[1] During the 2010 eruption of Eyjafjallajökull, improvements were made to the modeling procedure at the Met Office, UK, enabling peak ash concentrations within the volcanic cloud to be estimated. In this paper we describe the ash concentration forecasting method, its rationale and how it evolved over time in response to new information and user requirements. The change from solely forecasting regions of ash to also estimating peak ash concentrations required consideration of volcanic ash emission rates, the fraction of ash surviving near-source fall-out, and the relationship between predicted mean and local peak ash concentrations unresolved by the model. To validate the modeling procedure, predicted peak ash concentrations are compared against observations obtained by ground-based and research aircraft instrumentation. This comparison between modeled and observed peak concentrations highlights the many sources of error and the uncertainties involved. Despite the challenges of predicting ash concentrations, the ash forecasting method employed here is found to give useful guidance on likely ash concentrations. Predicted peak ash concentrations lie within about one and a half orders of magnitude of the observed peak concentrations. A significant improvement in the agreement between modeled and observed values is seen if a buffer zone, accounting for positional errors in the predicted ash cloud, is used. Sensitivity of the predicted ash concentrations to the source properties (e.g., the plume height and the vertical distribution of ash at the source) is assessed and in some cases, seemingly minor uncertainties in the source specification have a large effect on predicted ash concentrations.

The 2014-2015 Bárðarbunga-Veiðivötn fissure eruption at Holuhraun produced about 1.5 km 3 of lava, making it the largest eruption in Iceland in more than 200 years. Over the course of the eruption, daily volcanic sulfur dioxide (SO 2 ) emissions exceeded daily SO 2 emissions from all anthropogenic sources in Europe in 2010 by at least a factor of 3. We present surface air quality observations from across Northern Europe together with satellite remote sensing data and model simulations of volcanic SO 2 for September 2014. We show that volcanic SO 2 was transported in the lowermost troposphere over long distances and detected by air quality monitoring stations up to 2750 km away from the source. Using retrievals from the Ozone Monitoring Instrument (OMI) and the Infrared Atmospheric Sounding Interferometer (IASI), we calculate an average daily SO 2 mass burden of 99 ± 49 kilotons (kt) of SO 2 from OMI and 61 ± 18 kt of SO 2 from IASI for September 2014. This volcanic burden is at least a factor of 2 greater than the average SO 2 mass burden between 2007 and 2009 due to anthropogenic emissions from the whole of Europe. Combining the observational data with model simulations using the United Kingdom Met Office's Numerical Atmospheric-dispersion Modelling Environment model, we are able to constrain SO 2 emission rates to up to 120 kilotons per day (kt/d) during early September 2014, followed by a decrease to 20-60 kt/d between 6 and 22 September 2014, followed by a renewed increase to 60-120 kt/d until the end of September 2014. Based on these fluxes, we estimate that the eruption emitted a total of 2.0 ± 0.6 Tg of SO 2 during September 2014, in good agreement with ground-based remote sensing and petrological estimates. Although satellite-derived and model-simulated vertical column densities of SO 2 agree well, the model simulations are biased low by up to a factor of 8 when compared to surface observations of volcanic SO 2 on 6-7 September 2014 in Ireland. These biases are mainly due to relatively small horizontal and vertical positional errors in the simulations of the volcanic plume occurring over transport distances of thousands of kilometers. Although the volcanic air pollution episodes were transient and lava-dominated volcanic eruptions are sporadic events, the observations suggest that (i) during an eruption, volcanic SO 2 measurements should be assimilated for near real-time air quality forecasting and (ii) existing air quality monitoring networks should be retained or extended to monitor SO 2 and other volcanic pollutants.

Eyjafjallajökull, a volcano in southern Iceland, erupted explosively in April and May 2010 depositing ash over a region of more than 3000 km2 to the east and southeast of the volcano. This deposited ash has been frequently remobilized by the wind causing concern for the health of Icelanders living in the region. An investigation was carried out to determine whether it would be possible to produce forecasts of days when high airborne ash concentrations were likely to occur. Information about the spatially varying surface characteristics of the region of deposited ash is not available so in the modeling approach adopted here ash is released from the surface at a rate proportional to the cube of the excess friction velocity (local friction velocity minus a threshold) only when the friction velocity exceeds a threshold. Movement of the resuspended ash is then modeled in a Lagrangian dispersion model. Modeled ash concentrations are compared to observed concentrations from two periods; PM10 observations between 23 May and 2 July 2010 and airborne particle counts between 21 September 2010 and 16 February 2011. More than 66% of the resuspension episodes between May and July are captured by the model and the relative magnitudes of the modeled episodes in this period are in good agreement with the observations. 66% of episodes between October and February are also captured by the model although there is an increase in the false alarm rate which appears to be due to the influence of precipitation.

The total heat gained by the North Atlantic Ocean over the past 50 years is equivalent to a basinwide increase in the flux of heat across the ocean surface of 0.4 +/- 0.05 watts per square meter. We show, however, that this basin has not warmed uniformly: Although the tropics and subtropics have warmed, the subpolar ocean has cooled. These regional differences require local surface heat flux changes (+/-4 watts per square meter) much larger than the basinwide average. Model investigations show that these regional differences can be explained by large-scale, decadal variability in wind and buoyancy forcing as measured by the North Atlantic Oscillation index. Whether the overall heat gain is due to anthropogenic warming is difficult to confirm because strong natural variability in this ocean basin is potentially masking such input at the present time.

Five different atmospheric transport and dispersion model's (ATDM) deposition and air concentration results for atmospheric releases from the Fukushima Daiichi nuclear power plant accident were evaluated over Japan using regional (137)Cs deposition measurements and (137)Cs and (131)I air concentration time series at one location about 110 km from the plant. Some of the ATDMs used the same and others different meteorological data consistent with their normal operating practices. There were four global meteorological analyses data sets available and two regional high-resolution analyses. Not all of the ATDMs were able to use all of the meteorological data combinations. The ATDMs were configured identically as much as possible with respect to the release duration, release height, concentration grid size, and averaging time. However, each ATDM retained its unique treatment of the vertical velocity field and the wet and dry deposition, one of the largest uncertainties in these calculations. There were 18 ATDM-meteorology combinations available for evaluation. The deposition results showed that even when using the same meteorological analysis, each ATDM can produce quite different deposition patterns. The better calculations in terms of both deposition and air concentration were associated with the smoother ATDM deposition patterns. The best model with respect to the deposition was not always the best model with respect to air concentrations. The use of high-resolution mesoscale analyses improved ATDM performance; however, high-resolution precipitation analyses did not improve ATDM predictions. Although some ATDMs could be identified as better performers for either deposition or air concentration calculations, overall, the ensemble mean of a subset of better performing members provided more consistent results for both types of calculations.