scholarly journals Impact of mixing state and hygroscopicity on CCN activity of biomass burning aerosol in Amazonia

Author(s):  
Madeleine Sánchez Gácita ◽  
Karla M. Longo ◽  
Julliana L. M. Freire ◽  
Saulo R. Freitas ◽  
Scot T. Martin

Abstract. Smoke aerosols prevail throughout Amazonia because of widespread biomass burning during the dry season. External mixing, low variability in the particle size distribution and low particle hygroscopicity are typical. There can be profound effects on cloud properties. This study uses an adiabatic cloud model to simulate the activation of smoke particles as cloud condensation nuclei (CCN) and to assess the relative importance of variability in hygroscopicity, mixing state, and activation kinetics for the activated fraction and maximum supersaturation. The analysis shows that use of medium values of hygroscopicity representative of smoke aerosols for other biomass burning regions on Earth can lead to significant errors, compared to the use of low hygroscopicity reported for Amazonia. Kinetic limitations, which can be significant for medium and high hygroscopicity, did not play a strong role for CCN activation of particles representative of Amazonia smoke aerosols, even when taking into account the large aerosol mass and number concentrations typical of the region. Internal compared to external mixing of particle components of variable hygroscopicity resulted in a significant overestimation of the activated fraction. These findings on uncertainties and sensitivities provide guidance on appropriate simplifications that can be used for modeling of smoke aerosols within general circulation models.

2017 ◽  
Vol 17 (3) ◽  
pp. 2373-2392 ◽  
Author(s):  
Madeleine Sánchez Gácita ◽  
Karla M. Longo ◽  
Julliana L. M. Freire ◽  
Saulo R. Freitas ◽  
Scot T. Martin

Abstract. Smoke aerosols prevail throughout Amazonia because of widespread biomass burning during the dry season, and external mixing, low variability in the particle size distribution and low particle hygroscopicity are typical. There can be profound effects on cloud properties. This study uses an adiabatic cloud model to simulate the activation of smoke particles as cloud condensation nuclei (CCN) for three hypothetical case studies, chosen as to resemble biomass burning aerosol observations in Amazonia. The relative importance of variability in hygroscopicity, mixing state, and activation kinetics for the activated fraction and maximum supersaturation is assessed. For a population with κp = 0.04, an overestimation of the cloud droplet number concentration Nd for the three selected case studies between 22.4 ± 1.4 and 54.3 ± 3.7 % was obtained when assuming a hygroscopicity parameter κp = 0.20. Assuming internal mixing of the aerosol population led to overestimations of up to 20 % of Nd when a group of particles with medium hygroscopicity was present in the externally mixed population cases. However, the overestimations were below 10 % for external mixtures between very low and low-hygroscopicity particles, as seems to be the case for Amazon smoke particles. Kinetic limitations were significant for medium- and high-hygroscopicity particles, and much lower for very low and low-hygroscopicity particles. When particles were assumed to be at equilibrium and to respond instantly to changes in the air parcel supersaturation, the overestimation of the droplet concentration was up to  ∼  100 % in internally mixed populations, and up to  ∼  250 % in externally mixed ones, being larger for the higher values of hygroscopicity. In addition, a perceptible delay between the times when maximum supersaturation and maximum aerosol activated fraction are reached was noticed and, for aerosol populations with effective hygroscopicity κpeff higher than a certain threshold value, the delay in particle activation was such that no particles were activated at the time of maximum supersaturation. Considering internally mixed populations, for an updraft velocity W = 0.5 m s−1 this threshold of no activation varied between κpeff = 0.35 and κpeff = 0.5 for the different case studies. However, for low hygroscopicity, kinetic limitations played a weaker role for CCN activation of particles, even when taking into account the large aerosol mass and number concentrations. For the very low range of hygroscopicities, the overestimation of the droplet concentration due to the equilibrium assumption was lowest and the delay between the times when maximum supersaturation and maximum activated fraction were reached was greatly reduced or no longer observed (depending on the case study). These findings on uncertainties and sensitivities provide guidance on appropriate simplifications that can be used for modeling of smoke aerosols within general circulation models. The use of medium values of hygroscopicity representative of smoke aerosols for other biomass burning regions on Earth can lead to significant errors compared to the use of low hygroscopicity for Amazonia (between 0.05 and 0.13, according to available observations). Also in this region, consideration of the biomass burning population as internally mixed will lead to small errors in the droplet concentration, while significantly increasing the computational burden. Regardless of the large smoke aerosol loads in the region during the dry season, kinetic limitations are expected to be low.


2008 ◽  
Vol 21 (19) ◽  
pp. 4955-4973 ◽  
Author(s):  
Michael P. Jensen ◽  
Andrew M. Vogelmann ◽  
William D. Collins ◽  
Guang J. Zhang ◽  
Edward P. Luke

Abstract To aid in understanding the role that marine boundary layer (MBL) clouds play in climate and assist in improving their representations in general circulation models (GCMs), their long-term microphysical and macroscale characteristics are quantified using observations from the Moderate Resolution Imaging Spectroradiometer (MODIS) instrument aboard the National Aeronautics and Space Administration’s (NASA’s) Terra satellite. Six years of MODIS pixel-level cloud products are used from oceanic study regions off the west coasts of California, Peru, the Canary Islands, Angola, and Australia where these cloud types are common. Characterizations are given for their organization (macroscale structure), the associated microphysical properties, and the seasonal dependencies of their variations for scales consistent with the size of a GCM grid box (300 km × 300 km). MBL mesoscale structure is quantified using effective cloud diameter CD, which is introduced here as a simplified measure of bulk cloud organization; it is straightforward to compute and provides descriptive information beyond that offered by cloud fraction. The interrelationships of these characteristics are explored while considering the influences of the MBL state, such as the occurrence of drizzle. Several commonalities emerge for the five study regions. MBL clouds contain the best natural examples of plane-parallel clouds, but overcast clouds occur in only about 25% of the scenes, which emphasizes the importance of representing broken MBL cloud fields in climate models (that are subgrid scale). During the peak months of cloud occurrence, mesoscale organization (larger CD) increases such that the fractions of scenes characterized as “overcast” and “clumped” increase at the expense of the “scattered” scenes. Cloud liquid water path and visible optical depth usually trend strongly with CD, with the largest values occurring for scenes that are drizzling. However, considerable interregional differences exist in these trends, suggesting that different regression functionalities exist for each region. For peak versus off-peak months, the fraction of drizzling scenes (as a function of CD) are similar for California and Angola, which suggests that a single probability distribution function might be used for their drizzle occurrence in climate models. The patterns are strikingly opposite for Peru and Australia; thus, the contrasts among regions may offer a test bed for model simulations of MBL drizzle occurrence.


2011 ◽  
Vol 11 (11) ◽  
pp. 5289-5303 ◽  
Author(s):  
G. Grell ◽  
S. R. Freitas ◽  
M. Stuefer ◽  
J. Fast

Abstract. A plume rise algorithm for wildfires was included in WRF-Chem, and applied to look at the impact of intense wildfires during the 2004 Alaska wildfire season on weather simulations using model resolutions of 10 km and 2 km. Biomass burning emissions were estimated using a biomass burning emissions model. In addition, a 1-D, time-dependent cloud model was used online in WRF-Chem to estimate injection heights as well as the vertical distribution of the emission rates. It was shown that with the inclusion of the intense wildfires of the 2004 fire season in the model simulations, the interaction of the aerosols with the atmospheric radiation led to significant modifications of vertical profiles of temperature and moisture in cloud-free areas. On the other hand, when clouds were present, the high concentrations of fine aerosol (PM2.5) and the resulting large numbers of Cloud Condensation Nuclei (CCN) had a strong impact on clouds and cloud microphysics, with decreased precipitation coverage and precipitation amounts during the first 12 h of the integration. During the afternoon, storms were of convective nature and appeared significantly stronger, probably as a result of both the interaction of aerosols with radiation (through an increase in CAPE) as well as the interaction with cloud microphysics.


2013 ◽  
Vol 6 (5) ◽  
pp. 8371-8411 ◽  
Author(s):  
S. Zeng ◽  
J. Riedi ◽  
F. Parol ◽  
C. Cornet ◽  
F. Thieuleux

Abstract. The A-Train observations provide an unprecedented opportunity for the production of high quality dataset describing cloud properties. We illustrate in this study the use of one year of coincident POLDER (Polarization and Directionality of the Earth Reflectance), MODIS (MODerate Resolution Imaging Spectroradiometer) and CALIOP (Cloud-Aerosol Lidar with Orthogonal Polarization) observations to establish a reference dataset for the description of cloud top thermodynamic phase at global scale. We present the results of an extensive comparison between POLDER and MODIS cloud top phase products and discuss those in view of cloud vertical structure and optical properties derived simultaneously from collocated CALIOP active measurements. These results allow to identify and quantify potential biases present in the 3 considered dataset. Among those, we discuss the impacts of observation geometry, thin cirrus in multilayered and single layered cloud systems, supercooled liquid droplets, aerosols, fractional cloud cover and snow/ice or bright surfaces on global statistics of cloud phase derived from POLDER and MODIS passive measurements. Based on these analysis we define criteria for the selection of high confidence cloud phase retrievals which in turn can serve for the establishment of a reference cloud phase product. This high confidence joint product derived from POLDER/PARASOL and MODIS/Aqua can be used in the future as a benchmark for the evaluation of other cloud climatologies, for the assessment of cloud phase representation in models and the development of better cloud phase parametrization in the general circulation models (GCMs).


2019 ◽  
Author(s):  
Mary Kacarab ◽  
K. Lee Thornhill ◽  
Amie Dobracki ◽  
Steven G. Howell ◽  
Joseph R. O'Brien ◽  
...  

Abstract. The southeastern Atlantic (SEA) and its associated cloud deck, off the west coast of central Africa, is an area where aerosol-cloud interactions can have a strong radiative impact. Seasonally, extensive biomass burning (BB) aerosol plumes from southern Africa reach this area. The NASA ObseRvations of Aerosols above Clouds and their intEractionS (ORACLES) study focused on quantitatively understanding these interactions and their importance. Here we present measurements of cloud condensation nuclei (CCN) concentration, aerosol size distribution, and vertical updraft velocity in and around the marine boundary layer (MBL) collected by the NASA P-3B aircraft during the August 2017 ORACLES deployment. BB aerosol levels vary considerably but systematically with time; high aerosol concentrations were observed in the MBL (800–1000 cm−3) early on, decreasing mid-campaign to concentrations between 500–800 cm−3. By late August and early September, relatively clean MBL conditions were sampled (


2013 ◽  
Vol 30 (12) ◽  
pp. 2896-2906 ◽  
Author(s):  
J. Mielikainen ◽  
B. Huang ◽  
H.-L. A. Huang ◽  
M. D. Goldberg ◽  
A. Mehta

Abstract The Weather Research and Forecasting model (WRF) double-moment 6-class microphysics scheme (WDM6) implements a double-moment bulk microphysical parameterization of clouds and precipitation and is applicable in mesoscale and general circulation models. WDM6 extends the WRF single-moment 6-class microphysics scheme (WSM6) by incorporating the number concentrations for cloud and rainwater along with a prognostic variable of cloud condensation nuclei (CCN) number concentration. Moreover, it predicts the mixing ratios of six water species (water vapor, cloud droplets, cloud ice, snow, rain, and graupel), similar to WSM6. This paper describes improving the computational performance of WDM6 by exploiting its inherent fine-grained parallelism using the NVIDIA graphics processing unit (GPU). Compared to the single-threaded CPU, a single GPU implementation of WDM6 obtains a speedup of 150× with the input/output (I/O) transfer and 206× without the I/O transfer. Using four GPUs, the speedup reaches 347× and 715×, respectively.


2009 ◽  
Vol 66 (1) ◽  
pp. 105-115 ◽  
Author(s):  
Alexandru Rap ◽  
Satyajit Ghosh ◽  
Michael H. Smith

Abstract This paper presents a novel method based on the application of interpolation techniques to the multicomponent aerosol–cloud parameterization for global climate modeling. Quantifying the aerosol indirect effect still remains a difficult task, and thus developing parameterizations for general circulation models (GCMs) of the microphysics of clouds and their interactions with aerosols is a major challenge for climate modelers. Three aerosol species are considered in this paper—namely sulfate, sea salt, and biomass smoke—and a detailed microphysical chemical parcel model is used to obtain a dataset of points relating the cloud droplet number concentration (CDNC) to the three aerosol input masses. The resulting variation of CDNC with the aerosol mass has some nonlinear features that require a complex but efficient parameterization to be easily incorporated into GCMs. In bicomponent systems, simple interpolation techniques may be sufficient to relate the CDNC to the aerosol mass, but with increasing components, simple methods fail. The parameterization technique proposed in this study employs either the modified Shepard interpolation method or the Hardy multiquadrics interpolation method, and the numerical results obtained show that both methods provide realistic results for a wide range of aerosol mass loadings. This is the first application of these two interpolation techniques to aerosol–cloud interaction studies.


2014 ◽  
Vol 14 (14) ◽  
pp. 7485-7497 ◽  
Author(s):  
B. Gantt ◽  
J. He ◽  
X. Zhang ◽  
Y. Zhang ◽  
A. Nenes

Abstract. One of the greatest sources of uncertainty in the science of anthropogenic climate change is from aerosol–cloud interactions. The activation of aerosols into cloud droplets is a direct microphysical linkage between aerosols and clouds; parameterizations of this process link aerosol with cloud condensation nuclei (CCN) and the resulting indirect effects. Small differences between parameterizations can have a large impact on the spatiotemporal distributions of activated aerosols and the resulting cloud properties. In this work, we incorporate a series of aerosol activation schemes into the Community Atmosphere Model version 5.1.1 within the Community Earth System Model version 1.0.5 (CESM/CAM5) which include factors such as insoluble aerosol adsorption and giant cloud condensation nuclei (CCN) activation kinetics to understand their individual impacts on global-scale cloud droplet number concentration (CDNC). Compared to the existing activation scheme in CESM/CAM5, this series of activation schemes increase the computation time by ~10% but leads to predicted CDNC in better agreement with satellite-derived/in situ values in many regions with high CDNC but in worse agreement for some regions with low CDNC. Large percentage changes in predicted CDNC occur over desert and oceanic regions, owing to the enhanced activation of dust from insoluble aerosol adsorption and reduced activation of sea spray aerosol after accounting for giant CCN activation kinetics. Comparison of CESM/CAM5 predictions against satellite-derived cloud optical thickness and liquid water path shows that the updated activation schemes generally improve the low biases. Globally, the incorporation of all updated schemes leads to an average increase in column CDNC of 150% and an increase (more negative) in shortwave cloud forcing of 12%. With the improvement of model-predicted CDNCs and better agreement with most satellite-derived cloud properties in many regions, the inclusion of these aerosol activation processes should result in better predictions of radiative forcing from aerosol–cloud interactions.


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