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Title: Cloud Condensation Nuclei Activity of Aerosols during GoAmazon 2014/15 Field Campaign Report

Technical Report ·
DOI:https://doi.org/10.2172/1248889· OSTI ID:1248889
 [1];  [2];  [1];  [1]
  1. Brookhaven National Lab. (BNL), Upton, NY (United States)
  2. Harvard Univ., Cambridge, MA (United States)

Aerosol indirect effects, which represent the impact of aerosols on climate through influencing the properties of clouds, remain one of the main uncertainties in climate predictions (Stocker et al. 2013). Reducing this large uncertainty requires both improved understanding and representation of aerosol properties and processes in climate models, including the cloud activation properties of aerosols. The Atmospheric System Research (ASR) science program plan of January 2010 states that: “A key requirement for simulating aerosol-cloud interactions is the ability to calculate cloud condensation nuclei and ice nuclei (CCN and IN, respectively) concentrations as a function of supersaturation from the chemical and microphysical properties of the aerosol.” The Observations and Modeling of the Green Ocean Amazon (GoAmazon 2014/15) study seeks to understand how aerosol and cloud life cycles are influenced by pollutant outflow from a tropical megacity (Manaus)—in particular, the differences in cloud-aerosol-precipitation interactions between polluted and pristine conditions. One key question of GoAmazon2014/5 is: “What is the influence of the Manaus pollution plume on the cloud condensation nuclei (CCN) activities of the aerosol particles and the secondary organic material in the particles?” To address this question, we measured size-resolved CCN spectra, a critical measurement for GoAmazon2014/5.

Research Organization:
DOE ARM Climate Research Facility, Washington, DC (United States)
Sponsoring Organization:
USDOE Office of Science (SC), Biological and Environmental Research (BER)
DOE Contract Number:
AC05-7601830
OSTI ID:
1248889
Report Number(s):
DOE/SC-ARM-16-005
Country of Publication:
United States
Language:
English

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