Influence of aerosol particles from biomass burning on cloud microphysical properties and radiative forcing

Cattani, Elsa; Costa, María João; Torricella, F.; Levizzani, Vincenzo; Silva, Ana Maria

doi:10.1016/j.atmosres.2005.10.010

Cited by 30 publications

(16 citation statements)

References 46 publications

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“…Haywood et al, 2004;Cattani et al, 2006;Bennartz and Harshvardhan, 2007;Wilcox et al, 2009;Coddington et al, 2010). In support of the presented analysis, potential biases in r e have been shown to be less than 1 µm for retrievals where the visible reflectance is matched with the 3.7 µm or 2.13 µm reflectance.…”

Section: Above-cloud Aerosol Layerssupporting

confidence: 48%

Investigating potential biases in observed and modeled metrics of aerosol-cloud-precipitation interactions

2011

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Abstract. This study utilizes large eddy simulation, aircraft measurements, and satellite observations to identify factors that bias the absolute magnitude of metrics of aerosol-cloudprecipitation interactions for warm clouds. The metrics considered are precipitation susceptibility S o , which examines rain rate sensitivity to changes in drop number, and a cloudprecipitation metric, χ, which relates changes in rain rate to those in drop size. While wide ranges in rain rate exist at fixed cloud drop concentration for different cloud liquid water amounts, χ and S o are shown to be relatively insensitive to the growth phase of the cloud for large datasets that include data representing the full spectrum of cloud lifetime. Spatial resolution of measurements is shown to influence the liquid water path-dependent behavior of S o and χ. Other factors of importance are the choice of the minimum rain rate threshold, and how to quantify rain rate, drop size, and the cloud condensation nucleus proxy. Finally, low biases in retrieved aerosol amounts owing to wet scavenging and high biases associated with above-cloud aerosol layers should be accounted for. The paper explores the impact of these effects for model, satellite, and aircraft data.

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Section: Above-cloud Aerosol Layerssupporting

confidence: 48%

Investigating potential biases in observed and modeled metrics of aerosol-cloud-precipitation interactions

2011

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“…BC has received attention by the scientific community due to its potential for ice nucleation, which can affect the microphysical properties of clouds (Cattani et al, 2006;Cozic et al, 2008). The supersaturation required for ice formation decreases with the presence of BC (DeMott et al, 1999).…”

Section: Discussionmentioning

confidence: 99%

Influence of biomass aerosol on precipitation over the Central Amazon: an observational study

2015

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Abstract. Understanding the influence of biomass burning aerosol on clouds and precipitation in the Amazon is key to reducing uncertainties in simulations of climate change scenarios with regard to deforestation fires. Here, we associate rainfall characteristics obtained from an S-band radar in the Amazon with in situ measurements of biomass burning aerosol for the entire year of 2009. The most important results were obtained during the dry season (July-December). The results indicate that the influence of aerosol on precipitating systems is modulated by the atmospheric degree of instability. For less unstable atmospheres, the higher the aerosol concentration is, the lower the precipitation is over the region. In contrast, for more unstable cases, higher concentrations of black carbon are associated with greater precipitation, increased ice content, and larger rain cells; this finding suggests an association with long-lived systems. The results presented are statistically significant. However, due to limitations imposed by the available data set, important features, such as the contribution of each mechanism to the rainfall suppression, need further investigation. Regional climate model simulations with aircraft and radar measurements would help clarify these questions.

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“…However, use of the 1.63‐ μ m reflectance for the retrieval of r e can result in underestimates of r e of several μ m. Biases in the retrieval of τ were greatest for bright clouds with high values of τ . Haywood et al [2004] and Cattani et al [2006] both presented case studies from several Moderate Resolution Imaging Spectrometer (MODIS) granules indicating a bias in the 1.63‐ μ m r e retrieval relative to the 2.13‐ μ m retrieval.…”

Section: Introductionmentioning

confidence: 99%

Estimate of the impact of absorbing aerosol over cloud on the MODIS retrievals of cloud optical thickness and effective radius using two independent retrievals of liquid water path

Wilcox¹,

Harshvardhan²,

Platnick³

2009

J. Geophys. Res.

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[1] Two independent satellite retrievals of cloud liquid water path (LWP) from the NASA Aqua satellite are used to diagnose the impact of absorbing biomass burning aerosol overlaying boundary-layer marine water clouds on the Moderate Resolution Imaging Spectrometer (MODIS) retrievals of cloud optical thickness (t) and cloud droplet effective radius (r e ). In the MODIS retrieval over oceans, cloud reflectance in the 0.86-mm and 2.13-mm bands is used to simultaneously retrieve t and r e . A low bias in the MODIS t retrieval may result from reductions in the 0.86-mm reflectance, which is only very weakly absorbed by clouds, owing to absorption by aerosols in cases where biomass burning aerosols occur above water clouds. MODIS LWP, derived from the product of the retrieved t and r e , is compared with LWP ocean retrievals from the Advanced Microwave Scanning Radiometer-EOS (AMSR-E), determined from cloud microwave emission that is transparent to aerosols. For the coastal Atlantic southern African region investigated in this study, a systematic difference between AMSR-E and MODIS LWP retrievals is found for stratocumulus clouds over three biomass burning months in 2005 and 2006 that is consistent with above-cloud absorbing aerosols. Biomass burning aerosol is detected using the ultraviolet aerosol index from the Ozone Monitoring Instrument (OMI) on the Aura satellite. The LWP difference (AMSR-E minus MODIS) increases both with increasing t and increasing OMI aerosol index. During the biomass burning season the mean LWP difference is 14 g m À2 , which is within the 15-20 g m À2range of estimated uncertainties in instantaneous LWP retrievals. For samples with only low amounts of overlaying smoke (OMI AI 1) the difference is 9.4, suggesting that the impact of smoke aerosols on the mean MODIS LWP is 5.6 g m À2 . Only for scenes with OMI aerosol index greater than 2 does the average LWP difference and the estimated bias in MODIS cloud optical thickness attributable to the impact of overlaying biomass burning aerosol exceed the instantaneous uncertainty in the retrievals.Citation: Wilcox, E. M., Harshvardhan, and S. Platnick (2009), Estimate of the impact of absorbing aerosol over cloud on the MODIS retrievals of cloud optical thickness and effective radius using two independent retrievals of liquid water path, J. Geophys.

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Influence of aerosol particles from biomass burning on cloud microphysical properties and radiative forcing

Cited by 30 publications

References 46 publications

Investigating potential biases in observed and modeled metrics of aerosol-cloud-precipitation interactions

Investigating potential biases in observed and modeled metrics of aerosol-cloud-precipitation interactions

Influence of biomass aerosol on precipitation over the Central Amazon: an observational study

Estimate of the impact of absorbing aerosol over cloud on the MODIS retrievals of cloud optical thickness and effective radius using two independent retrievals of liquid water path

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