U.S. Department of Energy Office of Biological and Environmental Research

BER Research Highlights

Aerosol Particles from Ocean Biological Emissions Increase Number of Cloud Droplets and Cloud Reflectivity
Published: July 17, 2015
Posted: December 11, 2015

Globally, about one-third of the sunlight that reaches Earth is reflected back to outer space before ever reaching the surface. Most of this sunlight is reflected by cloud droplets, which act like tiny mirrors, deflecting the sun’s rays and cooling the planet. The amount of sunlight reflected by clouds depends both on the extent of clouds and their properties, including the number and size of water droplets within the clouds. In a recent study, researchers at Pacific Northwest National Laboratory (PNNL), University of Washington, Los Alamos National Laboratory, and University of Leeds found that small particles originating from ocean phytoplankton are responsible for most of the seasonal and geographic differences in the number of droplets in clouds over vast stretches of the ocean in the Southern Hemisphere. This, in turn, affects the fraction of sunlight reflected by the clouds, also known as cloud albedo. The team assembled a collection of datasets related to cloud properties, marine aerosols, and meteorological variables (such as wind speed), using a combination of information from satellite observations and atmospheric and ocean models. By comparing these datasets and others, the researchers showed that about half of the seasonal and geographic variation in cloud drop number over the oceans between 35 degrees and 55 degrees south latitude can be predicted using models describing aerosol particles that are primarily of marine biogenic origin. This finding suggests that marine critters are responsible for much of the variation in cloud albedo in this region. The effects of ocean biology on clouds are largest in the oceans of the Southern Hemisphere, a geographic region where current climate models perform poorly relative to other parts of the world. This finding will improve the representation of cloud albedo in global atmospheric models, which may help to improve simulations of past and present climate as well as future climate projections.

Reference: McCoy, D. T., S. M. Burrows, R. Wood, D. P. Grosvenor, S. M. Elliott, P.-L. Ma, P. J. Rasch, and D. L. Hartmann. 2015. “Natural Aerosols Explain Seasonal and Spatial Patterns of Southern Ocean Cloud Albedo,” Science Advances 1(6), e1500157. DOI: 10.1126/sciadv.1500157. (Reference link)

Media: PNNL news release and Scientific American podcast.

Contact: Dorothy Koch, SC-23.1, (301) 903-0105
Topic Areas:

  • Research Area: Earth and Environmental Systems Modeling
  • Research Area: Atmospheric System Research

Division: SC-23.1 Climate and Environmental Sciences Division, BER


BER supports basic research and scientific user facilities to advance DOE missions in energy and environment. More about BER

Recent Highlights

May 10, 2019
Quantifying Decision Uncertainty in Water Management via a Coupled Agent-Based Model
Considering risk perception can improve the representation of human decision-making processes in age [more...]

May 09, 2019
Projecting Global Urban Area Growth Through 2100 Based on Historical Time Series Data and Future Scenarios
Study provides country-specific urban area growth models and the first dataset on country-level urba [more...]

May 05, 2019
Calibrating Building Energy Demand Models to Refine Long-Term Energy Planning
A new, flexible calibration approach improved model accuracy in capturing year-to-year changes in bu [more...]

May 03, 2019
Calibration and Uncertainty Analysis of Demeter for Better Downscaling of Global Land Use and Land Cover Projections
Researchers improved the Demeter model’s performance by calibrating key parameters and establi [more...]

Apr 22, 2019
Representation of U.S. Warm Temperature Extremes in Global Climate Model Ensembles
Representation of warm temperature events varies considerably among global climate models, which has [more...]

List all highlights (possible long download time)