Effects of Particle Nonsphericity on Dust Optical Properties in a Forecast System: Implications for Model‐Observation Comparison

Hoshyaripour, Gholam Ali; Bachmann, Vanessa; Förstner, Jochen; Steiner, Andrea; Vogel, H.; Wagner, Frank; Walter, Carolin; Vogel, Bernhard

doi:10.1029/2018jd030228

Cited by 21 publications

(24 citation statements)

References 70 publications

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“…The vertical distribution, particle size distribution, and mass concentration are the key properties that are predicted in a dust transport model. On the other hand, the main observable quantity on a global scale is aerosol optical depth from AERONET (Holben et al, 1998), MODIS (Hsu et al, 2004(Hsu et al, , 2006(Hsu et al, , 2013Levy et al, 2013;Sayer et al, 2013Sayer et al, , 2014, and potentially other sources such as the Polar Multi-Sensor Aerosol product (PMAp; Lang et al, 2017), the Visible Infrared Imaging Radiometer Suite (VIIRS; Hsu et al, 2019), and several others. Aerosol optical depth is at the same time an optical property and a vertically integrated quantity, meaning that the same observable AOD can be retrieved e.g.…”

Section: Discussionmentioning

confidence: 99%

“…MODIS collection 6.1 level 2 atmospheric aerosol products from Aqua (MYD04_L2) and Terra (MOD04_L2) were obtained from the Level-1 and Atmosphere Archive & Distribution System (LAADS, ftp://ladsftp.nascom.nasa.gov/ allData/61/, last access: 21 September 2017). The merged Deep Blue and Dark Target aerosol optical depth at 550 nm from both Aqua and Terra was used to create daily AOD maps (Hsu et al, 2004(Hsu et al, , 2006(Hsu et al, , 2013Levy et al, 2013;Sayer et al, 2013Sayer et al, , 2014. The differences between the collection 5 (used in both models for operational assimilation in August 2015) and the subsequently released collection 6 are treated in detail in the above-referenced papers.…”

Section: Satellite Datasetsmentioning

confidence: 99%

“…Aerosol Robotic Network (AERONET) sun photometer retrievals (Holben et al, 1998) play an important role in dust model evaluation (for example, see Scanza et al, 2015;Cuevas et al, 2015;Ridley et al, 2016) and offer nearly continuous measurements and, for some stations, long observation records. However, AERONET instruments do not provide information on vertical distribution.…”

Section: Introductionmentioning

confidence: 99%

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Models transport Saharan dust too low in the atmosphere: a comparison of the MetUM and CAMS forecasts with observations

et al. 2020

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Abstract. We investigate the dust forecasts from two operational global atmospheric models in comparison with in situ and remote sensing measurements obtained during the AERosol properties – Dust (AER-D) field campaign. Airborne elastic backscatter lidar measurements were performed on board the Facility for Airborne Atmospheric Measurements during August 2015 over the eastern Atlantic, and they permitted us to characterise the dust vertical distribution in detail, offering insights on transport from the Sahara. They were complemented with airborne in situ measurements of dust size distribution and optical properties, as well as datasets from the Cloud–Aerosol Transport System (CATS) spaceborne lidar and the Moderate Resolution Imaging Spectroradiometer (MODIS). We compare the airborne and spaceborne datasets to operational predictions obtained from the Met Office Unified Model (MetUM) and the Copernicus Atmosphere Monitoring Service (CAMS). The dust aerosol optical depth predictions from the models are generally in agreement with the observations but display a low bias. However, the predicted vertical distribution places the dust lower in the atmosphere than highlighted in our observations. This is particularly noticeable for the MetUM, which does not transport coarse dust high enough in the atmosphere or far enough away from the source. We also found that both model forecasts underpredict coarse-mode dust and at times overpredict fine-mode dust, but as they are fine-tuned to represent the observed optical depth, the fine mode is set to compensate for the underestimation of the coarse mode. As aerosol–cloud interactions are dependent on particle numbers rather than on the optical properties, this behaviour is likely to affect their correct representation. This leads us to propose an augmentation of the set of aerosol observations available on a global scale for constraining models, with a better focus on the vertical distribution and on the particle size distribution. Mineral dust is a major component of the climate system; therefore, it is important to work towards improving how models reproduce its properties and transport mechanisms.

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Section: Discussionmentioning

confidence: 99%

Section: Satellite Datasetsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Models transport Saharan dust too low in the atmosphere: a comparison of the MetUM and CAMS forecasts with observations

et al. 2020

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“…Their optical properties, such as the lidar ratio, are also subject to their chemical composition. Therefore, dust particles originating from different regions exhibit different scattering properties due to their different microphysical and chemical composition (Järvinen et al, 2016;Müller et al, 2007;Nisantzi et al, 2015;Shin et al, 2018). Mineral dust and other aerosol particle types can affect clouds and their microphysical properties and precipitation patterns by acting as cloud condensation nuclei (CCN) and ice nuclei (IN) (DeMott et al, 2003;Karydis et al, 2011).…”

Section: Introductionmentioning

confidence: 99%

Optical and geometrical aerosol particle properties over the United Arab Emirates

Filioglou¹,

Giannakaki²,

Backman³

et al. 2020

Atmos. Chem. Phys.

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Abstract. One year of ground-based night-time Raman lidar observations has been analysed under the Optimization of Aerosol Seeding In rain enhancement Strategies (OASIS) project, in order to characterize the aerosol particle properties over a rural site in the United Arab Emirates. In total, 1130 aerosol particle layers were detected during the 1-year measurement campaign which took place between March 2018 and February 2019. Several subsequent aerosol layers could be observed simultaneously in the atmosphere up to 11 km. The observations indicate that the measurement site is a receptor of frequent dust events, but predominantly the dust is mixed with aerosols of anthropogenic and/or marine origin. The mean aerosol optical depth over the measurement site ranged at 0.37 ± 0.12 and 0.21 ± 0.11 for 355 and 532 nm, respectively. Moreover, mean lidar ratios of 43 ± 11 sr at a wavelength of 355 nm and 39 ± 10 sr at 532 nm were found. The average linear particle depolarization ratio measured over the course of the campaign was 15 ± 6 % and 19 ± 7 % at the 355 and 532 nm wavelengths, respectively. Since the region is both a source and a receptor of mineral dust, we have also explored the properties of Arabian mineral dust of the greater area of the United Arab of Emirates and the Arabian Peninsula. The observed Arabian dust particle properties were 45 ± 5 (42 ± 5) sr at 355 (532) nm for the lidar ratio, 25 ± 2 % (31 ± 2 %) for the linear particle depolarization ratio at 355 (532) nm, and 0.3 ± 0.2 (0.2 ± 0.2) for the extinction-related Ångström exponent (backscatter-related Ångström exponent) between 355 and 532 nm. This study is the first to report comprehensive optical properties of the Arabian dust particles based on 1-year long observations, using to their fullest the capabilities of a multi-wavelength Raman lidar instrument. The results suggest that the mineral dust properties over the Middle East and western Asia, including the observation site, are comparable to those of African mineral dust with regard to the particle depolarization ratios, but not for lidar ratios. The smaller lidar ratio values in this study compared to the reference studies are attributed to the difference in the geochemical characteristics of the soil originating in the study region compared to northern Africa.

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“…This approach ensures full coupling and feedback between aerosol processes, radiation and the atmospheric state (Shao et al, 2011). Besides, a forward operator is implemented in the model to diagnose the attenuated backscatter at the wavelengths 532 and 1064 nm (Hoshyaripour et al, 2019). To account for secondary aerosol formation and internally mixed aerosols, a new aerosol dynamics module is currently developed and implemented in ICON-ART.…”

Section: Volcanic Cloud Height From Modis Viirs Omps and Caliopmentioning

confidence: 99%

Particle Aging and Aerosol–Radiation Interaction Affect Volcanic Plume Dispersion: Evidence from Raikoke Eruption 2019

Muser¹,

Hoshyaripour²,

Bruckert³

et al. 2020

Preprint

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Abstract. A correct and reliable forecast of volcanic plume dispersion is vital for aviation safety. This can only be achieved by representing all responsible physical and chemical processes (sources, sinks, and interactions) in the forecast models. The representation of the sources has been enhanced over the last decade, while the sinks and interactions have received less attention. In particular, aerosol dynamic processes and aerosol-radiation interaction are neglected so far. Here we address this gap by further developing the ICON-ART (ICOsahedral Nonhydrostatic – Aerosols and Reactive Trace gases) global modelling system to account for these processes. We use this extended model for the simulation of volcanic aerosol dispersion after the Raikoke eruption in June 2019. Additionally, we validate the simulation results with measurements from AHI (Advanced Himawari Imager), CALIOP (Cloud-Aerosol Lidar with Orthogonal Polarization), and OMPS-LP (Ozone Mapping and Profiling Suite – Limb Profiler). Our results show that around 50 % of very fine volcanic ash mass (particles with diameter d < 30 µm) is removed due to particle growth and aging. Furthermore, the maximum volcanic cloud top height rises more than 6 km over the course of 4 days after the eruption due to aerosol-radiation interaction. This is the first direct evidence that shows how cumulative effects of aerosol dynamics and aerosol-radiation interaction lead to a more precise forecast of very fine ash lifetime in volcanic clouds.

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Effects of Particle Nonsphericity on Dust Optical Properties in a Forecast System: Implications for Model‐Observation Comparison

Cited by 21 publications

References 70 publications

Models transport Saharan dust too low in the atmosphere: a comparison of the MetUM and CAMS forecasts with observations

Models transport Saharan dust too low in the atmosphere: a comparison of the MetUM and CAMS forecasts with observations

Optical and geometrical aerosol particle properties over the United Arab Emirates

Particle Aging and Aerosol–Radiation Interaction Affect Volcanic Plume Dispersion: Evidence from Raikoke Eruption 2019

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