Smoke Invigoration Versus Inhibition of Clouds over the Amazon

Koren, Ilan; Martins, J. V.; Remer, L. A.; Afargan, Hila

doi:10.1126/science.1159185

Cited by 417 publications

(483 citation statements)

References 23 publications

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“…Absorbing aerosols can significantly change the atmospheric heating rate, which in turn modulates the lifetime of adjacent clouds [Hansen et al, 1997;Ackerman et al, 2000;Koren et al, 2008] and atmospheric stability [Penner et al, 2003;Mishra et al, 2014]. Height information can also be indicative of possible long-range transport of aerosols, due to the increased residence time and high wind speed in the free troposphere as compared to the planetary boundary layer [Williams et al, 2002].…”

Section: Introductionmentioning

confidence: 99%

Retrieving the height of smoke and dust aerosols by synergistic use of VIIRS, OMPS, and CALIOP observations

et al. 2015

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This study extends the application of the previously developed Aerosol Single-scattering albedo and layer Height Estimation (ASHE) algorithm, which was originally applied to smoke aerosols only, to both smoke and dust aerosols by including nonspherical dust properties in the retrieval process. The main purpose of the algorithm is to derive aerosol height information over wide areas using aerosol products from multiple satellite sensors simultaneously: aerosol optical depth (AOD) and Ångström exponent from the Visible Infrared Imaging Radiometer Suite (VIIRS), UV aerosol index from the Ozone Mapping and Profiler Suite (OMPS), and total backscatter coefficient profile from the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP). The case studies suggest that the ASHE algorithm performs well for both smoke and dust aerosols, showing root-mean-square error of the retrieved aerosol height as compared to CALIOP observations from 0.58 to 1.31 km and mean bias from À0.70 to 1.13 km. In addition, the algorithm shows the ability to retrieve single-scattering albedo to within 0.03 of Aerosol Robotic Network inversion data for moderate to thick aerosol loadings (AOD of~1.0). For typical single-layered aerosol cases, the estimated uncertainty in the retrieved height ranges from 1.20 to 1.80 km over land and from 1.15 to 1.58 km over ocean when favorable conditions are met. Larger errors are observed for multilayered aerosol events, due to the limited sensitivities of the passive sensors to such cases.

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Section: Introductionmentioning

confidence: 99%

Retrieving the height of smoke and dust aerosols by synergistic use of VIIRS, OMPS, and CALIOP observations

et al. 2015

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“…However, it is still not clear how deep or lower tropospheric VWS affects updraft buoyancy. In addition, aerosols can delay the formation of precipitation size hydrometeors, invigorating strong convection, while suppressing shallower and weaker convection (Rosenfeld et al, 2008;Koren et al, 2008;Lin et al, 2006;Andreae et al, 2004). Low-to-moderate aerosols enhance convective strength and such an influence depends on humidity (Chakraborty et al, 2016).…”

Section: Introductionmentioning

confidence: 99%

On the role of aerosols, humidity, and vertical wind shear in the transition of shallow-to-deep convection at the Green Ocean Amazon 2014/5 site

Chakraborty

Schiro

et al. 2018

Atmos. Chem. Phys.

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Abstract. The preconditioning of the atmosphere for a shallow-to-deep convective transition during the dry-to-wet season transition period (August-November) is investigated using Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) GoAmazon2014/5 campaign data from March 2014 to November 2015 in Manacapuru, Brazil. In comparison to conditions observed prior to shallow convection, anomalously high humidity in the free troposphere and boundary layer is observed prior to a shallow-to-deep convection transition. An entraining plume model, which captures this leading dependence on lower tropospheric moisture, is employed to study indirect thermodynamic effects associated with vertical wind shear (VWS) and cloud condensation nuclei (CCN) concentration on preconvective conditions. The shallow-to-deep convective transition primarily depends on humidity, especially that from the free troposphere, which tends to increase plume buoyancy. Conditions preceding deep convection are associated with high relative humidity, and low-to-moderate CCN concentration (less than the 67th percentile, 1274 cm −3 ). VWS, however, shows little relation to moisture and plume buoyancy. Buoyancy estimates suggest that the latent heat release due to freezing is important to deep convective growth under all conditions analyzed, consistent with potential pathways for aerosol effects, even in the presence of a strong entrainment. Shallow-only convective growth, however, shows an association with a strong (weak) low (deep) level VWS and with higher CCN concentration.

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“…In addition, clouds affect the solar and longwave radiation budgets in the field. Over land the radiation effects change the surface temperature and therefore can significantly affect heat and moisture fluxes and as a result the cloud properties (Koren et al, 2004(Koren et al, , 2008a.…”

Section: Introductionmentioning

confidence: 99%

Time-dependent, non-monotonic response of warm convective cloud fields to changes in aerosol loading

et al. 2017

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Abstract. Large eddy simulations (LESs) with bin microphysics are used here to study cloud fields' sensitivity to changes in aerosol loading and the time evolution of this response. Similarly to the known response of a single cloud, we show that the mean field properties change in a nonmonotonic trend, with an optimum aerosol concentration for which the field reaches its maximal water mass or rain yield. This trend is a result of competition between processes that encourage cloud development versus those that suppress it. However, another layer of complexity is added when considering clouds' impact on the field's thermodynamic properties and how this is dependent on aerosol loading. Under polluted conditions, rain is suppressed and the non-precipitating clouds act to increase atmospheric instability. This results in warming of the lower part of the cloudy layer (in which there is net condensation) and cooling of the upper part (net evaporation). Evaporation at the upper part of the cloudy layer in the polluted simulations raises humidity at these levels and thus amplifies the development of the next generation of clouds (preconditioning effect). On the other hand, under clean conditions, the precipitating clouds drive net warming of the cloudy layer and net cooling of the sub-cloud layer due to rain evaporation. These two effects act to stabilize the atmospheric boundary layer with time (consumption of the instability). The evolution of the field's thermodynamic properties affects the cloud properties in return, as shown by the migration of the optimal aerosol concentration toward higher values.

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Smoke Invigoration Versus Inhibition of Clouds over the Amazon

Cited by 417 publications

References 23 publications

Retrieving the height of smoke and dust aerosols by synergistic use of VIIRS, OMPS, and CALIOP observations

Retrieving the height of smoke and dust aerosols by synergistic use of VIIRS, OMPS, and CALIOP observations

On the role of aerosols, humidity, and vertical wind shear in the transition of shallow-to-deep convection at the Green Ocean Amazon 2014/5 site

Time-dependent, non-monotonic response of warm convective cloud fields to changes in aerosol loading

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