Aerosol optical properties over Europe: an evaluation of the AQMEII Phase 3 simulations against satellite observations
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Published:2019-03-07
Issue:5
Volume:19
Page:2965-2990
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ISSN:1680-7324
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Container-title:Atmospheric Chemistry and Physics
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language:en
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Short-container-title:Atmos. Chem. Phys.
Author:
Palacios-Peña LauraORCID, Jiménez-Guerrero PedroORCID, Baró Rocío, Balzarini Alessandra, Bianconi Roberto, Curci GabrieleORCID, Landi Tony ChristianORCID, Pirovano Guido, Prank Marje, Riccio Angelo, Tuccella Paolo, Galmarini StefanoORCID
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.
Publisher
Copernicus GmbH
Subject
Atmospheric Science
Reference96 articles.
1. Ackermann, I. J., Hass, H., Memmesheimer, M., Ebel, A., Binkowski, F. S., and
Shankar, U.: Modal aerosol dynamics model for Europe: development and first
applications, Atmos. Environ., 32, 2981–2999,
https://doi.org/10.1016/S1352-2310(98)00006-5, 1998. a 2. Ahmadov, R., McKeen, S. A., Robinson, A. L., Bahreini, R., Middlebrook, A. M.,
de Gouw, J. A., Meagher, J., Hsie, E.-Y., Edgerton, E., Shaw, S., and
Trainer, M.: A volatility basis set model for summertime secondary organic
aerosols over the eastern United States in 2006, J. Geophys. Res.-Atmos., 117, D06301, https://doi.org/10.1029/2011JD016831, 2012. a 3. Altaratz, O., Bar-Or, R. Z., Wollner, U., and Koren, I.: Relative humidity and
its effect on aerosol optical depth in the vicinity of convective clouds,
Environ. Res. Lett., 8, 034025,
https://doi.org/10.1088/1748-9326/8/3/034025, 2013. a, b 4. Ångström, A.: On the atmospheric transmission of sun radiation and on
dust in the air, Geogr. Ann., 11, 156–166, 1929. a 5. Balzarini, A.: Implementing the WRF-Chem modeling system to investigate the
interactions between air quality and meteorology, PhD thesis, University of
Milano-Bicocca, 2013. a, b, c
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