Aerosol processing and CCN formation of an intense Saharan dust plume during the EUCAARI 2008 campaign

Bègue, Nelson; Tulet, Pierre; Pelon, Jacques; Aouizerats, B.; Berger, Alfons; Schwarzenböeck, Alfons

doi:10.5194/acp-15-3497-2015

Cited by 39 publications

(37 citation statements)

References 128 publications

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“…With increasing maximum diameter (D max ), the ice crystals become more complex and their effective density decreases (Heymsfield et al, 2010). The DARDAR algorithm describes this relationship using a combination of in situ measurements by Brown and Francis (1995) for lowdensity aggregates (D max > 300 µm) and by Mitchell (1996) for hexagonal columns (D max < 300 µm). We derive the n ice (DARDAR-Nice) following the approach presented by Sourdeval et al (2018) on the DARDAR-Cloud parameters of the ice water content (IWC) and the normalization factor of the modified gamma size distribution (N * 0 ).…”

Section: Spaceborne Cloud Observationsmentioning

confidence: 99%

Retrieval of ice-nucleating particle concentrations from lidar observations and comparison with UAV in situ measurements

et al. 2019

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Abstract. Aerosols that are efficient ice-nucleating particles (INPs) are crucial for the formation of cloud ice via heterogeneous nucleation in the atmosphere. The distribution of INPs on a large spatial scale and as a function of height determines their impact on clouds and climate. However, in situ measurements of INPs provide sparse coverage over space and time. A promising approach to address this gap is to retrieve INP concentration profiles by combining particle concentration profiles derived by lidar measurements with INP efficiency parameterizations for different freezing mechanisms (immersion freezing, deposition nucleation). Here, we assess the feasibility of this new method for both ground-based and spaceborne lidar measurements, using in situ observations collected with unmanned aerial vehicles (UAVs) and subsequently analyzed with the FRIDGE (FRankfurt Ice nucleation Deposition freezinG Experiment) INP counter from an experimental campaign at Cyprus in April 2016. Analyzing five case studies we calculated the cloud-relevant particle number concentrations using lidar measurements (n250,dry with an uncertainty of 20 % to 40 % and Sdry with an uncertainty of 30 % to 50 %), and we assessed the suitability of the different INP parameterizations with respect to the temperature range and the type of particles considered. Specifically, our analysis suggests that our calculations using the parameterization of Ullrich et al. (2017) (applicable for the temperature range −50 to −33 ∘C) agree within 1 order of magnitude with the in situ observations of nINP; thus, the parameterization of Ullrich et al. (2017) can efficiently address the deposition nucleation pathway in dust-dominated environments. Additionally, our calculations using the combination of the parameterizations of DeMott et al. (2015, 2010) (applicable for the temperature range −35 to −9 ∘C) agree within 2 orders of magnitude with the in situ observations of INP concentrations (nINP) and can thus efficiently address the immersion/condensation pathway of dust and nondust particles. The same conclusion is derived from the compilation of the parameterizations of DeMott et al. (2015) for dust and Ullrich et al. (2017) for soot. Furthermore, we applied this methodology to estimate the INP concentration profiles before and after a cloud formation, indicating the seeding role of the particles and their subsequent impact on cloud formation and characteristics. More synergistic datasets are expected to become available in the future from EARLINET (European Aerosol Research Lidar Network) and in the frame of the European ACTRIS-RI (Aerosols, Clouds, and Trace gases Research Infrastructure). Our analysis shows that the developed techniques, when applied on CALIPSO (Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations) spaceborne lidar observations, are in agreement with the in situ measurements. This study gives us confidence for the production of global 3-D products of cloud-relevant particle number concentrations (n250,dry, Sdry and nINP) using the CALIPSO 13-year dataset. This could provide valuable insight into the global height-resolved distribution of INP concentrations related to mineral dust, as well as possibly other aerosol types.

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Section: Spaceborne Cloud Observationsmentioning

confidence: 99%

Retrieval of ice-nucleating particle concentrations from lidar observations and comparison with UAV in situ measurements

et al. 2019

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“…The days from 17 to 20 May are referred as "scavenged background situation" (Mensah et al, 2012), because they are dominated by a northerly wind from the North Sea associated with a low aerosol mass loading, due to wet scavenging. The period starting from 23 May is dominated by long-range transport of dust from Sahara desert (Roelofs et al, 2010;Bègue et al, 2015).…”

Section: Measurementsmentioning

confidence: 99%

“…OM prediction is also affected by meteorological errors. Bei et al (2012) found that the uncertainties in meteorological initial conditions have a significant impact on the simulations of the peaks, horizontal distribution, and temporal variation of SOA. The same authors demonstrated that the spread of the simulated peaks can reach up to 4.0 µg m −3 .…”

Section: Aloft Aerosol Mass Concentrationmentioning

confidence: 99%

A new chemistry option in WRF-Chem v. 3.4 for the simulation of direct and indirect aerosol effects using VBS: evaluation against IMPACT-EUCAARI data

et al. 2015

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International audienceA parameterization for secondary organic aerosol (SOA) production based on the volatility basis set (VBS) approach has been coupled with microphysics and radiative scheme in WRF/Chem model. The new chemistry option called "RACM/MADE/VBS" was evaluated on a cloud resolving scale against ground-based and aircraft measurements collected during the IMPACT-EUCAARI campaign, and complemented with satellite data from MODIS. The day-to-day variability and the diurnal cycle of ozone (O3) and nitrogen oxides (NOx) at the surface is captured by the model. Surface aerosol mass of sulphate (SO4), nitrate (NO3), ammonium (NH4), and organic matter (OM) is simulated with a correlation larger than 0.55. WRF/Chem captures the vertical profile of the aerosol mass in both the planetary boundary layer (PBL) and free troposphere (FT) as a function of the synoptic condition, but the model does not capture the full range of the measured concentrations. Predicted OM concentration is at the lower end of the observed mass. The bias may be attributable to the missing aqueous chemistry processes of organic compounds, the uncertainties in meteorological fields, the assumption on the deposition velocity of condensable organic vapours, and the uncertainties in the anthropogenic emissions of primary organic carbon. Aerosol particle number concentration (condensation nuclei, CN) is overestimated by a factor 1.4 and 1.7 within PBL and FT, respectively. Model bias is most likely attributable to the uncertainties of primary particle emissions (mostly in the PBL) and to the nucleation rate. The overestimation of simulated cloud condensation nuclei (CCN) is more contained with respect to that of CN. The CCN efficiency, which is a measure of the ability of aerosol particles to nucleate cloud droplets, is underestimated by a factor of 1.5 and 3.8 in the PBL and FT, respectively. The comparison with MODIS data shows that the model overestimates the aerosol optical thickness (AOT). The domain averages (for one day) are 0.38 ± 0.12 and 0.42 ± 0.10 for MODIS and WRF/Chem data, respectively. Cloud water path (CWP) is overestimated on average by a factor of 1.7, whereas modelled cloud optical thickness (COT) agrees with observations within 10%. In a sensitivity test where the SOA was not included, simulated CWP is reduced by 40%, and its distribution function shifts toward lower values with respect to the reference run with SOA. The sensitivity test exhibits also 10% more optically thin clouds (COT < 40) and an average COT roughly halved. Moreover, the run with SOA shows convective clouds with an enhanced content of liquid and frozen hydrometers, and stronger updrafts and downdrafts. Considering that the previous version of WRF/Chem coupled with a modal aerosol module predicted very low SOA content (SORGAM mechanism) the new proposed option may lead to a better characterization of aerosol–cloud feedbacks

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“…During its long-range transport the SAL affects the Earth's radiation budget in two different ways. First, mineral dust aerosols may act as ice-nucleating particles (INPs) or cloud condensation nuclei (CCN -only when being internally mixed with soluble material) in water and ice clouds, hence influencing cloud microphysics -this effect is referred to as "indirect" mineral dust aerosol effect (Twomey, 1974(Twomey, , 1977Karydis et al, 2011;Bègue et al, 2015;DeMott et al, 2015;Boose et al, 2016). Thus, cloud formation, lifetime and occurrence as well as precipitation and ice formation may be manipulated by Saharan dust deposition into the cloud layer (Mahowald and Kiehl, 2003;Seifert et al, 2010).…”

Section: Introductionmentioning

confidence: 99%

Cloud macro-physical properties in Saharan-dust-laden and dust-free North Atlantic trade wind regimes: a lidar case study

2019

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Abstract. The Next-generation Aircraft Remote-Sensing for Validation Studies (NARVAL) aimed at providing a better understanding of shallow marine trade wind clouds and their interplay with long-range-transported elevated Saharan dust layers over the subtropical North Atlantic Ocean. Two airborne campaigns were conducted – the first one in December 2013 (winter) and the second one in August 2016, the latter one during the peak season of transatlantic Saharan dust transport (summer). In this study airborne lidar measurements in the vicinity of Barbados performed during both campaigns are used to investigate possible differences between shallow marine cloud macro-physical properties in dust-free regions and regions comprising elevated Saharan dust layers as well as between different seasons. The cloud top height distribution derived in dust-laden regions differs from the one derived in dust-free regions and indicates that there are less and shallower clouds in the dust-laden than in dust-free trades. Additionally, a clear shift of the distribution to higher altitudes is observed in the dust-free winter season, compared to the summer season. While during the summer season most cloud tops are observed in heights ranging from 0.5 to 1.0 km, most cloud tops in winter season are detected between 2.0 and 2.5 km. Moreover, it is found that regions comprising elevated Saharan dust layers show a larger fraction of small clouds and larger cloud-free regions, compared to dust-free regions. The cloud fraction in the dust-laden summer trades is only 14 % compared to a fraction of 31 % and 37 % in dust-free trades and the winter season. Dropsonde measurements show that long-range-transported Saharan dust layers come along with two additional inversions which counteract convective development, stabilize the stratification and may lead to a decrease in convection in those areas. Moreover, a decreasing trend of cloud fractions and cloud top heights with increasing dust layer vertical extent as well as aerosol optical depth is found.

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Aerosol processing and CCN formation of an intense Saharan dust plume during the EUCAARI 2008 campaign

Cited by 39 publications

References 128 publications

Retrieval of ice-nucleating particle concentrations from lidar observations and comparison with UAV in situ measurements

Retrieval of ice-nucleating particle concentrations from lidar observations and comparison with UAV in situ measurements

A new chemistry option in WRF-Chem v. 3.4 for the simulation of direct and indirect aerosol effects using VBS: evaluation against IMPACT-EUCAARI data

Cloud macro-physical properties in Saharan-dust-laden and dust-free North Atlantic trade wind regimes: a lidar case study

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