Research Lidar Network with a mean depth of 1.2 km and standard deviation of 0.9 km. In this paper we evaluate the ability of the Met Office's Numerical Atmospheric-dispersion Modelling Environment (NAME) to simulate the observed ash layers and examine the processes controlling their depth. NAME simulates distal ash layer depths exceptionally well with a mean depth of 1.2 km and standard deviation of 0.7 km. The dominant process determining the depth of ash layers over Europe is the balance between the vertical wind shear (which acts to reduce the depth of the ash layers) and vertical turbulent mixing (which acts to deepen the layers). Interestingly, differential sedimentation of ash particles and the volcano vertical emission profile play relatively minor roles.

Spatial evaluation of volcanic ash forecasts using satellite observations

The decision to close airspace in the event of a volcanic eruption is based on hazard maps of predicted ash extent. These are produced using output from volcanic ash transport and dispersion (VATD)models. In this paper an objectivemetric to evaluate the spatial accuracy of VATD simulations relative to satellite retrievals of volcanic ash is presented. The 5 metric is based on the fractions skill score (FSS). Thismeasure of skill provides more information than traditional point-bypoint metrics, such as success index and Pearson correlation coefficient, as it takes into the account spatial scale overwhich skill is being assessed. The FSS determines the scale overwhich a simulation has skill and can differentiate between a "near miss" and a forecast that is badly misplaced. The 10 idealised scenarios presented show that even simulations with considerable displacement errors have useful skill when evaluated over neighbourhood scales of 200–700km2. This method could be used to compare forecasts produced by different VATDs or using different model parameters, assess the impact of assimilating satellite retrieved ash data and evaluate VATD forecasts over a long time period.

Using data insertion with the NAME model to simulate the 8 May 2010 Eyjafjallajökull volcanic ash cloud

A data insertion method, where a dispersion model is initialized from ash properties derived from a series of satellite observations, is used to model the 8 May 2010 Eyjafjallajökull volcanic ash cloud which extended from Iceland to northern Spain. We also briefly discuss the application of this method to the April 2010 phase of the Eyjafjallajökull eruption and the May 2011 Grímsvötn eruption. An advantage of this method is that very little knowledge about the eruption itself is required because some of the usual eruption source parameters are not used. The method may therefore be useful for remote volcanoes where good satellite observations of the erupted material are available, but little is known about the properties of the actual eruption. It does, however, have a number of limitations related to the quality and availability of the observations. We demonstrate that, using certain configurations, the data insertion method is able to capture the structure of a thin filament of ash extending over northern Spain that is not fully captured by other modeling methods. It also verifies well against the satellite observations according to the quantitative object-based quality metric, SAL—structure, amplitude, location, and the spatial coverage metric, Figure of Merit in Space.

Small global-mean cooling due to volcanic radiative forcing

In both the observational record and atmosphere-ocean general circulation model (AOGCM) simulations of the last ∼∼ 150 years, short-lived negative radiative forcing due to volcanic aerosol, following explosive eruptions, causes sudden global-mean cooling of up to ∼∼ 0.3 K. This is about five times smaller than expected from the transient climate response parameter (TCRP, K of global-mean surface air temperature change per W m−2 of radiative forcing increase) evaluated under atmospheric CO2 concentration increasing at 1 % yr−1. Using the step model (Good et al. in Geophys Res Lett 38:L01703, 2011. doi:10.​1029/​2010GL045208), we confirm the previous finding (Held et al. in J Clim 23:2418–2427, 2010. doi:10.​1175/​2009JCLI3466.​1) that the main reason for the discrepancy is the damping of the response to short-lived forcing by the thermal inertia of the upper ocean. Although the step model includes this effect, it still overestimates the volcanic cooling simulated by AOGCMs by about 60 %. We show that this remaining discrepancy can be explained by the magnitude of the volcanic forcing, which may be smaller in AOGCMs (by 30 % for the HadCM3 AOGCM) than in off-line calculations that do not account for rapid cloud adjustment, and the climate sensitivity parameter, which may be smaller than for increasing CO2 (40 % smaller than for 4 × CO2 in HadCM3).

How accurate are volcanic ash simulations of the 2010 Eyjafjallajökull eruption?

In the event of a volcanic eruption the decision to close airspace is based on forecast ash maps, produced using volcanic ash transport and dispersion models. In this paper we quantitatively evaluate the spatial skill of volcanic ash simulations using satellite retrievals of ash from the Eyja allajökull eruption during the period from 7 to 16 May 2010. We find that at the start of this period, 7–10 May, the model (FLEXible PARTicle) has excellent skill and can predict the spatial distribution of the satellite-retrieved ash to within 0.5∘ × 0.5∘ latitude/longitude. However, on 10 May there is a decrease in the spatial accuracy of the model to 2.5∘× 2.5∘ latitude/longitude, and between 11 and 12 May the simulated ash location errors grow rapidly. On 11 May ash is located close to a bifurcation point in the atmosphere, resulting in a rapid divergence in the modeled and satellite ash locations. In general, the model skill reduces as the residence time of ash increases. However, the error growth is not always steady. Rapid increases in error growth are linked to key points in the ash trajectories. Ensemble modeling using perturbed meteorological data would help to represent this uncertainty, and assimilation of satellite ash data would help to reduce uncertainty in volcanic ash forecasts.