Aerosol optical properties over Europe: an evaluation of the AQMEII Phase 3 simulations against satellite observations

Abstract. The main uncertainties regarding the estimation of changes in the Earth's energy budget are related to the role of atmospheric aerosols. These changes are caused by aerosol–radiation (ARIs) and aerosol–cloud interactions (ACIs), which heavily depend on aerosol properties. Since the 1980s, many international modeling initiatives have studied atmospheric aerosols and their climate effects. Phase 3 of the Air Quality Modelling Evaluation International Initiative (AQMEII) focuses on evaluating and intercomparing regional and linked global/regional modeling systems by collaborating with the Task Force on the Hemispheric Transport of Air Pollution Phase 2 (HTAP2) initiative. Within this framework, the main aim of this work is the assessment of the representation of aerosol optical depth (AOD) and the Ångström exponent (AE) in AQMEII Phase 3 simulations over Europe. The evaluation was made using remote-sensing data from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensors aboard the Terra and Aqua platforms, and the instruments belonging to the ground-based Aerosol Robotic Network (AERONET) and the Maritime Aerosol Network (MAN). Overall, the skills of AQMEII simulations when representing AOD (mean absolute errors from 0.05 to 0.30) produced lower errors than for the AE (mean absolute errors from 0.30 to 1). Regardless of the models or the emissions used, models were skillful at representing the low and mean AOD values observed (below 0.5). However, high values (around 1.0) were overpredicted for biomass burning episodes, due to an underestimation in the common fires' emissions, and were overestimated for coarse particles – principally desert dust – related to the boundary conditions. Despite this behavior, the spatial and temporal variability of AOD was better represented by all the models than AE variability, which was strongly underestimated in all the simulations. Noticeably, the impact of the model selection when representing aerosol optical properties is higher than the use of different emission inventories. On the other hand, the influence of ARIs and ACIs has a little visible impact compared to the impact of the model used

On the combined use of rain gauges and GPM IMERG satellite rainfall products for hydrological modelling: impact assessment of the cellular-automata-based methodology in the Tanaro River basin in Italy

The uncertainty of hydrological forecasts is strongly related to the uncertainty of the rainfall field due to the nonlinear relationship between the spatio-temporal pattern of rainfall and runoff. Rain gauges are typically considered to provide reference data to rebuild precipitation fields. However, due to the density and the distribution variability of the rain gauge network, the rebuilding of the precipitation field can be affected by severe errors which compromise the hydrological simulation output. On the other hand, retrievals obtained from remote sensing observations provide spatially resolved precipitation fields, improving their representativeness. In this regard, the comparison between simulated and observed river flow discharge is crucial for assessing the effectiveness of merged precipitation data in enhancing the model's performance and its ability to realistically simulate hydrological processes. This paper aims to investigate the hydrological impact of using the merged rainfall fields from the Italian rain gauge network and the NASA Global Precipitation Measurement (GPM) IMERG precipitation product. One aspect is to highlight the benefits of applying the cellular automata algorithm to pre-process input data in order to merge them and reconstruct an improved version of the precipitation field. The cellular automata approach is evaluated in the Tanaro River basin, one of the tributaries of the Po River in Italy. As this site is characterized by the coexistence of a variety of natural morphologies, from mountain to alluvial environments, as well as the presence of significant civil and industrial settlements, it makes it a suitable case study to apply the proposed approach. The latter has been applied over three different flood events that occurred from November to December 2014. The results confirm that the use of merged gauge–satellite data using the cellular automata algorithm improves the performance of the hydrological simulation, as also confirmed by the statistical analysis performed for 17 selected quality scores.</p

Analysis of Summer Ozone Observations at a High Mountain Site in Central Italy (Campo Imperatore, 2388 m a.s.l.)

Tropospheric ozone (O3) is an important atmospheric pollutant and climate forcer. The Mediterranean basin is a hot-spot region in terms of short-term O3 distribution, with frequent episodes of high tropospheric O3, especially during summer. To improve the characterisation of summer O3 variability in the Mediterranean area, during the period 6–27 August 2009 an experimental campaign was conducted at Campo Imperatore, Mt Portella (CMP), a high mountain site (2,388 m a.s.l.) located in the central Italian Apennines. As deduced from analysis of atmospheric circulation, the measurement site was significantly affected by air masses originating over the Mediterranean basin, which affected the measurement site for 32 % of the time. Analysis of average values and diurnal and day-to-day variability revealed that CMP O3 observations (average value 60.0 ± 5.1 ppbv) were comparable with measurements at other European mountain stations, indicating a prevalent effect of meteorological conditions and atmospheric transport on the synoptic scale. In fact, only a small "reverse" diurnal variation typically characterises diurnal O3 variability because of local thermal wind circulation, which sporadically favours transport of air masses rich in O3 from the foothill regions. Statistical analysis of five-day back-trajectory ensembles indicates that synoptic-scale air-mass transport from the Mediterranean Sea usually results in decreasing O3 concentrations at CMP, whereas the highest hourly O3 values are mostly associated with air masses from central continental Europe, eastern Europe, and northern Italy. High O3 concentrations are also related to downward air-mass transport from higher altitudes. Comparison of in-situ O3 variability with tropospheric O3 satellite-based measurements reveals similar features of the two data sets. Together with the results from back-trajectory analysis, this indicates that CMP measurements might usefully improve characterisation of broad-scale O3 variability over the central Mediterranean basin

Sensitivity of feedback effects in CBMZ/MOSAIC chemical mechanism

To investigate the impact of the aerosol effects on meteorological variables and pollutant concentrations two simulations with the WRF-Chem model have been performed over Europe for year 2010. We have performed a baseline simulation without any feedback effects and a second simulation including the direct as well as the indirect aerosol effect. The paper describes the full configuration of the model, the simulation design, special impacts and evaluation. Although low aerosol particle concentrations are detected, the inclusion of the feedback effects results in an increase of solar radiation at the surface over cloudy areas (North-West, including the Atlantic) and decrease over more sunny locations (South-East). Aerosol effects produce an increase of the water vapor and decrease the planet boundary layer height over the whole domain except in the Sahara area, where the maximum particle concentrations are detected. Significant ozone concentrations are found over the Mediterranean area. Simulated feedback effects between aerosol concentrations and meteorological variables and on pollutant distributions strongly depend on the aerosol concentrations and the clouds. Further investigations are necessary with higher aerosol particle concentrations. WRF-Chem variables are evaluated using available hourly observations in terms of performance statistics. Standardized observations from the ENSEMBLE system web-interface were used. The research was developed under the second phase of Air Quality Model Evaluation International Initiative (AQMEII). WRF-Chem demonstrates its capability in capturing temporal and spatial variations of the major meteorological variables and pollutants, except the wind speed over complex terrain. The wind speed bias may affect the accuracy in the chemical predictions (NO2, SO2). The analysis of the correlations between simulated data sets and observational data sets indicates that the simulation with aerosol effects performs slightly better. These results indicate potential importance of the aerosol feedback effects and an urgent need to further improve the representations in current atmospheric models to reduce uncertainties at all scales

Insights into the deterministic skill of air quality ensembles from the analysis of AQMEII data

© 2016. This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution, and reproduction in any medium, provided the original work is properly cited. Ioannis Kioutsioukis, et al, ‘Insights into the deterministic skill of air quality ensembles from the analysis of AQMEII data’, Atmospheric Chemistry and Physics, Vol 16(24): 15629-15652, published 20 December 2016, the version of record is available at doi:10.5194/acp-16-15629-2016 Published by Copernicus Publications on behalf of the European Geosciences Union.Simulations from chemical weather models are subject to uncertainties in the input data (e.g. emission inventory, initial and boundary conditions) as well as those intrinsic to the model (e.g. physical parameterization, chemical mechanism). Multi-model ensembles can improve the forecast skill, provided that certain mathematical conditions are fulfilled. In this work, four ensemble methods were applied to two different datasets, and their performance was compared for ozone (O3), nitrogen dioxide (NO2) and particulate matter (PM10). Apart from the unconditional ensemble average, the approach behind the other three methods relies on adding optimum weights to members or constraining the ensemble to those members that meet certain conditions in time or frequency domain. The two different datasets were created for the first and second phase of the Air Quality Model Evaluation International Initiative (AQMEII). The methods are evaluated against ground level observations collected from the EMEP (European Monitoring and Evaluation Programme) and AirBase databases. The goal of the study is to quantify to what extent we can extract predictable signals from an ensemble with superior skill over the single models and the ensemble mean. Verification statistics show that the deterministic models simulate better O3 than NO2 and PM10, linked to different levels of complexity in the represented processes. The unconditional ensemble mean achieves higher skill compared to each station's best deterministic model at no more than 60 % of the sites, indicating a combination of members with unbalanced skill difference and error dependence for the rest. The promotion of the right amount of accuracy and diversity within the ensemble results in an average additional skill of up to 31 % compared to using the full ensemble in an unconditional way. The skill improvements were higher for O3 and lower for PM10, associated with the extent of potential changes in the joint distribution of accuracy and diversity in the ensembles. The skill enhancement was superior using the weighting scheme, but the training period required to acquire representative weights was longer compared to the sub-selecting schemes. Further development of the method is discussed in the conclusion.Peer reviewedFinal Published versio

Modelling black carbon absorption of solar radiation: combining external and internal mixing assumptions

An accurate simulation of the absorption properties is key for assessing the radiative effects of aerosol on meteorology and climate. The representation of how chemical species are mixed inside the particles (the mixing state) is one of the major uncertainty factors in the assessment of these effects. Here we compare aerosol optical properties simulations over Europe and North America, coordinated in the framework of the third phase of the Air Quality Model Evaluation International Initiative (AQMEII), to 1 year of AERONET sunphotometer retrievals, in an attempt to identify a mixing state representation that better reproduces the observed single scattering albedo and its spectral variation. We use a single post-processing tool (FlexAOD) to derive aerosol optical properties from simulated aerosol speciation profiles, and focus on the absorption enhancement of black carbon when it is internally mixed with more scattering material, discarding from the analysis scenes dominated by dust. We found that the single scattering albedo at 440&thinsp;nm (ω0,440) is on average overestimated (underestimated) by 3–5&thinsp;% when external (core-shell internal) mixing of particles is assumed, a bias comparable in magnitude with the typical variability of the quantity. The (unphysical) homogeneous internal mixing assumption underestimates ω0,440 by ∼14&thinsp;%. The combination of external and core-shell configurations (partial internal mixing), parameterized using a simplified function of air mass aging, reduces the ω0,440 bias to -1/-3&thinsp;%. The black carbon absorption enhancement (Eabs) in core-shell with respect to the externally mixed state is in the range 1.8–2.5, which is above the currently most accepted upper limit of ∼1.5. The partial internal mixing reduces Eabs to values more consistent with this limit. However, the spectral dependence of the absorption is not well reproduced, and the absorption Ångström exponent AAE675440 is overestimated by 70–120&thinsp;%. Further testing against more comprehensive campaign data, including a full characterization of the aerosol profile in terms of chemical speciation, mixing state, and related optical properties, would help in putting a better constraint on these calculations.</p