Synergistic use of multiple types of measurements improves estimate of the indirect effects of aerosols on clouds.
The impact of atmospheric aerosols on climate through their ability to modify subtropical marine low clouds remains a central uncertainty in climate models, hampering accurate quantification of anthropogenic radiative forcing. Thus, uncertainty reduction requires reliable measurements of cloud and aerosol properties that can guide future model improvements. However, long-term observations over marine environments have been elusive until a recent ARM field campaign over the Northeast Pacific: The Marine ARM Investigation of Clouds (MAGIC) campaign. MAGIC deployed the second ARM mobile facility (AMF2) on board a cargo ship, the Horizon Spirit, that sailed between the ports of Los Angeles, California and Honolulu, Hawaii for nearly 20 round trips during two observation periods: September (2012)-January (2013) and May-September of 2013, for a total of nearly 200 days at sea. The AMF2, which contained three radars, lidars, microwave radiometers, and a suite of other instruments that measured properties of clouds and precipitation, aerosols, and radiation, and meteorological and oceanographic conditions, provided an unprecedented data set that can be used to validate and constrain climate models and satellite retrievals.
In this study, the unique MAGIC data set was used to quantify the co-variability between aerosol concentration and estimates of cloud droplet number concentration, two parameters that are needed to understand the impacts of aerosols on marine low clouds. By synergistically exploiting the strengths of several remote sensors, uncertainties in the quantification of the aerosol indirect effect on clouds can be greatly reduced. The study also points to the importance of sampling the aerosol vertical structure, especially when the near-surface measurements are not representative of those right below the cloud base.
This study used remotely sensed MAGIC observations of cloud properties to compute cloud droplet number concentration (Nd) and quantify its co-variability with near-surface measurements of cloud condensation nuclei (CCN) and aerosol properties. The researchers found that Nd, CCN, and aerosol concentrations (for particles larger than 0.1 mm in diameter) are highly correlated, with more polluted samples being associated with higher number of droplets, under relatively well-coupled boundary-layer conditions. In addition, the slope of the aerosol-Nd relationship is high and similar to aircraft-based studies, suggesting strong interactions between aerosols and cloud microphysics. In contrast, other ground-based deployments show a weaker and more scattered aerosol-cloud relationship. To understand this discrepancy, they used the aerosol backscatter cross-section from a high-spectral-resolution lidar (HSRL) as an aerosol proxy, and investigated its vertical structure. They found that in shallow and well-coupled boundary layers, aerosols tend to be vertically homogenous with height, whereas deeper boundary layers feature a more complex aerosol vertical structure. In addition, for shallow boundary layers, aerosol measurements at different vertical levels yield high temporal correlations with those near the surface. The weaker temporal correlation between near-surface and 600-1200 m aerosols for deep boundary layers indicates that surface measurements do not fully represent the aerosol variability near the cloud base, demonstrating that knowledge of the aerosol vertical structure is essential for accurate quantification of the aerosol indirect effect.
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ASR Program Manager
ARM Program Manager
NASA Langley Research Center, Hampton, Virginia, USA
This work was supported by the U.S. Department of Energy (DOE), Office of Science, Office of Biological and Environmental Research: Atmospheric System Research (ASR) grants DE- SC001167 (D. Painemal, P. Minnis, and C. Yost) and DE-SC0011666 (J.C. Chiu), Atmospheric Radiation Measurement Infrastructure, under contract DE-AC02-06CH11357 (M. Cadeddu), and contract DE-SC00112704 awarded to Brookhaven National Laboratory (E.R. Lewis). C. Yost was also supported by the NASA CERES program. The MAGIC data set was downloaded from the ARM archive available at http://www.archive.arm.gov/. MODIS and GOES-15 retrievals are available at http://www-pm.larc.nasa.gov or upon request.
Painemal, D., J.-Y. C. Chiu, P. Minnis, C. Yost, X. Zhou, M. Cadeddu, E. Eloranta, E. R. Lewis, R. Ferrare, and P. Kollias, "Aerosol and cloud microphysics co-variability in the northeast Pacific boundary layer estimated with ship-based and satellite remote sensing observations." Journal of Geophysical Research: Atmospheres, 122 (4): 2403-2418 (2017). [DOI: 10.1002/2016JD025771]
ASR Highlight: Aerosol and Cloud Co-variability in the Northeast Pacific Estimated with MAGIC Observations
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