Two-year ARM deployment shows what is special about Amazonian clouds and provides a rich dataset to the community.
As the heat engine of our planet, the tropics drive climate and weather patterns around the globe. A new paper summarizes the two-year, multi-agency effort for routine collection of cloud observations and environmental conditions during the Observations and Modeling of the Green Ocean Amazon (GoAmazon2014/15) field campaign led by the U.S. Department of Energy’s Atmospheric Radiation Measurement (ARM) Climate Research Facility, a scientific user facility. This effort quantifies the propensity for convective clouds to initiate, deepen, and organize across the Amazon basin, the radiative impacts of those clouds, and increases in clouds and precipitation observed during the Amazon wet season (December through April).
The long-term Amazonian ground deployment and two short-term aircraft intensive observing periods provide a rich data set for studies of cloud and aerosol life cycles, including cloud-aerosol-precipitation interactions and the influences of a pollution plume from the Brazilian city of Manaus. The observations help characterize the cloud life cycle, their effects on Earth’s energy balance, and cloud-aerosol interactions for the under-sampled, yet climatically important, Amazon basin in support of improving Earth system modeling capabilities.
The Amazon forest is the largest tropical rainforest on Earth, featuring prolific and diverse cloud conditions. GoAmazon2014/15, which involved observations collected from ARM mobile and aerial facilities, was motivated by the need for scientists to gain a better understanding of how aerosol and cloud interactions influence climate and the global circulation. Researchers summarized the routine ARM observations from this two-year campaign to help quantify large-scale environmental controls on clouds and precipitation over an under-sampled Amazon basin region. Covering both wet and dry seasons, the study contrasted daily cycles of large-scale environmental conditions, cloud fractions classified by cloud types, their surface radiative effects, and associated precipitation. It also documented substantial increases in wet season cloud frequency, propensity for widespread precipitation, and precipitation accumulation. Researchers found that shallow cumulus clouds played a dominant role in affecting energy balance at the surface during both wet and dry seasons. Aircraft observations also showed the increased aerosol concentrations during the dry season reduced cloud particle sizes and increased cloud particle concentrations compared to the wet season, ultimately altering the impact of shallow clouds on the surface energy balance. The rich GoAmazon2014/15 data set supports future opportunities for process studies to better understand coupled cloud-aerosol interactions.
Contacts (BER PM)
Atmospheric System Research Program Manager
Atmospheric System Research Program Manager
Atmospheric Radiation Measurement Program Manager
Pacific Northwest National Laboratory
Brookhaven National Laboratory
This paper has been authored by employees of Brookhaven Science Associates, LLC, under contract no. DE-SC0012704 with the US Department of Energy (DOE).
Zhe Feng at the Pacific Northwest National Laboratory (PNNL) is supported by the US DOE, as part of the Atmospheric System Research (ASR) Program. The PNNL is operated for DOE by Battelle Memorial Institute under contract no. DE-AC05-76RL01830.
Work at the Lawrence Livermore National Laboratory (LLNL) was supported by the DOE ARM program and performed under the auspices of the US DOE by LLNL under contract no. DE-AC52-07NA27344.
Funding was also obtained from the US DOE, the São Paulo Research Foundation (FAPESP - 2009/15235-8), the Amazonas State University (UEA) and the Amazonas Research Foundation (FAPEAM - 062.00568/2014).
The work was conducted under scientific licenses 001030/2012-4, 001262/2012-2 and 00254/2013-9 of the Brazilian National Council for Scientific and Technological Development (CNPq).
Institutional support was provided by the Central Office of the Large Scale Biosphere Atmosphere Experiment in Amazonia (LBA), the National Institute of Amazonian Research (INPA), the National Institute for Space Research (INPE) and the Brazil Space Agency (AEB).
We also acknowledge the Atmospheric Radiation Measurement (ARM) Climate Research Facility, a user facility of the US DOE, Office of Science, sponsored by the Office of Biological and Environmental Research, and support from the ASR program of that office.
The GoAmazon2014/5 GOES-13 satellite retrievals were also supported by the US Department of Energy, Office of Biological and Environmental Research, Atmospheric System Research Program award DE-SC0000991.
Giangrande, S., Z. Feng, M. Jensen, J. Comstock, K. Johnson, T. Toto, M. Wang, C. Burleyson, N. Bharadwaj, F. Mei, L. Machado, A. Manzi, S. Xie, S. Tang, M. Silva Dias, R. de Souza, C. Schumacher, and S. Martin. "Cloud characteristics, thermodynamic controls and radiative impacts during the Observations and Modeling of the Green Ocean Amazon (GoAmazon2014/5) experiment." Atmospheric Chemistry and Physics, 17(23), (2018). [DOI: 10.5194/acp-17-14519-2017]
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
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)