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D. A. Knopf
,
K. R. Barry
,
T. A. Brubaker
,
L. G. Jahl
,
K. A. Jankowski
,
J. Li
,
Y. Lu
,
L. W. Monroe
,
K. A. Moore
,
F. A. Rivera-Adorno
,
K. A. Sauceda
,
Y. Shi
,
J. M. Tomlin
,
H. S. K. Vepuri
,
P. Wang
,
N. N. Lata
,
E. J. T. Levin
,
J. M. Creamean
,
T. C. J. Hill
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S. China
,
P. A. Alpert
,
R. C. Moffet
,
N. Hiranuma
,
R. C. Sullivan
,
A. M. Fridlind
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M. West
,
N. Riemer
,
A. Laskin
,
P. J. DeMott
, and
X. Liu

Abstract

Prediction of ice formation in clouds presents one of the grand challenges in the atmospheric sciences. Immersion freezing initiated by ice-nucleating particles (INPs) is the dominant pathway of primary ice crystal formation in mixed-phase clouds, where supercooled water droplets and ice crystals coexist, with important implications for the hydrological cycle and climate. However, derivation of INP number concentrations from an ambient aerosol population in cloud-resolving and climate models remains highly uncertain. We conducted an aerosol–ice formation closure pilot study using a field-observational approach to evaluate the predictive capability of immersion freezing INPs. The closure study relies on collocated measurements of the ambient size-resolved and single-particle composition and INP number concentrations. The acquired particle data serve as input in several immersion freezing parameterizations, which are employed in cloud-resolving and climate models, for prediction of INP number concentrations. We discuss in detail one closure case study in which a front passed through the measurement site, resulting in a change of ambient particle and INP populations. We achieved closure in some circumstances within uncertainties, but we emphasize the need for freezing parameterization of potentially missing INP types and evaluation of the choice of parameterization to be employed. Overall, this closure pilot study aims to assess the level of parameter details and measurement strategies needed to achieve aerosol–ice formation closure. The closure approach is designed to accurately guide immersion freezing schemes in models, and ultimately identify the leading causes for climate model bias in INP predictions.

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S. T. Martin
,
P. Artaxo
,
L. Machado
,
A. O. Manzi
,
R. A. F. Souza
,
C. Schumacher
,
J. Wang
,
T. Biscaro
,
J. Brito
,
A. Calheiros
,
K. Jardine
,
A. Medeiros
,
B. Portela
,
S. S. de Sá
,
K. Adachi
,
A. C. Aiken
,
R. Albrecht
,
L. Alexander
,
M. O. Andreae
,
H. M. J. Barbosa
,
P. Buseck
,
D. Chand
,
J. M. Comstock
,
D. A. Day
,
M. Dubey
,
J. Fan
,
J. Fast
,
G. Fisch
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E. Fortner
,
S. Giangrande
,
M. Gilles
,
A. H. Goldstein
,
A. Guenther
,
J. Hubbe
,
M. Jensen
,
J. L. Jimenez
,
F. N. Keutsch
,
S. Kim
,
C. Kuang
,
A. Laskin
,
K. McKinney
,
F. Mei
,
M. Miller
,
R. Nascimento
,
T. Pauliquevis
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M. Pekour
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J. Peres
,
T. Petäjä
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C. Pöhlker
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U. Pöschl
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L. Rizzo
,
B. Schmid
,
J. E. Shilling
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M. A. Silva Dias
,
J. N. Smith
,
J. M. Tomlinson
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J. Tóta
, and
M. Wendisch

Abstract

The Observations and Modeling of the Green Ocean Amazon 2014–2015 (GoAmazon2014/5) experiment took place around the urban region of Manaus in central Amazonia across 2 years. The urban pollution plume was used to study the susceptibility of gases, aerosols, clouds, and rainfall to human activities in a tropical environment. Many aspects of air quality, weather, terrestrial ecosystems, and climate work differently in the tropics than in the more thoroughly studied temperate regions of Earth. GoAmazon2014/5, a cooperative project of Brazil, Germany, and the United States, employed an unparalleled suite of measurements at nine ground sites and on board two aircraft to investigate the flow of background air into Manaus, the emissions into the air over the city, and the advection of the pollution downwind of the city. Herein, to visualize this train of processes and its effects, observations aboard a low-flying aircraft are presented. Comparative measurements within and adjacent to the plume followed the emissions of biogenic volatile organic carbon compounds (BVOCs) from the tropical forest, their transformations by the atmospheric oxidant cycle, alterations of this cycle by the influence of the pollutants, transformations of the chemical products into aerosol particles, the relationship of these particles to cloud condensation nuclei (CCN) activity, and the differences in cloud properties and rainfall for background compared to polluted conditions. The observations of the GoAmazon2014/5 experiment illustrate how the hydrologic cycle, radiation balance, and carbon recycling may be affected by present-day as well as future economic development and pollution over the Amazonian tropical forest.

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