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

Abstract

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.

Added Value of Aerosol-Cloud Interactions for Representing Aerosol Optical Depth in an Online Coupled Climate-Chemistry Model over Europe

“…The results of the modelling system presented here have been extensively evaluated in previous works. In this sense, the simulations have been compared to the remote-sensing data from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensors aboard the Terra and Aqua platforms (MOD04_L2 and MYD04_L2) from collection six (C6) [18], finding that large underestimations in the simulations can be related to the misrepresentation of black carbon coming from biomass burning episodes. Also, the slight underestimations found for AODTO can be ascribed to a misrepresentation of the aerosol vertical profile modelled in these simulations [12].…”

“…Hence, regional online coupled models improve those values, with AOD biases of 0.015 for both ARI and ACI simulations, a bias 50% lower than that found for global models as a consequence of the higher resolution used in regional models. In addition, Palacios et al [18] used an ensemble of models from AQMEII Phase 3 [17] to assess AODTO against in-situ and remote sensing observations, finding out that the biases of the ensemble of AQMEII simulations when representing AOD are in the order of 0.05. In this sense, the bias observed in our evaluation is again lower than those found in the literature, pointing out to an accurate skill of the model when reproducing aerosol climatologies over the European area.…”

“…The bias for AODTO is higher in northern Africa, caused by the pervasive underestimation of the aerosol load coming from the Sahara desert (AODDU is underestimated by 0.02-0.04 in this area, representing an underestimation of over 20% of AOD). However, AODDU in northern Europe is slightly overestimated, especially over the northeastern part of the domain, caused by the unrealistic high values of dust coming from the Gobbi desert through the boundary conditions [12,18]. AODSU presents a slight underestimation (Table 2) both in ARI (−0.64 × 10 −3 ) and ACI simulations (−0.55 × 10 −3 ), especially over eastern Europe, which can be related to a strong underestimation of winter sulphate aerosol [71,72].…”

“…Thus, motivated by a better understanding of the impact of ARI and/or ACI on a regional scale, online chemistry/climate models with full couplings between the air quality and meteorological/climatological components have been developed and applied recently (e.g., [10][11][12]). A growing number of studies have recently started to address the coupling of aerosols and clouds in regional chemistry/climate models, coordinated through collaborative European projects from FP7 and Horizon 2020 (e.g., MACC), International programmes such as AQMEII [13][14][15][16][17][18]; or COST Actions like ES1004-EuMetChem [12,19,20]. However, as observed in the scientific literature, the application of regional chemistry/climate on-line coupled models is currently biased towards studies of isolated episodes (e.g., [21][22][23][24]) because of the demanding computational resources.…”

Saharan Dust Modeling Over the Mediterranean Basin and Central Europe: Does the Resolution Matter?

“…As this network is associated with AERONET and uses its standards, AOD uncertainty is < ± 0.02 (Smirnov et al, 2009). Further details on the evaluation of the model using MODIS, MAN and AERONET can be found in Palacios-Peña et al 2018and Palacios-Peña et al (2019).…”