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Observations and model results show an increase in extreme precipitation with global warming since the 1950s. During the last decades there have also been strong trends in anthropogenic aerosol concentration, aerosols that may affect cloud and precipitation processes that develop these extreme events. As human activities are the source of anthropogenic aerosols, they tend to be concentrated over highly populated regions where the potential cost and impact of extreme precipitation is high. In this study we investigate the link between extreme precipitation and aerosol particles in the atmosphere by using the cloud resolving WRF model. The model is set up with an aerosol-dependent cloud microphysics scheme that include processes such as; the increase in smaller droplets in aerosol rich clouds, the change in cloud reflective properties that can reduce surface evapotranspiration as well as a deepening of convective clouds and possible an increase in precipitation intensity. The model is run over several years in a stable climate to distinguish how these processes influence extreme precipitation separately from the extreme precipitation increase due to global warming.

More than half of the world's population lives in urban areas (UN Population Division 2018 The World's cities in 2018 (UN: New York)), which are especially vulnerable to climate extremes (Field et al 2012 Managing the Risks of Extreme Events and Disasters to Advance Climate Change Adaptation: Special Report of the Intergovernmental Panel on Climate Change (Cambridge: Cambridge University Press)). Urbanization itself is known to increase surface temperatures, but its quantitative effect on extreme precipitation remains very uncertain. Using decadal convection-permitting climate simulations in four midlatitude megacities (Paris, France; New York City, USA; Tokyo, Japan; Shanghai, China), we show that urbanization can strongly increase the frequency and intensity of extreme urban precipitation. Frequency increases far more than intensity, by +16% (11%–22%) (95% confidence interval) for 1 year daily extremes, and +26% (11%–41%) for 1 year hourly extremes, downwind of city centers. Intensities of the same events increase by +5% (3.2%–6.4%) (daily extremes) and +6% (3.2%–9.8%) (hourly extremes), respectively. The intensity and frequency of extremes increases more for the rarest, most extreme events considered, and there is some indication that hourly extremes increase more than daily extremes. Our simulations also show that direct urban anthropogenic emissions of heat could be an important factor driving these changes. Urbanization is expected to continue in the future, and our results indicate that these effects should be considered in urban planning decisions to make cities more resilient to extreme precipitation.

This paper presents a new version of the EMEP MSC-W model called eEMEP developed for transportation and dispersion of volcanic emissions, both gases and ash. EMEP MSC-W is usually applied to study problems with air pollution and aerosol transport and requires some adaptation to treat volcanic eruption sources and effluent dispersion. The operational set-up of model simulations in case of a volcanic eruption is described. Important choices have to be made to achieve CPU efficiency so that emergency situations can be tackled in time, answering relevant questions of ash advisory authorities. An efficient model needs to balance the complexity of the model and resolution. We have investigated here a meteorological uncertainty component of the volcanic cloud forecast by using a consistent ensemble meteorological dataset (GLAMEPS forecast) at three resolutions for the case of SO2 emissions from the 2014 Barðarbunga eruption. The low resolution (40 × 40 km) ensemble members show larger agreement in plume position and intensity, suggesting that the ensemble here does not give much added value. To compare the dispersion at different resolutions, we compute the area where the column load of the volcanic tracer, here SO2, is above a certain threshold, varied for testing purposes between 0.25 and 50 Dobson units. The increased numerical diffusion causes a larger area (+34 %) to be covered by the volcanic tracer in the low resolution simulations than in the high resolution ones. The higher resolution (10 × 10 km) ensemble members show higher column loads farther away from the volcanic eruption site in narrower clouds. Cloud positions are more varied between the high resolution members, and the cloud forms resemble the observed clouds more than the low resolution ones. For a volcanic emergency case this means that to obtain quickly results of the transport of volcanic emissions, an individual simulation with our low resolution is sufficient; however, to forecast peak concentrations with more certainty for forecast or scientific analysis purposes, a finer resolution is needed. The model is further developed to simulate ash from highly explosive eruptions. A possibility of increasing the number of vertical layers, achieving finer vertical resolution, as well as a higher model top, is included in the eEMEP version. Ash size distributions may be altered for different volcanic eruptions and assumptions. Since ash particles are larger than typical particles in the standard model, gravitational settling across all vertical layers is included. We attempt finally a specific validation of the simulation of ash and its vertical distribution. Model simulations with and without gravitational settling for the 2010 Eyjafjallajökull eruption are compared to lidar observations over central Europe. The results show that with gravitation the centre of the ash mass can be 1 km lower over central Europe than without gravitation. However, the height variations in the ash layer caused by real weather situations are not captured perfectly well by either of the two simulations, playing down the role of gravitation parameterization imperfections. Both model simulations have on average an ash centre of mass below the observed values. Correlations between the observed and corresponding model centres of mass are higher for the model simulation with gravitational settling for four of the six stations studied here. The inclusion of gravitational settling is suggested to be required for a volcanic ash model.

The volcanic fissure at Holuhraun, Iceland started at the end of August 2014 and continued for 6 months to the end of February 2015, with an extensive lava flow onto the Holuhraun plain. This event was associated with large SO2 emissions, amounting up to approximately 4.5 times the daily anthropogenic SO2 emitted from the 28 European Union countries, Norway, Switzerland and Iceland. In this paper we present results from EMEP/MSC-W model simulations to which we added 750 kg s−1 SO2 emissions at the Holuhraun plain from September to November (SON), testing three different emission heights. The three simulated SO2 concentrations, weighted with the OMI (Ozone Monitoring Instrument) satellite averaging kernel, are found to be within 30 % of the satellite-observed SO2 column burden. Constraining the SO2 column burden with the satellite data while using the kernel along with the three simulated height distributions of SO2, we estimate that the median of the daily burdens may have been between 13 and 40 kt in the North Atlantic area under investigation. We suggest this to be the uncertainty in the satellite-derived burdens of SO2, mainly due to the unknown vertical distribution of SO2. Surface observations in Europe outside Iceland showed concentration increases up to > 500 µg m−3 SO2 from volcanic plumes passing. Three well identified episodes, where the plume crossed several countries, are compared in detail to surface measurements. For all events, the general timing of the observed concentration peaks compared quite well to the model results. The overall changes to the European SO2 budget due to the volcanic fissure are estimated. Three-monthly wet deposition (SON) of SOx in the 28 European Union countries, Norway and Switzerland is found to be more than 30 % higher in the model simulation with Holuhraun emissions compared to a model simulation with no Holuhraun emissions. The largest increases, apart from extreme values on Iceland, are found on the coast of northern Norway, a region with frequent precipitation during westerly winds. Over a 3-month average (during SON 2014) over Europe, SO2 and PM2.5 surface concentrations, due to the volcanic emissions, increased by only ten and 6 % respectively. Although the percent increase of PM2.5 concentration is highest over Scandinavia and Scotland, an increase in PM exceedance days is found over Ireland and the already polluted Benelux region (up to 3 additional days), where any small increase in particulate matter concentration leads to an increase in exceedance days.

The ability of 11 models in simulating the aerosol vertical distribution from regional to global scales, as part of the second phase of the AeroCom model intercomparison initiative (AeroCom II), is assessed and compared to results of the first phase. The evaluation is performed using a global monthly gridded data set of aerosol extinction profiles built for this purpose from the CALIOP (Cloud-Aerosol Lidar with Orthogonal Polarization) Layer Product 3.01. Results over 12 subcontinental regions show that five models improved, whereas three degraded in reproducing the interregional variability in Zα0–6 km, the mean extinction height diagnostic, as computed from the CALIOP aerosol profiles over the 0–6 km altitude range for each studied region and season. While the models' performance remains highly variable, the simulation of the timing of the Zα0–6 km peak season has also improved for all but two models from AeroCom Phase I to Phase II. The biases in Zα0–6 km are smaller in all regions except Central Atlantic, East Asia, and North and South Africa. Most of the models now underestimate Zα0–6 km over land, notably in the dust and biomass burning regions in Asia and Africa. At global scale, the AeroCom II models better reproduce the Zα0–6 km latitudinal variability over ocean than over land. Hypotheses for the performance and evolution of the individual models and for the intermodel diversity are discussed. We also provide an analysis of the CALIOP limitations and uncertainties contributing to the differences between the simulations and observations.

This paper presents a new version of the EMEP MSC-W model called eEMEP developed for transportation and dispersion of volcanic emissions, both gases and ash. EMEP MSC-W is usually applied to study problems with air pollution and aerosol transport and requires some adaptation to treat volcanic eruption sources and effluent dispersion. The operational setup of model simulations in case of a volcanic eruption is described. Important choices have to be made to achieve CPU efficiency so that emergency situations can be tackled in time, answering relevant questions of ash advisory authorities. An efficient model needs to balance complexity of the model and resolution. We have investigated here a meteorological uncertainty component of the volcanic cloud forecast by using a consistent ensemble meteorological dataset (GLAMEPS forecast) in three resolutions for the case of SO2 effusion from the 2014 Barðarbunga eruption. The low resolution (40 × 40 km) ensemble members show larger agreement in plume position and intensity, suggesting that the ensemble here don't give much added value. For comparing the dispersion in different resolutions we compute the area where the column load of the volcanic tracer, here SO2, is above a certain threshold, varied for testing purposed between 0.25–50 DU Dobson units. The increased numerical diffusion causes a larger area (+34 %) to be covered by the volcanic tracer in the low resolution simulations than in the high resolution ones. The higher resolution (10 × 10 km) ensemble members show higher concentrations farther away from the volcanic eruption site in more narrow plumes. Plume positions are more varied between the high resolution members, while the plume form resemble the observed plumes more than the low resolution ones. For a volcanic emergency case this means: To obtain quickly results of the transport of volcanic emissions an individual simulation with our low resolution is sufficient, however, to forecast peak concentrations with more certainty for forecast or scientific analysis purposes a finer resolution is needed. The model is further developed to simulate ash from highly explosive eruptions. A possibility to increase the number of vertical layers, achieving finer vertical resolution, as well as a higher model top is included in the eEMEP version. Ash size distributions may be altered for different volcanic eruptions and assumptions. Since ash particles are larger than typical particles in the standard model, gravitational settling across all vertical layers is included. We attempt finally a specific validation of the simulation of ash and its vertical distribution. Model simulations with and without gravitational settling for the 2010 Eyjafjallajökull eruption are compared to lidar observations over Central Europe. The results show that with gravitation the centre of ash mass can be 1km lower over central Europe than without gravitation. However the height variations in the ash layer caused by real weather situations are not captured perfectly well by either of the two simulations, playing down the role of gravitation parameterization imperfections. Both model simulations have on average ash centre of mass below the observed values. Correlation between the observed and corresponding model centre of mass are higher for the model simulation with gravitational settling for four of six stations studied here. The inclusion of gravitational settling is suggested to be required for a volcanic ash model.

Significant improvements in the way we can observe and model volcanic ash clouds have been obtained since the 2010 Eyjafjallajökull eruption. One major development has been the application of data assimilation techniques, which combine models and satellite observations such that an optimal understanding of ash clouds can be gained. Still, questions remain regarding the degree to which the forecasting capabilities are improved by inclusion of such techniques and how these improvements depend on the data input. This study explores how different satellite data and different uncertainty assumptions of the satellite and a priori emissions affect the calculated volcanic ash emission estimate, which is computed by an inversion method that couples the satellite retrievals and a priori emissions with dispersion model data. Two major ash episodes over 4 days in April and May of the 2010 Eyjafjallajökull eruption are studied. Specifically, inversion calculations are done for four different satellite data sets with different size distribution assumptions in the retrieval. A reference satellite data set is chosen, and the range between the minimum and maximum 4-day average load of hourly retrieved ash is 121 % in April and 148 % in May, compared to the reference. The corresponding a posteriori maximum and minimum emission sum found for these four satellite retrievals is 26 and 47 % of the a posteriori reference estimate for the same two periods, respectively. Varying the assumptions made in the satellite retrieval is seen to affect the a posteriori emissions and modelled ash column loads, and modelled column loads therefore have uncertainties connected to them depending on the uncertainty in the satellite retrieval. By further exploring our uncertainty estimates connected to a priori emissions and the mass load uncertainties in the satellite data, the uncertainty in the a priori estimate is found in this case to have an order-of-magnitude-greater impact on the a posteriori solution than the mass load uncertainties in the satellite. Part of this is explained by a too-high a priori estimate used in this study that is reduced by around half in the a posteriori reference estimate. Setting large uncertainties connected to both a priori and satellite mass load shows that they compensate each other, but the a priori uncertainty is found to be most sensitive. Because of this, an inversion-based emission estimate in a forecasting setting needs well-tested and well-considered assumptions on uncertainties for the a priori emission and satellite data. The quality of using the inversion in a forecasting environment is tested by adding gradually, with time, more observations to improve the estimated height versus time evolution of Eyjafjallajökull ash emissions. We show that the initially too-high a priori emissions are reduced effectively when using just 12 h of satellite observations. More satellite observations (> 12 h), in the Eyjafjallajökull case, place the volcanic injection at higher altitudes. Adding additional satellite observations (> 36 h) changes the a posteriori emissions to only a small extent for May and minimal for the April period, because the ash is dispersed and transported effectively out of the domain after 1–2 days. A best-guess emission estimate for the forecasting period was constructed by averaging the last 12 h of the a posteriori emission. Using this emission for a forecast simulation leads to better performance, especially compared to model simulations with no further emissions over the forecast period in the case of a continued volcanic eruption activity. Because of undetected ash in the satellite retrieval and diffusion in the model, the forecast simulations generally contain more ash than the observed fields, and the model ash is more spread out. Overall, using the a posteriori emissions in our model reduces the uncertainties in the ash plume forecast, because it corrects effectively for false-positive satellite retrievals, temporary gaps in observations, and false a priori emissions in the window of observation.

A 6-models strong European ensemble of Copernicus Atmospheric Monitoring Service (CAMS) was run through the season of 2014 computing the olive pollen dispersion in Europe. The simulations have been compared with observations in 6 countries, members of the European Aeroallergen Network. Analysis was performed for individual models, the ensemble mean and median, and for a dynamically optimized combination of the ensemble members obtained via fusion of the model predictions with observations. The models, generally reproducing the olive season of 2014, showed noticeable deviations from both observations and each other. In particular, the season start was reported too early, by 8 days but for some models the error mounted to almost two weeks. For the season end, the disagreement between the models and the observations varied from a nearly perfect match up to two weeks too late. A series of sensitivity studies performed to understand the origin of the disagreements revealed crucial role of ambient temperature, especially systematic biases in its representation by meteorological models. A simple correction to the heat sum threshold eliminated the season shift but its validity in other years remains to be checked. The short-term features of the concentration time series were reproduced better suggesting that the precipitation events and cold/warm spells, as well as the large-scale transport were represented rather well. Ensemble averaging led to more robust results. The best skill scores were obtained with data fusion, which used the previous-days observations to identify the optimal weighting coefficients of the individual model forecasts. Such combinations were tested for the forecasting period up to 4 days and shown to remain nearly optimal throughout the whole period.

The volcanic fissure at Holuhraun, Iceland started at the end of August 2014 and continued for six months to the end of February 2015. Lava floated onto the Holuhraun plain associated with large SO2 emissions. In this paper we present results from EMEP/MSC-W model simulations where we added 750 kg/s SO2 emissions at the Holuhraun plain from September to November. The emission amounted to approximately 4.5 times the daily anthropogenic SO2 emitted from the 28 European Union countries, Norway, Switzerland and Iceland. Model results are compared to satellite observations and European surface measurements. The dispersion but also the ambiguity of the satellite data, due to what is assumed in the retrieval as a priori SO2 profile, is further explored with model sensitivity runs using different emission height distributions from the volcano. Satellite-comparable adjusted model vertical column densities are calculated for the different sensitivity runs where the SO2 mixing ratios from different vertical layers are weighted with the averaging kernel. The results show the importance of using the averaging kernel when comparing the model to satellite column loads, the maximum column densities over 10 DU in the original model data are reduced by around 50 % due to the weighting. For most days the satellite retrievals have higher mass burdens values than the adjusted model when summed up over the North Atlantic area. The discrepancies are explained by the unrealistic constant emission term in the model simulations, and because the area used for the summation is dependent on the satellite data detection limit, and the correct position of the model SO2 plume. Surface observations in Europe showed peak type increases of SO2 concentrations from volcanic plumes passing by and lasting only for a short time. Three well identified episodes are documented for more detail. For all the events the timing of the observed concentration peaks compared to the model quite well. For the first episode presented, the model concentrations are only about 10 % to 40 % of the observed concentrations. The transport of SO2 to Europe during this event is found to contribute to very high measured and modelled concentrations at the stations. For the later plumes, the observed and model concentrations at the stations compare better in magnitude. The overall changes in the European SO2 budget due to the volcanic fissure are estimated. SOX three monthly wet deposition in the 28 European Union countries, Norway and Switzerland is found to be more than 30 % higher in the control model simulation with Holuhraun emission compared to a model simulation with no Holuhraun emission. The biggest increases, apart from Iceland, are found on the coast of Northern Norway, a region with frequent precipitation during westerly winds. The total deposition levels in this region become equal to the most polluted regions over Europe and the average model deposition for Norway is doubled the level it was back in 1990. For SO2 and PM2.5 concentrations, there is only a ten and six percent increase over Europe between the two model simulations, respectively. Although the percent increase of PM2.5 concentration is highest over Scandinavia and Scotland, an increase in PM exceedance days is found over Ireland and the Benelux region. Especially the Benelux region is already very polluted, so that a small increase in pollution leads to an increase in exceedances days. Although there was a large increase in total daily emission of SO2 over Europe due to the eruption, Iceland is located too far away to make a large impact on average pollution levels in the European countries, except in Iceland itself.

This paper presents the first ensemble modelling experiment in relation to birch pollen in Europe. The seven-model European ensemble of MACC-ENS, tested in trial simulations over the flowering season of 2010, was run through the flowering season of 2013. The simulations have been compared with observations in 11 countries, all members of the European Aeroallergen Network, for both individual models and the ensemble mean and median. It is shown that the models successfully reproduced the timing of the very late season of 2013, generally within a couple of days from the observed start of the season. The end of the season was generally predicted later than observed, by 5 days or more, which is a known feature of the source term used in the study. Absolute pollen concentrations during the season were somewhat underestimated in the southern part of the birch habitat. In the northern part of Europe, a record-low pollen season was strongly overestimated by all models. The median of the multi-model ensemble demonstrated robust performance, successfully eliminating the impact of outliers, which was particularly useful since for most models this was the first experience of pollen forecasting.

At the end of January and beginning of February 2006, an extreme precipitation event occurred over Central Norway. The precipitation in addition to warm temperatures produced flooding and landslides that caused considerable damage to infrastructure. The event is explored with conventional data, data from remote sensing and numerical simulations. It is shown that there was very little quasi-geostrophic forcing during the event and that the extreme precipitation is locally generated by strong and persistent winds impinging the mountains. The mountains in the southwestern part of Norway, far away from the precipitation, contributed significantly to the extreme, by blocking, deflection and enhancement of the low-level flow. The warm and humid air masses involved are shown to originate in the subtropics. Assessment of forecasts with different lead times reveal a sensitivity to a baroclinic system to the east of Newfoundland upstream of the event in Central Norway.

At the end of January and beginning of February 2006, an extreme precipitation event occurred over Central Norway. The precipitation in addition to warm temperatures produced flooding and landslides that caused considerable damage to infrastructure. The event is explored with conventional data, data from remote sensing and numerical simulations. It is shown that there was very little quasi-geostrophic forcing during the event and that the extreme precipitation is locally generated by strong and persistent winds impinging the mountains. The mountains in the southwestern part of Norway, far away from the precipitation, contributed significantly to the extreme, by blocking, deflection and enhancement of the low-level flow. The warm and humid air masses involved are shown to originate in the subtropics. Assessment of forecasts with different lead times reveal a sensitivity to a baroclinic system to the east of Newfoundland upstream of the event in Central Norway.